diff --git a/application/applying.md b/application/applying.md deleted file mode 100644 index f4deb5983..000000000 --- a/application/applying.md +++ /dev/null @@ -1,3 +0,0 @@ -# Applying the model - -This page contains information needed to apply the model. diff --git a/application/ev-rebates.md b/application/ev-rebates.md deleted file mode 100644 index fa5d88d10..000000000 --- a/application/ev-rebates.md +++ /dev/null @@ -1,24 +0,0 @@ -# Electric Vehicle Rebates -One of the policies that SANDAG planners would like to test for the 2025 Regional Plan is providing rebates for low- and middle-income households to purchase electric vehicles. One of the variables in the vehicle type choice model is the [new purchase price](https://github.com/SANDAG/ABM/blob/ABM3_develop/src/asim/configs/resident/vehicle_type_choice_op4.csv#L12-L17) for a vehicle of a given age, body type, and fuel type. The way the EV rebate is implemented in ABM3 is by deducting the appropriate rebate value for plugin and battery vehicles if a household meets the criteria (based on percentage of the federal poverty level). To configure the rebate values and poverty level thresholds, [new constants](https://github.com/SANDAG/ABM/blob/ABM3_develop/src/asim/configs/common/constants.yaml#L290) were added to the common/constants.yaml configuration file. The constants fit into the policy as follows: - -| Fuel Type | `LowIncomeEVRebateCutoff` < Household Poverty Level <= `MedIncomeEVRebateCutoff` | Household Poverty Level <= `LowIncomeEVRebateCutoff` | -| --------- | -------------------------------------------------------------------------------- | ---------------------------------------------------- | -| BEV | `MedIncomeBEVRebate` | `LowIncomeBEVRebate` | -| PEV | `MedIncomePEVRebate` | `LowIncomePEVRebate` | - -For example, if the following policy were to be tested... - -| Fuel Type | 300-400% Federal Poverty Limit | 300% Federal Poverty Limit or lower | -| --------- | ------------------------------ | ----------------------------------- | -| BEV | $2,000 | $6,750 | -| PEV | $1,000 | $3,375 | - -...then the constants would need to be set as follows: -~~~ -LowIncomeEVRebateCutoff: 3 -MedIncomeEVRebateCutoff: 4 -LowIncomeBEVRebate: 6750 -LowIncomePEVRebate: 3375 -MedIncomeBEVRebate: 2000 -MedIncomePEVRebate: 1000 -~~~ diff --git a/application/flexible-fleets.md b/application/flexible-fleets.md deleted file mode 100644 index 85f359838..000000000 --- a/application/flexible-fleets.md +++ /dev/null @@ -1,67 +0,0 @@ -# Flexible Fleets -The of the five big moves defined in SANDAG's 2021 regional plan was [Flexible Fleets](https://www.sandag.org/projects-and-programs/innovative-mobility/flexible-fleets), which involves on-demand transit services. The [initial concept](https://www.sandag.org/-/media/SANDAG/Documents/PDF/regional-plan/2025-regional-plan/2025-rp-draft-initial-concept-2024-1-25.pdf) of the 2025 Regional Plan involves rapidly expanding these services, with many new services planned to be in operation by 2035. For this reason, it is important that these services be modeled by ABM3. There are two flavors of flexible fleets that were incorporated into ABM3, Neighborhood Electric Vehicles (NEV) and microtransit. A table contrasting these services is shown below. - -| Characteristic | NEV | Microtransit | -| --------------- | ------- | ------------ | -| Vehicle Size | Smaller | Larger | -| Service Area | Smaller | Larger | -| Operating Speed | Slower | Faster | - -## Incorporation into ABM3 - -Rather than creating new modes for flexible fleet services, microtransit and NEV were incorporated into existing modes. How this was done was dependent on whether the trip was a full flexible fleet trip, first-mile access to fixed-route transit*, or last-mile egress from fixed-route transit*. A table explaining how each of these trip types was incorporated into ABM3 is shown below. Further, a heirarchy of services is enforced. ActivitySim first checks if NEV is available (based on a new land use attribute), and if it is, it's assumed that NEV is used. If not, ActivitySim checks if microtransit is available (based on a corresponding land use attribute), and if it is, it's assumed that microtransit is used. If neither are available, ActivitySim looks at the other services that are already available. - -**For trips on the return leg of a tour the access and egress attributes are swapped* - -| | Full microtransit trip | First-mile access to fixed-route transit | Last-mile egress from fixed-route transit | -| ------------------------------------------------------------- | --------------------------------------------------- | ------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| What models allow for this type of trip? | Resident, Visitor, Crossborder | Resident | Resident, Visitor, Crossborder | -| Which mode is used? | TNC Shared | TNC to transit | All transit modes | -| How is the flexible fleet travel time factored into the trip? | The travel time is the full travel time of the trip | The travel time is added to the transit access time and a transfer is added | The travel time is added to the transit egress time and a transfer is added if the destination is further from the nearest transit stop than a user would be willing to walk (that distance is configurable) | -| How is the flexible fleet cost factored into the trip? | The cost is the full cost of the trip | It is assumed that flexible fleet services are free when used to access fixed-route transit | It is assumed that flexible fleet services are free when egressing from fixed-route transit | - -## New Attributes -Several new attributes were added to allow the user to configure how flexible fleet services are operated. These are all defined in the common [constants.yaml](https://github.com/SANDAG/ABM/blob/ABM3_develop/src/asim/configs/common/constants.yaml#L255-L273) file. Each attribute is defined as follow: - -| Attribute | Definition | Default value | -| -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- | --------------- | -| Speed | Assumed operating speed in miles per hour | MT: 30, NEV: 17 | -| Cost | Cost of using service in US Cents | 125 for both | -| WaitTime | Assumed time passengers wait to wait to use service in minutes | 12 for both | -| MaxDist | Maximum distance in miles that the service can be used | MT: 4.5, NEV: 3 | -| DiversionConstant | Additional travel time to divert for servicing other passengers | 6 for both | -| DiversionFactor | Time multiplier accounting for diversion to service other passengers | 1.25 for both | -| StartPeriod | Time period to start service (not yet implemented) | 9 for both | -| EndPeriod | Time period to end service (not yet implemented) | MT: 32, NEV: 38 | -| maxWalkIfMTAccessAvailable | Maximum disatance someone is willing to walk at the destination end if flexible fleet services are available (same for microtransit and NEV) | 0.5 | - -## Travel Time Calculation -### Direct Time -The flexible fleet travel time calculation is a two-step process. The first step is to calculate the time that it would take to travel from the origin to the destination* directly without any diversion to pick up or drop off any passengers. This is done by taking the maximum of the time implied by the operating speed and the congested travel time: - -$t_{\textnormal{direct}} = \textnormal{max}(60\times\frac{s}{d}, t_{\textnormal{congested}})$ - -where: - -$t_{\textnormal{direct}} = \textnormal{Direct flexible fleet travel time}$ - -$s = \textnormal{speed}$ - -$d = \textnormal{Distance from origin to destination (taken from distance skim)}$ - -$t_{\textnormal{congested}} = \textnormal{Congested travel time from origin to destination (taken from Shared Ride 3 time skim)}$ - -**When used to access fixed-route transit, the destination is the nearest transit stop to the trip origin. When used to egress from fixed-route transit, the origin is the nearest transit stop to the trip destination.* - -### Total Time -The second step of the travel time calculation was to account for diversion to pick up other passengers. These were based on guidelines used in a NEV pilot. The formula to calculated the total flexible fleet travel time is as follows: - -$t_{\textnormal{total}} = \textnormal{max}(t_{\textnormal{direct}}+c, \alpha\times t_{\textnormal{direct}})$ - -where: - -$t_{\textnormal{total}} = \textnormal{Total flexible fleet travel time}$ - -$c = \textnormal{DiversionConstant}$ - -$\alpha = \textnormal{DiversionFactor}$ diff --git a/application/landuse-prep.md b/application/landuse-prep.md deleted file mode 100644 index b64eb7d76..000000000 --- a/application/landuse-prep.md +++ /dev/null @@ -1,5 +0,0 @@ -# Land-Use Data Preparation - -//TODO: Describe how to prepare land-use data. - -Describe how to update parking costs, enrollment data. diff --git a/application/micromobility.md b/application/micromobility.md deleted file mode 100644 index baa421ff5..000000000 --- a/application/micromobility.md +++ /dev/null @@ -1,3 +0,0 @@ -# Micromobility - -//TODO: Describe how to run micromobility policy tests diff --git a/application/network-coding.md b/application/network-coding.md deleted file mode 100644 index b73c925e1..000000000 --- a/application/network-coding.md +++ /dev/null @@ -1,3 +0,0 @@ -# Network Coding - -//TODO: Describe network attributes, how to code network \ No newline at end of file diff --git a/application/population-synthesis.md b/application/population-synthesis.md deleted file mode 100644 index 4963af7e4..000000000 --- a/application/population-synthesis.md +++ /dev/null @@ -1,3 +0,0 @@ -# Population Synthesis - -//TODO: Describe population synthesis procedure, how to modify inputs and construct new future-year synthetic population \ No newline at end of file diff --git a/application/scenario-manager.md b/application/scenario-manager.md deleted file mode 100644 index b233804da..000000000 --- a/application/scenario-manager.md +++ /dev/null @@ -1,18 +0,0 @@ -# Scenario manager - -ABM3 uses a python module as the scenario manager. The job of this scenario manager is updating the parameters used throughout the model to match a specific scenario’s definition and needs. A number of these parameters including auto operating cost, taxi and TNC fare, micromobility cost, and AV ownership penetration are usually assumed to change by forecast year or scenario. - -Manually changing these parameters requires the model user to know where each parameter is located, and individually changing them according to the scenario forecast values. A scenario manager, therefore, can be a convenient and efficient tool to automate this process. - -The ABM3 Scenario Manager reads in a CSV input file (located under ```input/parametersByYears.csv```) containing the parameter values for each scenario, and updates the associated parameters in the ActivitySim config files. A snapshot of this input parameter CSV file is shown below, where each row is associated with a specific scenario year/name. The parameter names used here can either be identical to the parameter names used in ActivitySim, or different. In case the parameter names are different, a separate file is used to map the parameters names between the input CSV and ActivitySim config files. - - -| Scenario Year | AOC fuel | AOC maintenance | Taxi baseFare | Taxi costPerMile | Taxi costPerMinute | -| ------------- | -------- | --------------- | ------------- | ---------------- | ----------------- | -| 2012 | 13.5 | 6.3 | 1.78 | 1.87 | 0.08 | -| 2014 | 12.9 | 6.3 | 1.78 | 1.87 | 0.08 | -| 2015 | 19.5 | 6.2 | 1.78 | 1.87 | 0.08 | -| 2016 | 10.7 | 5.6 | 1.78 | 1.87 | 0.08 | -| 2017 | 10.8 | 5.5 | 1.78 | 1.87 | 0.08 | - -The scenario manager is run as part of the model setup in the Master Run tool before any ActivitySim model is run (usually only in the first iteration of the run). Model user can choose to run or skip this step, although it is highly recommended to run with each run to ensure correct parameters. diff --git a/cvm.md b/cvm.md deleted file mode 100644 index 71bc123ba..000000000 --- a/cvm.md +++ /dev/null @@ -1,7 +0,0 @@ -# Commercial Vehicle Model - -## Design - -## Inputs - -## Outputs diff --git a/design/airport.md b/design/airport.md deleted file mode 100644 index ec4f6a3dc..000000000 --- a/design/airport.md +++ /dev/null @@ -1,121 +0,0 @@ -# Airport Ground Access Models - -There are two airport ground access models - one for San Diego International Airport and one for the Crossborder Express terminal which provides access to Tijuana International Airport from the United States. Both models use the same structure and software code, though the parameters that control the total number of airport travel parties, off-airport destination, mode, arrival and departure times, and other characteristics, vary for each airport according to survey and airport-specific data. -The airport ground access model simulates trips to and from the airport for residents, visitors, and external travelers. These trips are generated by arriving or departing passengers and are modeled as tours within the ActivitySim framework. A post processing script also generates trips to serve passengers who require a pickup or dropoff at the airport. For example, a passenger who is picked up at the airport generates two trips; one trip to the airport by the driver to pick up the air passenger(s), and another trip from the airport with the driver and the air passenger(s). -It is important to note that, to work within the ActivitySim framework, the airport trips must be modeled as tours, rather than being generated directly as in the previous model. These tours are assigned an origin at the airport MGRA. During the stop frequency step of ActivitySim, a trip is assigned to the appropriate leg of the tour (either to or from the airport) while the opposite leg is not assigned any trips (referred to as the ‘dummy leg’). Passengers who are leaving on a departing flight and traveling to the airport are considered "inbound," while arriving passengers are considered "outbound". - -The overall design of the model is shown in the figure below. - -![](../images/design/airport_model_design.png) - -1. Tour Enumeration: A list of airport travel parties is generated from input enplanements and transferring passenger rates, as well as distributions that describe the share of travel parties by purpose (business versus personal), household income, and party size. -2. Tour Level Models - - 2.1 Tour Scheduling Probabilistic: The tour scheduling model uses a probabilistic draw of the scheduling distribution. This model assigns start and end times to the tour. This is important because it will also serve as the schedule model for the final airport trips. In ActivitySim, trips are scheduled based on the tour schedule. If there is only one trip per leg on the tour (such as our case here) the trip is assigned the tour start/end time. - - 2.2 Tour Destination Choice: The destination choice model chooses the non-airport end of the airport trips. Each tour is set with an origin at the airport MGRA. The tour destination model of ActivitySim is used to choose the non-airport end of the trip. The utility equation includes the travel distance, and the destination size terms. ActivitySim destination choice framework requires a mode choice log sum. A dummy tour mode choice log sum was created which generates a value of zero for every destination using the ‘tour_mode_choice.csv’ and ‘tour_mode_choice.yml’ file. This is a work around to prevent ActivitySim from crashing and not having to include the tour mode choice log sum in the destination choice model. - - 2.3 Stop Frequency Choice: The stop frequency model is where the trip table is first created. The pre-processor tags each tour with a direction of ‘inbound’ or ‘outbound’ according to whether the tour is a departing or arriving passenger. For the Airport Ground Access model, inbound tours are tagged with zero outbound trips and -1 inbound trips (and the opposite is true for outbound tours: -1 outbound trips and 0 inbound trips). The 0 signifies that no intermediate stops are made; this leg of the tour will only have one trip. The -1 signifies that no trip is made at all on that leg. Using the -1 allows us to create ‘half-tours’ where only one leg of the tour is recorded as a trip. -3. Trip Level Models - - 3.1 Trip Departure Choice: The trip scheduling model assigns depart times for each trip on a tour. ActivitySim requires trip scheduling probabilities; however, these are not used in this implementation since there is only one trip on any given tour leg. This means the trips will be assigned the tour scheduling times which were determined in the tour scheduling model. The trip scheduling probabilities file is just a dummy file. - - 3.2 Trip Mode Choice: Each trip is assigned a trip mode; in the Airport Ground Access Model, trip mode refers to the airport arrival mode which simultaneously predicts the arrival mode and the location which the passenger uses to access that model. The arrival modes are shown in the table below. The trip mode choice yaml file contains detailed variables associated with each trip mode. For example, each parking location is given an MGRA location, a walk time, a wait-time, and a cost. If a parking location MGRA is set to -999 it is assumed to be unavailable and will not be in the choice set. The pre-processor in this step stores all values of skims from the trip origin to each of the access modes destinations along with any associated costs. Costs include parking fees per day, access fees, fares, and rental car charges. - Employees are not fed into the trip mode choice model. Instead, if a transit share is specified in the employee park file, that percentage of employees will be assigned ‘Walk Premium’ mode in the pre-processor. Otherwise, employees are all assigned ‘Walk’ mode from the employee parking lot to the terminal. - - 3.3 Airport Returns: Airport trips where the party is dropped of curbside or parked and escorted are assumed to also have the driver make a return trip to the non-airport location. This procedure is done as a post-processing step after mode choice and before trip tables are written out. An ‘airport_returns.yml’ file takes a user setting to determine which trip modes will include a return trip. These trips records are flagged and duplicated. The duplicated trips swap the origin and destination of the original trip and are assigned a unique trip id. These trips are tagged with ‘trip_num =2’ so they are easily sorted in any additional processing (such as for writing trip matrices). - - 3.4 Write trip matrices: The write trip matrices step converts the trip lists into vehicle trip matrices. The matrices are segmented by trip mode and value of time bins. The vehicle trip modes in the matrices include SOV, HOV2, HOV3+, Taxi, and TNC-single. Value of time segmentation is either low, medium, or high bins based on the thresholds set in the model settings. - -The major tour modes are shown below: -```mermaid -flowchart TD - subgraph four - direction LR - E[Ride-Hail] --> E1[Taxi] - end - subgraph three - direction LR - D[Transit] --> D1[Walk Access] - %% D --> D2[PNR Access] - D --> D3[KNR Access] - D --> D4[TNC Access] - - D1 --> D11[Local Only] - D1 --> D12[Premium Only] - D1 --> D13[Mixed] - - D3 --> D31[Local Only] - D3 --> D32[Premium Only] - D3 --> D33[Mixed] - - D4 --> D41[Local Only] - D4 --> D42[Premium Only] - D4 --> D43[Mixed] - end - subgraph two - direction LR - C[Active] --> C1[Walk] - end - - subgraph one - direction LR - B[Auto] --> B1[Drive-alone]; - B --> B2[Shared 2]; - B --> B3[Shared 3+]; - end - A[Tour Mode] --> one; - A --> two; - A --> three; - A --> four; - - classDef group1 fill:#f75f5f,stroke:#333,stroke-width:4px,font-size:26px,font-weight:bold;wrap - classDef group2 fill:#ffd966,stroke:#333,stroke-width:2px,font-size:20px;wrap - classDef group3 fill:#bdabf0,stroke:#333,stroke-width:2px,font-size:18px;wrap - - classDef hiddenTitle color:transparent; - class one,two,three,four hiddenTitle; - - class A group1; - class B,C,D,E group2; - class B1,B2,B3,C1,C2,C3,C4,D1,D2,D3,D4,E1,E2,E3,D11,D12,D13,D21,D22,D23,D31,D32,D33,D41,D42,D43 group3; -``` - -#### Airport Ground Access Model Trip Arrival Modes - -| **Arrival Mode** | **Description** | -| --- | --- | -| Park Location 1 | Party parks personal vehicle at parking location 1. | -| | | -| Park Location 2 | Party parks personal vehicle at parking location 2. | -| Park Location 3 | Party parks personal vehicle at parking location 3. | -| Park Location 4 | Party parks personal vehicle at parking location 4. | -| Park Location 5 | Party parks personal vehicle at parking location 5. | -| | | -| | | -| Curb Location 1 | Party is dropped off or picked up by another driver at curbside location 1. | -| Curb Location 2 | Party is dropped off or picked up by another driver at curbside location 2. | -| Curb Location 3 | Party is dropped off or picked up by another driver at curbside location 3. | -| Curb Location 4 | Party is dropped off or picked up by another driver at curbside location 4. | -| Curb Location 5 | Party is dropped off or picked up by another driver at curbside location 5 | -| Park and Escort | Party is driven in personal vehicle, parks on-site at the airport and is escorted to/from airport. | -| Rental Car | Party arrives/departs by rental car. | -| Shuttle Van | Party takes shuttle van. | -| Hotel Courtesy | Party takes hotel courtesy transportation. | -| Ridehail Location 1 | Party arrives\departs using ridehail at ridehail location 1 | -| Ridehail Location 2 | Party arrives\departs using ridehail at ridehail location 2 | -| | | -| Taxi Location 1 | Party arrives\departs using taxi at taxi location 1 | -| Taxi Location 2 | Party arrives\departs using taxi at taxi location 2 | -| Walk Local | Party arrives\departs using walk-local bus | -| Walk Premium | Party arrives\departs using walk-premium transit | -| Walk Mix | Party arrives\departs using walk-local plus premium transit | -| KNR Local | Party arrives\departs using KNR-local bus | -| KNR Premium | Party arrives\departs using KNR-premium transit | -| KNR Mix | Party arrives\departs using KNR-local plus premium transit | -| TNC Local | Party arrives\departs using TNC-local bus | -| TNC Premium | Party arrives\departs using TNC-premium transit | -| TNC Mix | Party arrives\departs using TNC-local plus premium transit | -| Walk | Party arrives\departs using walk | - -For more information on the Air Ground Access Travel Model see technical documentation. \ No newline at end of file diff --git a/design/crossborder.md b/design/crossborder.md deleted file mode 100644 index 5253dd5a9..000000000 --- a/design/crossborder.md +++ /dev/null @@ -1,122 +0,0 @@ -# Crossborder Model - -The Cross-Border Travel Model predicts travel made by residents of Mexico within San Diego County. It predicts the border crossing point of entry as well as all trips made within the county. The model is limited to simulating travel made by Mexican residents who return to Mexico within the simulation day. Cross-border travel not captured by the Cross-Border Model includes: - -* Residents of San Diego County who travel to/from Mexico. This travel is represented -by the resident travel model. -* Residents of Mexico (including U.S. citizens) who travel into San Diego County and who -do not return to Mexico at the end of the day. This travel is represented in the overnight -visitor travel model. -* Travel between points of entry through San Diego County to other U.S. destinations. This -travel is represented by the external-external travel model. -* Commercial vehicle travel to/from points of entry. This travel is represented by the -commercial vehicle model. - -The overall design of the model is shown in the figure below. - -![](../images/design/crossborder_model_design.png) - -#### Crossborder Model Purpose Definitions -There are five activity purposes in the cross-border travel demand model: - * Work: Any activity involving work for pay. - * School: Pre-k school, K-12, college/university, or trade school. - * Shop: Shopping at retail, wholesale, etc. - * Visit: Visiting friends or family - * Other: A broad category including eating out, medical appointments, recreational activities, etc. - -Note that home activities are not listed, since we do not model activities south of the border. - -#### Crossborder Model Mode Definitions - -The major tour modes are shown below: -```mermaid -flowchart TD - subgraph three - direction LR - D[Transit] --> D1[Walk Access] - - D1 --> D11[Local Only] - D1 --> D12[Premium Only] - D1 --> D13[Mixed] - end - subgraph two - direction LR - C[Active] --> C1[Walk] - end - - subgraph one - direction LR - B[Auto] --> B1[Drive-alone]; - B --> B2[Shared 2]; - B --> B3[Shared 3+]; - end - A[Tour Mode\Border Crossing Mode] --> one; - A --> two; - A --> three; - - classDef group1 fill:#f75f5f,stroke:#333,stroke-width:4px,font-size:26px,font-weight:bold;wrap - classDef group2 fill:#ffd966,stroke:#333,stroke-width:2px,font-size:20px;wrap - classDef group3 fill:#bdabf0,stroke:#333,stroke-width:2px,font-size:18px;wrap - - classDef hiddenTitle color:transparent; - class one,two,three hiddenTitle; - - class A group1; - class B,C,D,E group2; - class B1,B2,B3,C1,C2,C3,C4,D1,D11,D12,D13 group3; -``` - -The model has the following mode types at the trip level: - * Drive-alone: Single occupant private vehicle - * Shared 2: A private vehicle with exactly two passengers - * Shared 3+: A private vehicle with three or more passengers - * Walk: Walk mode - * Bike: Bike mode - * Walk-transit: Walk access to transit. There are three sub-types of transit: Local only, - premium only, local + premium (which includes both local and premium services in the - transit path) - * Taxi: Door-to-door taxi trip - * Single-pay TNC: Door-to-door TNC trip with a single payer (e.g. UberX) - * Shared-pay TNC: Stop-to-stop TNC trip with potentially multiple payers (e.g. UberPool) - -We also model tour mode, which is the mode used to cross the border. These modes include -drive-alone, shared 2, shared 3+ and walk. We assume that anyone crossing by bus or taxi is -similar to walk, since they do not have access to a personal vehicle for the rest of their travel in -San Diego County. - -We also classify border crossings by lane type: general purpose, SENTRI, and Ready. We -assume that the use of these lanes is related to the border crossing party; we attribute each party with SENTRI or Ready availability. The proportion of total border crossing parties with access to SENTRI and Ready lanes are based on observed survey data, pooled across all stations. This data is used to simulate the availability of the lane to the travel party. Each lane crossing type is related to the wait time that the travel party experiences at each border crossing station by mode. - -Below is a general description of the model structure. - -1. Tour Enumeration: A list of person-tours is created by first cross-multiplying the input total -person tours with the share of tours by pass type, then expanding tours by pass type to tours -by pass type and purpose. -1. Tour Level Models - 2.1 Time-of-day Choice: Each person-tour is assigned an outbound and return half-hour - period. - - 2.2 Primary Destination and Station Choice: Each border crossing person-tour chooses a - primary destination MGRA and border crossing station. - - 2.3 Border Crossing Mode Choice: Each person-tour chooses a border crossing tour mode. - -2. Wait Time Model - - 3.1. Wait time model: Calculate wait time based on demand at each POE from model 2.2 - - 3.2. Convergence check: If max iterations reached (currently 3), goto Stop and Trip level models, else goto Model 2.2 -3. Stop and Trip Level Models - 4.1 Stop Frequency Choice: Each person-tour is assigned number of stops by half-tour (outbound, return). - - 4.2 Stop Purpose Choice: Each stop is assigned a stop purpose (consistent with the tour purposes). - - 4.3 Trip Departure Choice: Each trip is assigned a half-hourly time period. - - 4.4 Stop Location Choice: Each stop chooses an MGRA location. - - 4.5 Trip Mode Choice: Each trip is assigned a trip mode. - - 4.6 Trip Assignments: Trips are assigned to networks, along with resident and other special market trip tables, and skims are created for the next iteration of the model. - -For more information on the Crossborder Travel Model see technical documentation. \ No newline at end of file diff --git a/design/design.md b/design/design.md deleted file mode 100644 index 5a50ee459..000000000 --- a/design/design.md +++ /dev/null @@ -1,13 +0,0 @@ -# Model Design - -The ABM3 model system is primarily based on the [ActivitySim](https://research.ampo.org/activitysim/) platform; ActivitySim is used to model resident travel, cross-border travel, overnight visitor travel, airport ground access travel, and commercial vehicle travel including light, medium, and heavy commercial vehicles. Aggregate models are used to model external-internal travel (from external stations other than the U.S./Mexico border crossing) and through travel. The model system relies on [EMME](https://www.bentley.com/software/emme/) software for network processing, skimming, and assignment. Models are mostly implemented in [Python](https://www.python.org/), and some models are implemented in [Java] (https://www.java.com/en/). - -The overall design of the model is shown in the figure below. - -![](../images/design/overall_model_design.png) - -The system starts by performing initial input processing in EMME. This includes building transport networks and scenarios for skimming and assignment. An initial set of skims are created based on input trip tables (e.g. warm start). Then disaggregate choice models in ActivitySIm are run, including the resident model, the crossborder travel model, two airport ground access models, the overnight visitor model, and the commercial vehicle model. Next auxiliary models are run; the taxi/TNC routing model and the autonomous vehicle intra-household allocation model are run in Java. Aggregate external-internal and through travel models are run in Python. After all models are run, trip tables are built from the result and assigned to transport networks. A check is made to determine whether the model has reached convergence (currently this is set to three feedback iterations). If convergence is reached, outputs are processed for export to the SANDAG Datalake for reporting summaries. If not, speeds from assignment are averaged using method of successive averages, and skims are rebuilt for the next iteration. The model system is then re-run with the updated skims. - -ActivitySim is used to represent all internal travel and internal-external made by residents of the SANDAG region (modeled area). The decision-makers in the model system include both persons and households. These decision-makers are created (synthesized) for each simulation year and land-use scenario, based on Census data and forecasted distributions of households and persons by key socio-economic categories. A similar but simplified method is used to generate disaggregate populations for cross-border, airport ground access, and overnight visitor models. The decision-makers are used in the subsequent discrete-choice models in a microsimulation framework where a single alternative is selected from a list of available alternatives according to a probability distribution. The probability distribution is generated from a logit model which considers the attributes of the decision-maker and the attributes of the various alternatives. The application paradigm is referred to as Monte Carlo simulation, since a random number draw is used to select an alternative from the probability distribution. The decision-making unit is an important element of model estimation and implementation and is explicitly identified for each model specified in the following sections. - -A key advantage of using the micro-simulation approach is that there are essentially no computational constraints on the number of explanatory variables that can be included in a model specification. However, even with this flexibility, the model system will include some segmentation of decision-makers. Segmentation is a useful tool to both structure models (for example, each person type segment could have their own model for certain choices) and to characterize person roles within a household. Segments can be created for persons as well as households. diff --git a/design/resident.md b/design/resident.md deleted file mode 100644 index 30e8ec9fb..000000000 --- a/design/resident.md +++ /dev/null @@ -1,92 +0,0 @@ -# Resident Model - -The resident model structure is based on the Coordinated Travel Regional Activity-based Modeling Platform (CT-RAMP). The figure below shows the resident model structure. In order to understand the flow chart, some definitions are required. These are described in more detail below. - -- Tour: A sequence of trips that start and end at an anchor location. In ActivitySim, anchors are home or work. -- Primary destination: The “main” activity of the tour; this activity determines the tour purpose. It also divides the tour into two "legs"; the sequence of trips from the anchor location to the primary destination is the outbound leg, and the sequence of trips from the primary destination back to the anchor location is the inbound or return leg. -- Mandatory activity: Work or school -- Non-mandatory activity: Any out of home activity that is not work or school, including maintenance activities such as shopping as well as discretionary activities such as out-of-home recreation and eating out. -- Fully joint tour: A tour in which two or more household members travel together to all out-of-home activity locations and return home together. In other words, no household member is picked-up or dropped-off en route. -- Intermediate stop: An out-of-home activity location on the tour other than the anchor location or the primary destination. Intermediate stops are made on the way from the anchor location to the primary destination (outbound) or on the way from the primary destination back to the anchor location (inbound). -- Tour mode: The “main mode” or “preferred mode” of the tour. This is an abstract concept used categorize the tour with respect to accessibility and constrain the availability of modes for trips on the tour to ensure some consistency of modes used for each trip. - -The resident model design is shown below. - -![](../images/design/resident_model_design.png) - -The first model in the sequence is disaggregate accessibilities. This is a recent addition to ActivitySim in which the tour destination choice model is run for a prototypical sample population covering key market segments and destination choice logsums from the model are written out for each tour in the population. These destination choice logsums are then merged with the actual synthetic population and used as accessibility variables in downstream models such as auto ownership, coordinated daily activity patterns, and tour frequency. are mandatory location choice; this model is run for all workers and students regardless of whether they attend work or school on the simulated day. - -Next a set of long-term and mobility models are run. The first model in the sequence predicts whether an autonomous vehicle is owned by the household. This model conditions the next model, which predicts the number of autos owned. If an autonomous vehicle is owned, multiple cars are less likely. Next, the mandatory (work and school) location choice models are run. The work location choice models includes a model to predict whether the worker has a usual out-of-home work location or exclusively works from home. If the worker chooses to work from home, they will not generate a work tour. An external worker identification model determines whether each worker with an out-of-home workplace location works within the region or external to the region. If they work external to the region, the external station is identified. Any primary destination of any work tours generated by the worker will be the external station chosen by this model. A work location choice model predicts the internal work location of each internal worker, and a school location choice model predicts the school location of each student. - -Next, a set of models predicts whether workers and students have subsidized transit fares and if so, the percent of transit fare that is subsidized, and whether each person in the household owns a transit pass. A vehicle type choice model then runs, which predicts the body type, fuel type, and age of each vehicle owned by the household; this model was extended to predict whether each vehicle is autonomous, conditioned by the autonomous vehicle ownership model. - -Next, we predict whether each household has access to a vehicle transponder which can be used for managed lane use. We assume that all vehicles built after a certain year (configurable by the user) are equipped with transponders. Next we predict whether each worker has subsidized parking available at work. Finally we predict the telecommute frequency of each worker, which affects downstream models including the daily activity pattern model, the non-mandatory tour frequency model, and stop frequency models. - -Next the daily and tour level models are run. The first daily model is the daily activity pattern model is run, which predicts the general activity pattern type for every household member. Then Mandatory tours are generated for workers and students, the tours are scheduled (their location is already predicted by the work/school location choice model), a vehicle availability model is run that predicts which household vehicle would be used for the tour, and the tour mode is chosen. After mandatory tours are generated, a school pickup/dropoff model forms half-tours where children are dropped off and/or picked up at school. The model assigns chaperones to drive or ride with children, groups children together into “bundles” for ride-sharing, and assigns the chaperone task to either a generated work tour or generates a new tour for the purpose of ridesharing. Fully joint tours – tours where two or more household members travel together for the entire tour - are generated at a household level, their composition is predicted (adults, children or both), the participants are determined, the vehicle availability model is run, and a tour mode is chosen. The primary destination of fully joint tours is predicted, the tours are scheduled, the vehicle availability model is run, and a tour mode is chosen. Next, non-mandatory tours are generated, their primary destination is chosen, they are scheduled, the vehicle availability model is run, and a tour mode is chosen for each. At-work subtours are tours that start and end at the workplace. These are generated, scheduled (with constraints that the start and end times must nest within the start and end time of the parent work tour), a primary destination is selected, the vehicle availability model is run, and a tour mode is chosen. - -The major tour modes are shown below: -```mermaid -flowchart TD - subgraph four - direction LR - E[Ride-Hail] --> E1[Taxi] - E --> E2[Single-pay TNC] - E --> E3[Shared TNC]; - end - subgraph three - direction LR - D[Transit] --> D1[Walk Access] - D --> D2[PNR Access] - D --> D3[KNR Access] - D --> D4[TNC Access] - - D1 --> D11[Local Only] - D1 --> D12[Premium Only] - D1 --> D13[Mixed] - - D2 --> D21[Local Only] - D2 --> D22[Premium Only] - D2 --> D23[Mixed] - - D3 --> D31[Local Only] - D3 --> D32[Premium Only] - D3 --> D33[Mixed] - - D4 --> D41[Local Only] - D4 --> D42[Premium Only] - D4 --> D43[Mixed] - end - subgraph two - direction LR - C[Active] --> C1[Walk] - C --> C2[Bike] - C --> C3[E-Scooter] - C --> C4[E-Bike] - end - - subgraph one - direction LR - B[Auto] --> B1[Drive-alone]; - B --> B2[Shared 2]; - B --> B3[Shared 3+]; - end - A[Tour Mode] --> one; - A --> two; - A --> three; - A --> four; - - classDef group1 fill:#f75f5f,stroke:#333,stroke-width:4px,font-size:26px,font-weight:bold;wrap - classDef group2 fill:#ffd966,stroke:#333,stroke-width:2px,font-size:20px;wrap - classDef group3 fill:#bdabf0,stroke:#333,stroke-width:2px,font-size:18px;wrap - - classDef hiddenTitle color:transparent; - class one,two,three,four hiddenTitle; - - class A group1; - class B,C,D,E group2; - class B1,B2,B3,C1,C2,C3,C4,D1,D2,D3,D4,E1,E2,E3,D11,D12,D13,D21,D22,D23,D31,D32,D33,D41,D42,D43 group3; -``` - - -At this point, all tours are generated, scheduled, have a primary destination, and a selected tour mode. The next set of models fills in details about the tours - number of intermediate stops, location of each stop, the departure time of each stop, and the mode of each trip on the tour. Finally, the parking location of each auto trip to the central business district (CBD) is determined. -After the model is run, the output files listed above are created. The trip lists are then summarized into origin-destination matrices by time period and vehicle class or transit mode and assigned to the transport network. \ No newline at end of file diff --git a/design/visitor.md b/design/visitor.md deleted file mode 100644 index 51436629d..000000000 --- a/design/visitor.md +++ /dev/null @@ -1,82 +0,0 @@ -# Overnight Visitor Model -The Overnight Visitor Model simulates trips of visitors staying overnight in hotels, motels, short-term vacation rentals, and with friends and family. The trips are modeled as part of tours that begin and end at the place of lodging. However, unlike the resident model, the Overnight Visitor Model does not utilize a 24-hour activity schedule. Therefore it can be thought of as a simpler, tour-based model. Once each tour is generated, it is scheduled independently. The model uses the same time periods and modes as the resident model. -The overall design of the model is shown in the figure below. - -![](../images/design/visitor_model_design.png) - -1. Tour Enumeration: A list of visitor parties is generated from the input household data and hotel room inventory at the MGRA level. Visitor travel parties by segment (business versus personal) are calculated based on separate rates for hotels and for households. Visitor parties are generated by purpose based on tour rates by segment, then attributed with household income and party size based on input distributions. There are three purposes in the Overnight Visitor model: - - * Work: Business travel made by business visitors. - * Dining: Travel to food establishments for both business and personal visitors. - * Recreational: All other non-work non-food related activities. - -2. Tour Level Models - - 2.1 Tour Scheduling Probabilistic: The tour scheduling model uses a probabilistic draw of the scheduling distribution. This model assigns start and end times to the tour. If there is only one trip per leg on the tour, the trip is assigned the tour start/end time. - - 2.2 Tour Destination Choice: The destination choice model chooses the MGRA of the primary activity location on the tour. - - 2.3 Tour Mode Choice: The tour mode choice model determines the primary mode of the tour. - -3. Stop Level Models - - 3.1 Stop Frequency Choice: The stop frequency model predicts the number of stops by direction based on input distributions that vary by tour purpose. - - 3.2 Stop Purpose: The stop purpose model chooses the activity purpose of each intermediate stop based on input distributions that vary according to tour purpose. - - 3.3 Stop Location Choice: The location choice model chooses the MGRA for each intermediate stop on the tour. - -4. Trip Level Models - - 4.1 Trip Departure Choice: The trip scheduling model assigns depart times for each trip on a tour based on input distributions that vary by direction (inbound versus outbound), stop number, and number of periods remaining on the tour. - - 4.2 Trip Mode Choice: Each trip is assigned a trip mode, consistent with the modes in the resident model. - - 4.3 Trip Assignment: Trips are aggregated by time of day, mode occupancy, value-of-time, and origin-destination TAZ and assigned simultaneously with other trips. - -The major tour modes are shown below: -```mermaid -flowchart TD - subgraph four - direction LR - E[Ride-Hail] --> E1[Taxi] - E --> E2[Single-pay TNC]; - end - subgraph three - direction LR - D[Transit] --> D1[Walk Access] - - D1 --> D11[Local Only] - D1 --> D12[Premium Only] - D1 --> D13[Mixed] - end - subgraph two - direction LR - C[Active] --> C1[Walk] - end - - subgraph one - direction LR - B[Auto] --> B1[Drive-alone]; - B --> B2[Shared 2]; - B --> B3[Shared 3+]; - end - A[Tour Mode] --> one; - A --> two; - A --> three; - A --> four; - - classDef group1 fill:#f75f5f,stroke:#333,stroke-width:4px,font-size:26px,font-weight:bold;wrap - classDef group2 fill:#ffd966,stroke:#333,stroke-width:2px,font-size:20px;wrap - classDef group3 fill:#bdabf0,stroke:#333,stroke-width:2px,font-size:18px;wrap - - classDef hiddenTitle color:transparent; - class one,two,three,four hiddenTitle; - - class A group1; - class B,C,D,E group2; - class B1,B2,B3,C1,C2,C3,C4,D1,D2,D3,D4,E1,E2,E3,D11,D12,D13,D21,D22,D23,D31,D32,D33,D41,D42,D43 group3; - -``` - -For more information on the Overnight Visitor Travel Model see technical documentation. \ No newline at end of file diff --git a/faq.md b/faq.md deleted file mode 100644 index 540e8fefd..000000000 --- a/faq.md +++ /dev/null @@ -1,13 +0,0 @@ -# FAQs - -## How many ABM versions does SANDAG maintain? -There are four released ABM versions - ABM1, ABM2, ABM2+, and ABM3. - -## Who uses the SANDAG ABM and what for? -The SANDAG ABM is used by SANDAG and many other public and private entities in the San Diego region. These entities include the City of San Diego and other local jurisdictions, Caltrans District 11, San Diego Metropolitan Transit System, North County Transit District, and private developers. Typical ABM applications include analysis for regional planning, air quality conformity, corridor studies, and land use development impact studies. - -## What model components does the SANDAG ABM have? -The SANDAG ABM is a suite of models covering various travel demand markets in the San Diego region. The microsimulation model components include a San Diego resident model, a commercial vehicle model, a Mexican resident crossborder model, a visitor model, a San Diego International Airport ground access model, a Cross-Border Express model serving Tijuana International Airport, and a special event model. The aggregate model components include an external heavy truck model and external trip models. - -## What is the base year of the SANDAG ABM? -ABM2 has a base year of 2022. ABM1 base year was 2012 and both ABM2 and ABM2+ have a base year of 2016. diff --git a/index.md b/index.md deleted file mode 100644 index dae30f682..000000000 --- a/index.md +++ /dev/null @@ -1,14 +0,0 @@ -# SANDAG ABM3 - -Welcome to the SANDAG Activity-Based Travel Model documentation site! - - -## Introduction - -This website describes the travel demand modeling system developed by the San Diego Association of Governments (SANDAG). SANDAG plans for many complex mobility issues facing the San Diego region, including development of the Regional Plan. Transportation models are complex analysis tools used to provide transportation planners and policymakers with information to help allocate scarce resources fairly and equitably. As we plan for the future, models are used to forecast potential future scenarios of where people will live and how they will travel. They are the principal tool used for alternatives analysis. - -The SANDAG transportation model is an activity-based model (ABM). It simulates individual and household transportation decisions that make up their daily travel. This includes all trips people make on a daily basis, such as to work, school, shopping, healthcare, and recreation. An ABM provides a controlled, analytical platform so that different inputs and alternatives can be evaluated to predict whether, when, and how this travel occurs. SANDAG ABM accounts for a variety of different weekday travel markets in the region, including San Diego region resident travel, travel by Mexico residents and other travelers crossing San Diego County’s borders, visitor travel, airport passengers at both the San Diego International Airport and the Cross Border Xpress bridge to the Tijuana International Airport, and commercial travel. - -The most recent version of the SANDAG ABM is referred to as “ABM3”, and was developed for use in the 2025 Regional Plan. ABM3 is a significant enhancement from ABM2+ which was used for the 2021 Regional Plan. All of the passenger demand models in ABM2+ were converted from CT-RAMP to [ActivitySim](https://research.ampo.org/activitysim), including resident travel, cross-border travel, visitor travel, and airport travel. The internal-external travel component is now fully integrated with the resident model. The model was also enhanced to improve the representation of household and person-based mobility, vehicle fleet ownership, transit, shared and private micro-mobility, and micro-transit. Many of the model components were re-estimated using household survey data collected in 2022, and all model components were re-calibrated to base-year 2023 conditions. A new disaggregate commercial vehicle model was developed based upon a 2020 commercial vehicle survey, and implemented in ActivitySim. - -This website includes a description of the model system, how to set up and run the models, and a description of model inputs and outputs. Some aspects of the site are a work-in-progress, so we recommend that you check in often, and share your thoughts on ways to improve the site with SANDAG Transportation Modeling staff. Thank you! diff --git a/inputs.md b/inputs.md deleted file mode 100644 index 535e6b481..000000000 --- a/inputs.md +++ /dev/null @@ -1,1957 +0,0 @@ -# ABM3 Model Inputs - -The main inputs to ABM3 include the transportation network, land-use data, synthetic population data, parameters files, and model specifications. Outputs include a set of files that describe travel decisions made by all travel markets considered by the model (residents, overnight visitors, airport ground access trips, commercial vehicles and trucks, Mexico residents traveling in San Diego County, and travel made by all other non-residents into and through San Diego County). - -### File Types - -There are several file types used for model inputs and outputs. They are denoted by their extension, as listed in the table below. - -| **Extension** | **Format** | -| --- | --- | -| .log, .txt | Text files created during a model run containing logging results. | -| .yaml | Text files used for setting properties that control ActivitySim or some other process. | -| .csv | Comma-separated value files used to store model parameters, input or output data. | -| .omx | Open matrix format files used to store input or output trip tables or skims | -| .h5 | HDF5 files, used to store pipeline for restarting ActivitySim | -| .shp (along with other files - .cpg, .dbf, .prj, .shx) | ArcGIS shapefiles and associated files | -| .html | Hypertext markup language files, open in web browser | -| .png | Portable network graphics file, open in web browser, Microsoft photos, or third-party graphics editor | - -## Model Inputs - -The table below contains brief descriptions of the input files required to execute the SANDAG ABM3. - -| **File Name** | **Purpose** | **File Type** | **Prepared By** | -| --- | --- | --- | --- | -| **Land Use** | | | | -| [mgra_based_input{SCENARIO_YEAR}.csv](#lu) | Land use forecast of the size and structure of the region’s economy and corresponding demographic forecast | CSV | Land Use Modelers, Transportation Modelers, and GIS | -| [activity_code_indcen_acs.csv](#activity_mapping) | PECAS activity code categories mapping to Census industry codes; This is used for military occupation mapping. | CSV | Land Use Modelers | -| [pecas_occ_occsoc_acs.csv](#pecas_occ) | PECAS activity code categories mapping to Census industry codes | CSV | Lande Use Modelers | -| [mobilityHubMGRA.csv](#mobility_mgra) | | CSV | Transportation Modelers | -| **Synthetic Population** | | | | -| [households.csv](#population_synth_households) | Synthetic households | CSV | Transportation Modelers | -| [persons.csv](#population_synth_persons) | Synthetic persons | CSV | Transportation Modelers | -| **Network: Highway (to be updated with TNED)** | | | | -| hwycov.e00 | Highway network nodes from GIS | ESRI input exchange | Transportation Modelers | -| hwycov.e00 | Highway network links from GIS | ESRI input exchange | Transportation Modelers | -| turns.csv | Highway network turns file | CSV | Transportation Modelers | -| LINKTYPETURNS.dbf | Highway network link type turns table | DBF | Transportation Modelers | -| LINKTYPETURNSCST.DBF | | DBF | Transportation Modelers | -| [vehicle_class_toll_factors.csv](#vehicle_class_toll) | Relative toll values by six vehicle classes by Facility name. Used to identify "free for HOV" type managed lane facilities. | CSV | Transportation Modelers | -| [off_peak_toll_factors.csv](#off_peak_toll) | Relative toll values for the three off-peak times-of-day (EA, MD, EV) by Facility name. Multiplied together with the values from vehicle_class_toll_factors.csv to get the final toll. | CSV | Transportation Modelers | -| [vehicle_class_availability.csv](#hwy_link_vehicle_class_availability) | The availability / unavailability of six vehicle classes for five times-of-day by facility name. | CSV | Transportation Modelers | -| **Network: Transit (To be updated with TNED)** | | | | -| trcov.e00 | Transit network arc data from GIS | ESRI input exchange | Transportation Modelers | -| trcov.e00 | Transit network node data from GIS | ESRI input exchange | Transportation Modelers | -| [trlink.csv](#tr_link) | Transit route with a list of links file | CSV | Transportation Modelers | -| trrt.csv | Transit route attribute file | CSV | Transportation Modelers | -| [trstop.csv](#transit_binary_stop) | Transit stop attribute file | TCSV | Transportation Modelers | -| mode5tod.csv | Transit mode parameters table | CSV | Transportation Modelers | -| [timexfer_XX.csv](#transit_transfer_proh) | Transit timed transfers table between COASTER and feeder buses; XX is the TOD (EA, AM, MD, PM, and EV) | CSV | Transportation Modelers | -| special_fares.txt | Fares to coaster | Text File | Transportation Modelers | -| **Network: Active Transportation** | | | | -| [SANDAG_Bike_Net.dbf](#bike_net_link) | Bike network links | DBF | GIS | -| [SANDAG_Bike_Node.dbf](#bike_net_node) | Bike network nodes | DBF | GIS | -| [bikeTazLogsum.csv](#bike_taz_logsum) (not saved in inputs, instead, run at the beginning of a model run) | Bike TAZ logsum | CSV | Transportation Modelers | -| [bikeMgraLogsum.csv](#bike_mgra_logsum) (not saved in inputs, instead, run at the beginning of a model run) | Bike MGRA logsum | CSV | Transportation Modelers | -| [walkMgraEquivMinutes.csv](#walk_mgra_equiv) (not saved in inputs, instead, run at the beginning of a model run) | Walk, in minutes, between MGRAs | CSV | | | | | | -| **Visitor Model (Derived from visitor survey)** | | | | -| visitor_businessFrequency.csv | Visitor model tour frequency distribution for business travelers | CSV | Transportation Modelers | -| visitor_personalFrequency.csv | Visitor model tour frequency distribution for personal travelers | CSV | Transportation Modelers | -| visitor_partySize.csv | Visitor model party size distribution | CSV | Transportation Modelers | -| visitor_autoAvailable.csv | Visitor model auto availability distribution | CSV | Transportation Modelers | -| visitor_income.csv | Visitor model income distribution | CSV | Transportation Modelers | -| visitor_tourTOD.csv | Visitor model tour time-of-day distribution | CSV | Transportation Modelers | -| visitor_stopFrequency.csv | Visitor model stop frequency distribution | CSV | Transportation Modelers | -| visitor_stopPurpose.csv | Visitor model stop purpose distribution | CSV | Transportation Modelers | -| visitor_outboundStopDuration.csv | Visitor model time-of-day offsets for outbound stops | CSV | Transportation Modelers | -| visitor_inboundStopDuration.csv | Visitor model time-of-day offsets for inbound stops | CSV | Transportation Modelers | -| **Airport Model (Derived from airport survey)** | | | | -| [airport_purpose.csv](#airport_trip_purpose) | Airport model tour purpose frequency table | CSV | Transportation Modelers | -| [airport_party.csv](#airport_party_purpose) | Airport model party type frequency table | CSV | Transportation Modelers | -| [airport_nights.csv](#airport_nights) | Airport model trip duration frequency table | CSV | Transportation Modelers | -| [airport_income.csv](#airport_income) | Airport model trip income distribution table | CSV | Transportation Modelers | -| [airport_departure.csv](#airport_departure) | Airport model time-of-day distribution for departing trips | CSV | Transportation Modelers | -| [airport_arrival.csv](#airport_arrival) | Airport model time-of-day distribution for arriving trips | CSV | Transportation Modelers | -| **Cross-Border Model (Derived from cross-border survey)** | | | | -| crossBorder_tourPurpose_control.csv | | CSV | | -| crossBorder_tourPurpose_nonSENTRI.csv | Cross Border Model tour purpose distribution for Non-SENTRI tours | CSV | Transportation Modelers | -| crossBorder_tourPurpose_SENTRI.csv | Cross Border Model tour purpose distribution for SENTRI tours | CSV | Transportation Modelers | -| [crossBorder_tourEntryAndReturn.csv](#cross_border_entry_return) | Cross Border Model tour entry and return time-of-day distribution | CSV | Transportation Modelers | -| [crossBorder_supercolonia.csv](#cross_border_supercolonia) | Cross Border Model distance from Colonias to border crossing locations | CSV | Transportation Modelers | -| [crossBorder_pointOfEntryWaitTime.csv](#cross_border_wait_time) | Cross Border Model wait times at border crossing locations table | CSV | GIS - Pat L vtsql | -| [crossBorder_stopFrequency.csv](#cross_border_stops) | Cross Border Model stop frequency data | CSV | Transportation Modelers | -| [crossBorder_stopPurpose.csv](#cross_border_stop_purpose) | Cross Border Model stop purpose distribution | CSV | Transportation Modelers | -| [crossBorder_outboundStopDuration.csv](#cross_border_out_stop) | Cross Border Model time-of-day offsets for outbound stops | CSV | Transportation Modelers | -| [crossBorder_inboundStopDuration.csv](#cross_border_in_stop) | Cross Border Model time-of-day offsets for inbound stops | CSV | Transportation Modelers | -| **External Models (Derived from SCAG survey)** | | | | -| [externalExternalTripsByYear.csv](#external_trip) (raw inputs have these by year) | External origin-destination station trip matrix | CSV | Transportation Modelers | | | | | -| [externalInternalControlTotalsByYear.csv](#external_internal) (raw inputs have these by year) | External Internal station control totals read by GISDK | CSV | Transportation Modelers | | | | | -| [internalExternal_tourTOD.csv](#internal_external_tod) | Internal-External Model tour time-of-day frequency distribution | CSV | Transportation Modelers | -| **Commercial Vehicle Model** (TO BE UPDATED) | | | | -| tazcentroids_cvm.csv | Zone centroid coordinates in state plane feet and albers | CSV | Transportation Modelers | -| commVehFF.csv | Commercial Vehicle Model friction factors | CSV | Transportation Modelers | -| OE.csv | Commercial vehicle model parameters file for off-peak early (OE) period | CSV | Transportation Modelers | -| AM.csv | Commercial vehicle model parameters file for AM period | CSV | Transportation Modelers | -| MD.csv | Commercial vehicle model parameters file for mid-day (MD) period | CSV | Transportation Modelers | -| PM.csv | Commercial vehicle model parameters file for PM period | CSV | Transportation Modelers | -| OL.csv | Commercial vehicle model parameters file for off-peak late (OL) period | CSV | Transportation Modelers | -| FA.csv | Commercial vehicle model parameters file for fleet allocator (FA) industry | CSV | Transportation Modelers | -| GO.csv | Commercial vehicle model parameters file for government/ office (GO) industry | CSV | Transportation Modelers | -| IN.csv | Commercial vehicle model parameters file for industrial (IN) industry | CSV | Transportation Modelers | -| FA.csv | Commercial vehicle model parameters file for fleet allocator (FA) industry | CSV | Transportation Modelers | -| RE.csv | Commercial vehicle model parameters file for retail (RE) industry | CSV | Transportation Modeler | -| SV.csv | Commercial vehicle model parameters file for service (SV) industry | CSV | Transportation Modelers | -| TH.csv | Commercial vehicle model parameters file transport and handling (TH) industry | CSV | Transportation Modelers | -| WH.csv | Commercial vehicle model parameters file wholesale (WH) industry | CSV | Transportation Modelers | -| **Truck Model** | | | | -| TruckTripRates.csv | Truck model data: Truck trip rates | CSV | Transportation Modelers | -| regionalEItrips.csv | Truck model data: Truck external to internal data | CSV | Transportation Modelers | -| regionalIEtrips.csv | Truck model data: Truck internal to external data | CSV | Transportation Modelers | -| regionalEEtrips.csv | Truck model data: Truck external to external data | CSV | Transportation Modelers | -| specialGenerators.csv | Truck model data: Truck special generator data | CSV | Transportation Modelers | -| **Other** | | | | -| [parametersByYears.csv](#parametersbyyearscsv) | Parameters by scenario years. Includes AOC, aiport enplanements, cross-border tours, cross-border sentri share. | CSV | Transportation Modelers | -| [filesByYears.csv](#filesbyyearscsv) | File names by scenario years. | CSV | Transportation Modelers | -| trip_XX.omx | Warm start trip table; XX is the TOD (EA, AM, MD, PM, and EV) | OMX | Transportation Modelers | -| zone.term | TAZ terminal times | Space Delimited Text File | Transportation Modelers | - -```MGRA_BASED_INPUT<>.CSV``` - -| Column name | Description | -| --- | --- | -| mgra | MGRANumber | -| taz | TAZ Number | -| luz_id | | -| pop | total population | -| hhp | total household population (exclude gq pop) | -| hs | housing structures | -| hs_sf | single family structures | -| hs_mf | multi family structures | -| hs_mh | mobile homes | -| hh | total number of households | -| hh_sf | number of households - single family | -| hh_mf | number of households - multi family | -| hh_mh | number of mobile homes | -| hhs | household size | -| gq_civ | GQ civilian | -| gq_mil | GQ military | -| i1 | Number of households with income less than $15,000 ($2010) | -| i2 | Number of households with income $15,000-$29,999 ($2010) | -| i3 | Number of households with income $30,000-$44,999 ($2010) | -| i4 | Number of households with income $45,000-$59,999 ($2010) | -| i5 | Number of households with income $60,000-$74,999 ($2010) | -| i6 | Number of households with income $75,000-$99,999 ($2010) | -| i7 | Number of households with income $100,000-$124,999 ($2010) | -| i8 | Number of households with income $125,000-$149,999 ($2010) | -| i9 | Number of households with income $150,000-$199,999 ($2010) | -| i10 | Number of households with income $200,000 or more ($2010) | -| emp_gov | Government employment | -| emp_mil | military employment | -| emp_ag_min | Agriculture and mining employment | -| emp_bus_svcs | Professional and Business Services employment | -| emp_fin_res_mgm | Financial and resource management employment | -| emp_educ | Education services employment | -| emp_hlth | Health services employment | -| emp_ret | Retail services employment | -| emp_trn_wrh | Transportation and Warehousing employment | -| emp_con | Construction employment | -| emp_utl | Utilities office support employment | -| emp_mnf | Manufacturing employment | -| emp_whl | Wholesale employment | -| emp_ent | Entertainment services employment | -| emp_accm | Hotel and accomodation services | -| emp_food | Food services employment | -| emp_oth | Other employment | -| emp_non_ws_wfh | Non-wage and salary work from home employments | -| emp_non_ws_oth | Non-wage and salary other employments | -| emp_total | Total employment | -| pseudomsa | Pseudo MSA - | -| | 1: Downtown | -| | 2: Central | -| | 3: North City | -| | 4: South Suburban | -| | 5: East Suburban | -| | 6: North County West | -| | 7: North County East | -| | 8: East County | -| zip09 | 2009 Zip Code | -| enrollgradekto8 | Grade School K-8 enrollment | -| enrollgrade9to12 | Grade School 9-12 enrollment | -| collegeenroll | Major College enrollment | -| othercollegeenroll | Other College enrollment | -| hotelroomtotal | Total number of hotel rooms | -| parkactive | Acres of Active Park | -| openspaceparkpreserve | Acres of Open Park or Preserve | -| beachactive | Acres of Active Beach | -| district27 | | -| milestocoast | Distance (miles) to the nearest coast | -| acres | Total acres in the mgra (used in CTM) | -| land_acres | Acres of land in the mgra (used in CTM) | -| effective_acres | Effective acres in the mgra (used in CTM) | -| truckregiontype | | -| exp_hourly | Expected hourly prking cost | -| exp_daily | Expected daily prking cost | -| exp_monthly | Expected monthly prking cost | -| parking_type | MGRA parking type | -| parking_spaces | MGRA estimated parking spaces | -| ech_dist | Elementary school district | -| hch_dist | High school district | -| remoteAVParking | Remote AV parking available at MGRA: 0 = Not available, 1 = Available | -| refueling_stations | Number of refueling stations at MGRA | -| MicroAccessTime | Micro-mobility access time (mins) | -| microtransit | microtransit access time (mins) | -| nev | Neighborhood Electric Vehicle access time (mins) | -| totint | Total intersections | -| duden | Dwelling unit density | -| empden | Employment density | -| popden | Population density | -| retempden | Retail employment density | -| totintbin | Total intersection bin | -| empdenbin | Employment density bin | -| dudenbin | Dwelling unit density bin | -| PopEmpDenPerMi | Population and employment density per mile | - - - -### Activity Mapping to Industry Codes -#### `ACTIVITY_CODE_INDCEN_ACS.CSV` - -| Column Name | Description | -| ----------- | ----------- | -| indcen | Industry code defined in PECAS: They are about 270 industry categories grouped by 6-digit NAICS code (North American Industrial Classification System) | -| activity_code | Activity code defined in PECAS. They are about 30 types of activities grouped by the industry categories:
1 = Agriculture
3 = Construction Non-Building office support (including mining)
5 = Utilities office support
9 = Manufacturing office support
10 = Wholesale and Warehousing
11 = Transportation Activity
12 = Retail Activity
13 = Professional and Business Services
14 = Professional and Business Services (Building Maintenance)
16 = Private Education Post-Secondary (Post K-12) and Other
17 = Health Services
18 = Personal Services Office Based
19 = Amusement Services
20 = Hotels and Motels
21 = Restaurants and Bars
22 = Personal Services Retail Based
23 = Religious Activity
24 = Private Households
25 = State and Local Government Enterprises Activity
27 = Federal Non-Military Activity
28 = Federal Military Activity
30 = State and Local Government Non-Education Activity office support
31 = Public Education | - - - - -### PECAS SOC - Defined Occupational Codes -#### `PECAS_OCC_OCCSOC_ACS.CSV` - - - - - - - - - - - - - - -
Column NameDescription
occsoc5Detailed occupation codes defined by the Standard Occupational Classification (SOC) system
commodity_id - Commodity code defined in PECAS. The detailed SOC occupations are grouped into 6 types of laborers, which are included as part of commodity:
- 51 = Services Labor
- 52 = Work at Home Labor
- 53 = Sales and Office Labor
- 54 = Natural Resources Construction and Maintenance Labor
- 55 = Production Transportation and Material Moving Labor
- 56 = Military Labor -
- - - -### Listing of External Zones Attributes -#### `EXTERNALZONES.XLS` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Internal Cordon LUZInternal Cordon Land use zone
External LUZExternal land use zone
Cordon PointCordon Point description
Destination ApproximationName of approximate city destination
Miles to be Added to Cordon PointMiles to be added to cordon point
Travel TimeTravel time to external zone
Border DelayBorder delay time
Minutes to be Added to Cordon PointMinutes to be added to cordon point
MPHAverage miles per hour based on miles and minutes to be added to cordon point
- - - -### Population Synthesizer Household Data -#### `HOUSEHOLDS.CSV` - -| Column Name | Description | -| ----------- | ----------- | -| hhid | Unique Household ID | -| household_serial_no | Household serial number | -| taz | TAZ of household | -| mgra | MGRA of household | -| hinccat1 | Household income category:
1 = <$30k
2 = $30-60k
3 = $60-100k
4 = $100-150k
5 = $150k+ | -| hinc | Household income | -| num_workers | Number of workers in household | -| veh | Number of vehicles in household | -| persons | Number of persons in household | -| hht | Household/family type:
0 = Not in universe (vacant or GQ)
1 = Family household: married-couple
2 = Family household: male householder, no wife present
3 = Family household: female householder, no husband present
4 = Nonfamily household: male householder, living alone
5 = Nonfamily household: male householder, not living alone
6 = Nonfamily household: female householder, living alone
7 = Nonfamily household: female householder, not living alone | -| bldgsz | Building size - Number of Units in Structure & Quality:
1 = Mobile home or trailer
2 = One-family house detached
3 = One-family house attached
8 = 20-49 Apartments
9 = 50 or more apartments | -| unittype | Household unit type:
0 = Non-GQ Household
1 = GQ Household | -| version | Synthetic population run version. Presently set to 0. | -| poverty | Poverty indicator utilized for social equity reports. Percentage value where value <= 2 (200% of the [Federal Poverty Level](https://aspe.hhs.gov/2020-poverty-guidelines)) indicates household is classified under poverty. | - - - - -### Population Synthesizer Person Data -#### `PERSONS.CSV` - -| Column Name | Description | -|----------------------|-----------------------------------------------------------------------------------------------| -| hhid | Household ID | -| perid | Person ID | -| Household_serial_no | Household serial number | -| pnum | Person Number | -| age | Age of person | -| sex | Gender of person
1 = Male
2 = Female | -| military | Military status of person:
0 = N/A Less than 17 Years Old
1 = Yes, Now on Active Duty | -| pemploy | Employment status of person:
1 = Employed Full-Time
2 = Employed Part-Time
3 = Unemployed or Not in Labor Force
4 = Less than 16 Years Old | -| pstudent | Student status of person:
1 = Pre K-12
2 = College Undergrad+Grad and Prof. School
3 = Not Attending School | -| ptype | Person type:
1 = Full-time Worker
2 = Part-time Worker
3 = College Student
4 = Non-working Adult
5 = Non-working Senior
6 = Driving Age Student
7 = Non-driving Student
8 = Pre-school | -| educ | Educational attainment:
1 = No schooling completed
9 = High school graduate
13 = Bachelor's degree | -| grade | School grade of person:
0 = N/A (not attending school)
2 = K to grade 8
5 = Grade 9 to grade 12
6 = College undergraduate | -| occen5 | Occupation:
0 = Not in universe (Under 16 years or LAST-WRK = 2)
1..997 = Legal census occupation code | -| occsoc5 | Detailed occupation codes defined by the Bureau of Labor Statistics | - - - - -### Highway Network Vehicle Class Toll Factors File -#### `vehicle_class_toll_factors.csv` - -Required file. Used to specify the relative toll values by six vehicle classes by Facility name, scenario year and time of day. Can be used, for example, to identify "free for HOV" type managed lane facilties. Used by the Import network Modeller tool. - -Example: - -| Facility_name | Year | Time_of_Day | DA_Factor | S2_Factor | S3_Factor | TRK_L_Factor | TRK_M_Factor | TRK_H_Factor | -| ------------- | ---- | ----------- | --------- | --------- | --------- | ------------ | ------------ | ------------ | -| I-15 | 2016 | EA | 1.0 | 0.0 | 0.0 | 1.0 | 1.03 | 2.33 | -| SR-125 | 2016 | ALL | 1.0 | 1.0 | 1.0 | 1.0 | 1.03 | 2.33 | -| I-5 | 2035 | ALL | 1.0 | 1.0 | 0.0 | 1.0 | 1.03 | 2.33 | - -The toll values for each class on each link are calculated by multiplying the input toll value from hwycov.e00 (ITOLLA, ITOLLP, ITOLLO) by this factor, matched by the Facility name (together with the toll factors from off_peak_toll_factors.csv in converting ITOLLO to the off-peak times-of-day). - -The network links are matched to a record in this file based on the NM, FXNM or TXNM values (in that order). A simple substring matching is used, so the record with Facility_name "I-15" matches any link with name "I-15 SB", "I-15 NB", "I-15/DEL LAGO DAR NB" etc. The records should not be overlapping: if there are two records which match a given link it will be an arbitrary choice as to which one is used. - -Note that if a link does not match to a record in this file, the default factors (specified in the table below) will be applied to said link. It is OK if there are records for which there are no link tolls. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Facility_nameName of the facility, used in the substring matching with links by NM, FXNM or TXNM fields
YearScenario year
Time_of_Day - Time of day period:
- EA = Early morning (3am - 5:59am)
- AM = AM peak (6am to 8:59am)
- MD = Mid-day (9am to 3:29pm)
- PM = PM peak (3:30pm to 6:59pm)
- EV = Evening (7pm to 2:59am)
- ALL = All time of day periods -
DA_FactorPositive toll factor for Drive Alone (SOV) vehicle classes. The default value is 1.0
S2_FactorPositive toll factor for Shared 2 person (HOV2) vehicle classes. The default value is 1.0
S3_FactorPositive toll factor for Shared 3+ person (HOV3) vehicle classes. The default value is 1.0
TRK_L_FactorPositive toll factor for Light Truck (TRKL) vehicle classes. The default value is 1.0
TRK_M_FactorPositive toll factor for Medium Truck (TRKM) vehicle classes. The default value is 1.03
TRK_H_FactorPositive toll factor for Heavy Truck (TRKH) vehicle classes. The default value is 2.03
- - - -### Highway Network Off-Peak Toll Factors File -#### `off_peak_toll_factors.csv` - -Optional file. Used to specify different tolls in the off-peak time-of-day scenarios based on the single link ITOLLO field, together with the tolls by vehicle class from vehicle_class_toll_factors.csv. -Used by the Import network Modeller tool. - -Example: -``` -Facility_name, OP_EA_factor, OP_MD_factor, OP_EV_factor -I-15, 0.75, 1.0, 0.75 -SR-125, 1.0 , 1.0, 1.0 -SR-52, 0.8 , 1.0, 0.8 -``` - -See note re: network link matching under vehicle_class_toll_factors.csv. Note that all facilities need not be specified, links not matched will use a factor of 1.0. - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Facility_nameName of the facility, used in the substring matching with links by NM, FXNM or TXNM fields
OP_EA_FACTORPositive toll factor for Early AM period tolls
OP_MD_FACTORPositive toll factor for Midday period tolls
OP_EV_FACTORPositive toll factor for Evening period tolls
- - - -### Highway Network Vehicle Class Toll Factors File -#### `vehicle_class_availability.csv` - -Optional file. Specifies the availability / unavailability of six vehicle classes for five times-of-day by Facility name. This will override any mode / vehicle class availability specified directly on the network (hwycov.e00), via ITRUCK and IHOV fields. Used in the generation of time-of-day Emme scenarios in the Master run Modeller tool. - -Example: - -| Facility_name | vehicle_class | EA_Avail | AM_Avail | MD_Avail | PM_Avail | EV_Avail | -| ------------- | ------------- | -------- | -------- | -------- | -------- | -------- | -| I-15 | DA | 1 | 1 | 1 | 1 | 1 | -| I-15 | S2 | 1 | 1 | 1 | 1 | 1 | -| I-15 | S3 | 1 | 0 | 1 | 0 | 1 | -| I-15 | TRK_L | 1 | 1 | 1 | 1 | 1 | -| I-15 | TRK_M | 1 | 0 | 0 | 0 | 1 | -| I-15 | TRK_H | 1 | 0 | 0 | 0 | 1 | - -See note re: network link matching under vehicle_class_toll_factors.csv. Note that all facilities need not be specified, links not matched will use the availability as indicated by the link fields in hwycov.e00. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Facility_nameName of the facility, used in the substring matching with links by NM, FXNM or TXNM fields
Vehicle_className of the vehicle class, one of DA, S2, S3, TRK_L, TRK_M, or TRK_H
EA_AvailFor this facility and vehicle class, is available for Early AM period (0 or 1)
AM_AvailFor this facility and vehicle class, is available for AM Peak period (0 or 1)
MD_AvailFor this facility and vehicle class, is available for Midday period (0 or 1)
PM_AvailFor this facility and vehicle class, is available for PM Peak period (0 or 1)
EV_AvailFor this facility and vehicle class, is available for Evening period (0 or 1)
- -#### `special_fares.txt` - -``` -boarding_cost: - base: - - {line: "398104", cost: 3.63} - - {line: "398204", cost: 3.63} - stop_increment: - - {line: "398104", stop: "SORRENTO VALLEY", cost: 0.46} - - {line: "398204", stop: "SORRENTO VALLEY", cost: 0.46} -in_vehicle_cost: - - {line: "398104", from: "SOLANA BEACH", cost: 0.45} - - {line: "398104", from: "SORRENTO VALLEY", cost: 0.45} - - {line: "398204", from: "OLD TOWN", cost: 0.45} - - {line: "398204", from: "SORRENTO VALLEY", cost: 0.45} -day_pass: 4.54 -regional_pass: 10.90 -``` - - - -### Transit Binary Stop Table -#### `TRSTOP.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Stop_idUnique stop ID
Route_idSequential route number
Link_idLink id associated with route
Pass_countNumber of times the route passes this stop. Most of value is one, some value is 2
MilepostStop mile post
LongitudeStop Longitude
LatitudeStop Latitude
NearNodeNode number that stop is nearest to
FareZoneZones defined in Fare System
StopNameName of Stop
MODE_NAME - Line haul mode name:
- Transfer
- Center City Walk
- Walk Access
- Commuter Rail
- Light Rail
- Regional BRT (Yellow)
- Regional BRT (Red)
- Limited Express
- Express
- Local -
MODE_ID - Mode ID
- 1 = Transfer
- 2 = Center City Walk
- 3 = Walk Access
- 4 = Commuter Rail
- 5 = Light Rail
- 6 = Regional BRT (Yellow)
- 7 = Regional BRT (Red)
- 8 = Limited Express
- 9 = Express
- 10 = Local -
PREMODE - Premium Transit mode
- 0 = No
- 1 = Yes -
EXPBSMODE - Express bus mode
- 0 = No
- 1 = Yes -
LOCMODE - Local bus mode
- 0 = No
- 1 = Yes -
OP_TRNTIME - Off peak transcad matrix used by mode:
- *oploctime
- *oppretime -
AM_TRNTIME - AM peak transcad matrix used by mode:
- *amloctime
- *ampretime -
PM_TRNTIME - PM peak transcad matrix used by mode:
- *pmloctime
- *pmpretime -
MODE_ACCESMode of access (1)
MODE_EGRESMode of egress (1)
WT_IVTPKWeight for peak in-vehicle time: 1, 1.5, or 1.8
WT_FWTPKWeight for peak first wait time: 1, 1.5
WT_XWTPKWeight for peak transfer wait time: 1, 3
WT_FAREPKWeight for peak fare: 0.46, 0.60, 0.63, 0.67, 1
WT_IVTOPWeight for off-peak in-vehicle time: 1, 1.5, or 1.6
WT_FWTOPWeight for off-peak first wait time: 1, 1.5
WT_XWTOPWeight for off-peak transfer wait time: 1, 3
WT_FAREOPWeight for off-peak fare: 0.23, 0.51, 0.52, 0.54, 0.58, 1
FARETransit fare: $0, $1.25, $1.50, $2.50, $3.00, $3.50
DWELLTIMEDwell time: 0, 0.3, 0.5
FARETYPE - Fare Type:
- 1 = Bus
- 2 = Rail -
FAREFIELD - Fare Field:
- coaster fare
- lightrail fare -
CRMODEBoolean if Commuter rail available
LRMODEBoolean if light rail available
XFERPENTMTransfer Penalty time: 5 minutes
WTXFERTMTransfer Wait time: 1 minute
TRNTIME_EAEarly AM transit time impedance
TRNTIME_AMAM transit time impedance
TRNTIME_MDMidday transit time impedance
TRNTIME_PMPM transit time impedance
TRNTIME_EVEvening transit time impedance
- - - -### Transit Timed Transfers Between COASTER and Feeder Buses -#### `TIMEXFER_XX.CSV` - - - - - - - - - - - - - - - - - - -
Column NameDescription
FROM_LINEFrom Route Number
TO_LINETo Route Number
WAIT_TIMEWait time in minutes
- - - -### Transit Stop Table -#### `TRSTOP.CSV` -| Column Name | Description | -| ------------ | ----------- | -| Stop_id | Unique stop ID | -| Route_id | Sequential route number | -| Link_id | Link id associated with route | -| Pass_count | Number of times the route passes this stop. Most of value is one, some value is 2 | -| Milepost | Stop mile post | -| Longitude | Stop Longitude | -| Latitude | Stop Latitude | -| NearNode | Node number that stop is nearest to | -| FareZone | Zones defined in Fare System | -| StopName | Name of Stop | -| MODE_NAME | Line haul mode name:
Transfer
Center City Walk
Walk Access
Commuter Rail
Light Rail
Regional BRT (Yellow)
Regional BRT (Red)
Limited Express
Express
Local | -| MODE_ID | Mode ID
1 = Transfer
2 = Center City Walk
3 = Walk Access
4 = Commuter Rail
5 = Light Rail
6 = Regional BRT (Yellow)
7 = Regional BRT (Red)
8 = Limited Express
9 = Express
10 = Local | -| PREMODE | Premium Transit mode
0 = No
1 = Yes | -| EXPBSMODE | Express bus mode
0 = No
1 = Yes | -| LOCMODE | Local bus mode
0 = No
1 = Yes | -| OP_TRNTIME | Off peak transcad matrix used by mode:
*oploctime
*oppretime | -| AM_TRNTIME | AM peak transcad matrix used by mode:
*amloctime
*ampretime | -| PM_TRNTIME | PM peak transcad matrix used by mode:
*pmloctime
*pmpretime | -| MODE_ACCES | Mode of access (1) | -| MODE_EGRES | Mode of egress (1) | -| WT_IVTPK | Weight for peak in-vehicle time: 1, 1.5, or 1.8 | -| WT_FWTPK | Weight for peak first wait time: 1, 1.5 | -| WT_XWTPK | Weight for peak transfer wait time: 1, 3 | -| WT_FAREPK | Weight for peak fare: 0.46, 0.60, 0.63, 0.67, 1 | -| WT_IVTOP | Weight for off-peak in-vehicle time: 1, 1.5, or 1.6 | -| WT_FWTOP | Weight for off-peak first wait time: 1, 1.5 | -| WT_XWTOP | Weight for off-peak transfer wait time: 1, 3 | -| WT_FAREOP | Weight for off-peak fare: 0.23, 0.51, 0.52, 0.54, 0.58, 1 | -| FARE | Transit fare: $0, $1.25, $1.50, $2.50, $3.00, $3.50 | -| DWELLTIME | Dwell time: 0, 0.3, 0.5 | -| FARETYPE | Fare Type:
1 = Bus
2 = Rail | -| FAREFIELD | Fare Field:
coaster fare
lightrail fare | -| CRMODE | Boolean if Commuter rail available | -| LRMODE | Boolean if light rail available | -| XFERPENTM | Transfer Penalty time: 5 minutes | -| WTXFERTM | Transfer Wait time: 1 minute | -| TRNTIME_EA | Early AM transit time impedance | -| TRNTIME_AM | AM transit time impedance | -| TRNTIME_MD | Midday transit time impedance | -| TRNTIME_PM | PM transit time impedance | -| TRNTIME_EV | Evening transit time impedance | - - - - -### Transit Link File -#### `TRLINK.CSV` - - - - - - - - - - - - - - - - - - -
Column NameDescription
Route_id:Sequential route number
Link_idLink id associated with route
Direction+ or -
- - - - -### Bike Network Link Field List -#### `SANDAG_BIKE_NET.DBF` - -| Column Name | Description | -| ----------- | ----------- | -| ROADSEGID | Road Segment ID | -| RD20FULL | Road/Street Name | -| A | Foreign key of first node | -| B | Foreign key of second node | -| A_LEVEL | Level of first node | -| B_LEVEL | Level of second node | -| Distance | Arc length of link (ft) | -| AB_Gain | Cumulative non-negative increase in elevation from A to B nodes (ft) | -| BA_Gain | Cumulative non-negative increase in elevation from B to A nodes (ft) | -| ABBikeClas | Type of Bike Classification in AB direction where:
1 = Multi-Use Path
2 = Bike Lane
3 = Bike Route | -| BABikeClas | Type of Bike Classification in BA direction where:
1 = Multi-Use Path
2 = Bike Lane
3 = Bike Route | -| AB_Lanes | Number of Lanes in AB direction | -| BA_Lanes | Number of Lanes in BA direction | -| Func_Class | Type of Road Functional Class where:
1 = Freeway to Freeway Ramp
2 = Light (2-lane) Collector Street
3 = Rural Collector Road
4 = Major Road/4-lane Major Road
5 = Rural Light Collector/Local Road
6 = Prime Arterial
7 = Private Street
8 = Recreational Parkway
9 = Rural Mountain Road
A = Alley
B = Class I Bicycle Path
C = Collector/4-lane Collector Street
D = Two-lane Major Street
E = Expressway
F = Freeway
L = Local Street/Cul-de-sac
M = Military Street within Base
P = Paper Street
Q = Undocumented
R = Freeway/Expressway On/Off Ramp
S = Six-lane Major Street
T = Transitway
U = Unpaved Road
W = Pedestrian Way/Bikeway | -| Bike2Sep | Separated Bike Lane Flag where:
0 = No
1 = Yes | -| Bike3Blvd | Bike Boulevard Lane Flag where:
0 = No
1 = Yes | -| SPEED | Road Speed | -| A_Elev | A Node Elevation | -| B_Elev | B Node Elevation | -| ProjectID | Project ID in the regional bike network | -| Year | Year built/opened to the public | -| Scenicldx | Scenic index represents the closeness to the ocean and parks | -| Path | Null | -| Shape_Leng | length of the link (ft) | - - - -### Bike Network Node Field List -#### `SANDAG_BIKE_NODE.DBF` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
NodeLev_IDNode Unique Identifier
MGRAMGRA ID for Centroids
TAZTAZ ID for Centroids
TAPTAP ID
XCOORDX Coordinate of Node in NAD 1983 State Plane California Region VI FIPS: 0406 (ft)
YCOORDY Coordinate of Node in NAD 1983 State Plane California Region VI FIPS: 0406(ft)
ZCOORDElevation (ft)
Signal - Traffic Signal Presence where:
- 0 = Absence
- 1 = Presence -
- -### Zone Terminal Time -#### `ZONE.TERM` - - - - - - - - - - - - - -
Column NameDescription
ZoneTAZ number
Terminal timeTerminal time (3, 4, 5, 7, 10 minutes) -
- - - -### Bike TAZ Logsum -#### `BIKETAZLOGSUM.CSV` - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
iOrigin TAZ
jDestination TAZ
LogsumLogsum - a measure of the closeness of the origin and the destination of the trip
timeTime (In minutes)
- - - -### Bike MGRA Logsum -#### `BIKEMGRALOGSUM.CSV` - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
iOrigin of MGRA
jDestination of MGRA
LogsumLogsum - a measure of the closeness of the origin and the destination of the trip
timeTime (in minutes)
- - - -### Walk MGRA Equivalent Minutes -#### `WALKMGRAEQUIVMINUTES.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
iOrigin (MGRA)
jDestination (MGRA)
percievedPercieved time to walk
actualActual time to walk (minutes)
gainGain in elevation
- - - -### Airport Trip Purpose Distribution -#### `AIRPORT_PURPOSE.SAN.CSV AND AIRPORT_PURPOSE.CBX.CSV` - - - - - - - - - - - - - - -
Column NameDescription
Purpose - Trip Purpose:
- 0 = Resident Business
- 1 = Resident Personal
- 2 = Visitor Business
- 3 = Visitor Personal
- 4 = External -
PercentDistribution of Trips in trip purpose
- - - -### Airport Party Size by Purpose Distribution -#### `AIRPORT_PARTY.SAN.CSV AND AIRPORT_PARTY.CBX.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
PartyParty size (0 through 5+)
purp0_percDistribution for Resident Business purpose
purp1_percDistribution for Resident Personal purpose
purp2_percDistribution for Visitor Business purpose
purp3_percDistribution for Visitor Personal purpose
purp4_percDistribution for External purpose
- - - -### Airport Number of Nights by Purpose Distribution -#### `AIRPORT_NIGHTS.SAN.CSV AND AIRPORT_NIGHTS.CBX.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
NightsNumber of Nights stayed (0 through 14+)
purp1_percDistribution for Resident Personal purpose
purp2_percDistribution for Visitor Business purpose
purp3_percDistribution for Visitor Personal purpose
purp4_percDistribution for External purpose
- - - -### Airport Income by Purpose Distribution -#### `AIRPORT_INCOME.SAN.CSV AND AIRPORT_INCOME.CBX.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Income group - Household income:
- 0 = Less than $25K
- 1 = $25K – $50K
- 2 = $50K – $75K
- 3 = $75K – $100K
- 4 = $100K – $125K
- 5 = $125K – $150K
- 6 = $150K – $200K
- 7 = $200K plus -
purp1_percDistribution for Resident Personal purpose
purp2_percDistribution for Visitor Business purpose
purp3_percDistribution for Visitor Personal purpose
purp4_percDistribution for External purpose
- - - -### Airport Departure Time by Purpose Distribution -#### `AIRPORT_DEPARTURE.SAN.CSV` and `AIRPORT_DEPARTURE.CBX.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Period - Departure Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
purp1_percDistribution for Resident Personal purpose
purp2_percDistribution for Visitor Business purpose
purp3_percDistribution for Visitor Personal purpose
purp4_percDistribution for External purpose
- - - - -### Airport Arrival Time by Purpose Distribution -#### `AIRPORT_ARRIVAL.SAN.CSV` and `AIRPORT_ARRIVAL.CBX.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Period - Arrival Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
purp1_percDistribution for Resident Personal purpose
purp2_percDistribution for Visitor Business purpose
purp3_percDistribution for Visitor Personal purpose
purp4_percDistribution for External purpose
- - - - -### Cross Border Model Tour Entry and Return Distribution -#### `CROSSBORDER_TOURENTRYANDRETURN.CSV` - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Purpose - Tour Purpose:
- 0 = Work
- 1 = School
- 2 = Cargo
- 3 = Shop
- 4 = Visit
- 5 = Other -
EntryPeriod - Entry Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
Return Period - Return Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
PercentDistribution of tours in entry and return period time slots
- - - -### Cross Border Model Supercolonia -#### `CROSSBORDER_SUPERCOLONIA.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Supercolonia_IDSuper colonia ID
PopulationPopulation of the super colonia
Distance_poe0Distance from colonia to point of entry 0 (San Ysidro)
Distance_poe1Distance from colonia to point of entry 1 (Otay Mesa)
Distance_poe2Distance from colonia to point of entry 2 (Tecate)
- - - -### Cross Border Model Point of Entry Wait Time -#### `CROSSBORDER_POINTOFENTRYWAITTIME.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
poe - Point of Entry number:
- 0 = San Ysidro
- 1 = Otay Mesa
- 2 = Tecate
- 3 = Otay Mesa East
- 4 = Jacumba -
StartHourStart Hour (1 through 12)
EndHourEnd Hour (1 through 12)
StartPeriod - Start Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
EndPeriod - End Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
StandardWaitStandard wait time
SENTRIWaitSENTRI users wait time
PedestrianWaitPedestrian wait time
- - - -### Cross Border Model Stop Frequency -#### `CROSSBORDER_STOPFREQUENCY.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Purpose - Tour Purpose:
- 0 = Work
- 1 = School
- 2 = Cargo
- 3 = Shop
- 4 = Visit
- 5 = Other -
DurationLoLower bound of tour duration (0, 4, or 8)
DurationHiUpper bound of tour duration (4, 8, or 24)
OutboundNumber of stops on the outbound (0, 1, 2, 3+)
InboundNumber of stops on the inbound (0, 1, 2, 3+)
PercentDistribution of tours by purpose, duration, number of outbound/inbound stops
- - - -### Cross Border Model Stop Purpose Distribution -#### `CROSSBORDER_STOPPURPOSE.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
TourPurp - Tour Purpose:
- 0 = Work
- 1 = School
- 2 = Cargo
- 3 = Shop
- 4 = Visit
- 5 = Other -
InboundBoolean for whether stop is inbound (0=No, 1=Yes)
StopNumStop number on tour (1, 2, or 3)
MultipleBoolean for whether there are multiple stops on tour (0=No, 1=Yes)
StopPurp0Distribution of Work stops
StopPurp1Distribution of School stops
StopPurp2Distribution of Cargo stops
StopPurp3Distribution of Shopping stops
StopPurp4Distribution of Visiting stops
StopPurp5Distribution of Other stops
- - - -### Cross Border Model Outbound Stop Duration Distribution -#### `CROSSBORDER_OUTBOUNDSTOPDURATION.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
RemainingLow - Lower bound of remaining half hour periods after last scheduled trip:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
RemainingHigh - Upper bound of remaining half hour periods after last scheduled trip:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
StopStop number on tour (1, 2, or 3)
0Probability that stop departure is in same period as last outbound trip
1Probability that stop departure is in last outbound trip period + 1
2Probability that stop departure is in last outbound trip period + 2
3Probability that stop departure is in last outbound trip period + 3
4Probability that stop departure is in last outbound trip period + 4
5Probability that stop departure is in last outbound trip period + 5
6Probability that stop departure is in last outbound trip period + 6
7Probability that stop departure is in last outbound trip period + 7
8Probability that stop departure is in last outbound trip period + 8
9Probability that stop departure is in last outbound trip period + 9
10Probability that stop departure is in last outbound trip period + 10
11Probability that stop departure is in last outbound trip period + 11
- - - -### Cross Border Model Inbound Stop Duration Distribution -#### `CROSSBORDER_INBOUNDSTOPDURATION.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
RemainingLow - Lower bound of remaining half hour periods after last scheduled trip:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
RemainingHigh - Upper bound of remaining half hour periods after last scheduled trip:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
StopStop number on tour (1, 2, or 3)
0Probability that stop departure period is same as tour arrival period
-1Probability that stop departure period is tour arrival period - 1
-2Probability that stop departure period is tour arrival period – 2
-3Probability that stop departure period is tour arrival period – 3
-4Probability that stop departure period is tour arrival period – 4
-5Probability that stop departure period is tour arrival period – 5
-6Probability that stop departure period is tour arrival period – 6
-7Probability that stop departure period is tour arrival period - 7
- - - -#### `EXTERNALEXTERNALTRIPSByYEAR.CSV` - - - - - - - - - - - - - - - - - - -
Column NameDescription
originTAZExternal origin TAZ
destinationTAZExternal destination TAZ
TripsNumber of trips between external TAZs
- - - -### External Internal Control Totals -#### `EXTERNALINTERNALCONTROLTOTALSByYEAR.CSV` - - - - - - - - - - - - - - - - - - -
Column NameDescription
TazExternal TAZ station
WorkNumber of work vehicle trips
NonworkNumber of non-work vehicle trips
- - - -### Internal External Tours Time of Day Distribution -#### `INTERNALEXTERNAL_TOURTOD.CSV` - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
Purpose - Tour Purpose:
- 0 = All Purposes -
EntryPeriod - Entry Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
ReturnPeriod - Return Period:
- 1 = Before 5:00AM
- 2 = 5:00AM-5:30AM
- 3 through 39 is every half hour time slots
- 40 = After 12:00AM -
PercentDistribution of tours by entry and return periods
- -### Parameters by Scenario Years -#### `PARAMETERSBYYEARS.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
yearScenario build year
aoc.fuelAuto operating fuel cost
aoc.maintenanceAuto operating maitenance cost
airport.SAN.enplanementsSan Diego International Airport enplanements
airport.SAN.connectingSan Diego International Airport connecting passengers
airport.SAN.airportMgraMGRA San Diego International Airport is located in
airport.CBX.enplanementsCross Border Express Terminal (Tijuana International Airport) enplanements
airport.CBX.connectingCross Border Express Terminal (Tijuana International Airport) connecting passengers
airport.CBX.airportMgraMGRA Cross Border Express Terminal is located in
crossBorder.toursNumber of cross border tours
crossBorders.sentriShareShare of cross border tours that are SENTRI
taxi.baseFareInitial taxi fare
taxi.costPerMileTaxi cost per mile
taxi.cosPerMinuteTaxi cost per minute
TNC.single.baseFareInitial TNC fare for single ride
TNC.single.costPerMileTNC cost per mile for single ride
TNC.single.costPerMinuteTNC cost per minute for single ride
TNC.single.costMinimumTNC minimum cost for single ride
TNC.shared.baseFareInitial TNC fare for shared ride
TNC.shared.costPerMileTNC cost per mile for shared ride
TNC.shared.costPerMinuteTNC cost per minute for shared ride
TNC.shared.costMinimumTNC minimum cost for shared ride
Mobility.AV.RemoteParkingCostPerHourRemote parking cost per hour for autonomous vehicles
active.micromobility.variableCostVariable cost for micromobility
active.micromobility.fixedCostFixed cost for micromobility
active.microtransit.fixedCostFixed cost for microtransit
Mobility.AV.ShareThe share of vehicles assumed to be autonomous vehicles in the vehicle fleet
smartSignal.factor.LC
smartSignal.factor.MA
smartSignal.factor.PA
atdm.factor
- -### Files by Scenario Years -#### `FILESBYYEARS.CSV` - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Column NameDescription
yearScenario build year
crossborder.dc.soa.alts.fileCrossborder model destination choice alternatives file
crossBorder.dc.uec.fileCrossborder model destination choice UEC file
uwsl.dc.uec.fileTour destination choice UEC file
nmdc.uec.fileNon-mandatory tour destination choice UEC file
crossBorder.tour.mc.uec.fileCrossborder model tour mode choice UEC file
visualizer.reference.pathPath to reference scenario for SANDAG ABM visualizer
- - - -### MGRAs at Mobility Hubs -#### `MOBILITYHUBMGRA.CSV` - - - - - - - - - - - - - - - - - - -
Column NameDecription
MGRAMGRA ID
MoHubNameMobility Hub name
MoHubType - Mobility Hub type:
- Suburban
- Coastal
- Gateway
- Major Employment Center
- Urban -
- -Go To Top diff --git a/outputs.md b/outputs.md deleted file mode 100644 index 6e88b449b..000000000 --- a/outputs.md +++ /dev/null @@ -1,6490 +0,0 @@ -# Model Outputs - -Model outputs are stored in the .\outputs directory. The contents of the directory are listed in the table below. - -### Output Directory (.\output) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Directory\File Name - Description -
airport.CBX (directory) - Outputs for Cross-Border Express Airport Ground Access Model -
airport.SAN (directory) - Outputs for San Diego International Airport Ground Access Model -
assignment (directory) - Assignment outputs -
crossborder (directory) - Crossborder Travel Model outputs -
cvm (directory) - Commercial Vehicle Model outputs -
parking (directory) - Parking model outputs -
resident (directory) - Resident model outputs -
skims (directory) - Skim outputs -
visitor (directory) - Visitor Model outputs -
bikeMgraLogsum.csv - Bike logsum file for close-together MGRAs -
bikeTazLogsum.csv - Bike logsum file for TAZs -
datalake_metadata.yaml - Metadata file for datalake reporting system -
derivedBikeEdges.csv - Derived bike network edge file -
derivedBikeNodes.csv - Derived bike network node file -
derivedBikeTraversals.csv - Derived bike network traversals file -
microMgraEquivMinutes.csv - Equivalent minutes for using micromobility between close-together MGRAs (not used) -
runtime_summary.csv - Summary of model runtime -
temp_tazdata_cvm.csv - TAZ data for commercial vehicle model -
transponderModelAccessibilities.csv - Transponder model accessibilities (not used) -
trip_(period).omx - Trips for each time period, for assignment -
walkMgraEquivMinutes.csv - Equivalent minutes for walking between close-together MGRAs -
- - - -### Skims (.\skims) - -This directory contains auto, transit, and non-motorized level-of-service matrices, also known as skims. Each file is a collection of origin destination tables of times and costs, at the TAZ level. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
File - Description -
dest_pmsa.omx - A matrix containing pseudo - metropolitan statistical area code for each destination TAZ -
dest_poi.omx - A matrix containing point of interest code for each destination TAZ (currently zeros) -
dest_poi.omx.csv - A csv file containing point of interest code for each destination TAZ (currently zeros) -
impm(truck type)(toll type)_(period)_(matrixtype).txt - Truck impedance matrix for truck type (ld = Light duty, lhd = light heavy duty, mhd = medium heavy duty, hhd = heavy heavy duty), toll type (n = non-toll, t = toll) and matrixtype (DU = utility, dist = distance, time = time) -
maz_maz_bike.csv - Bike logsums between close together MGRAs -
maz_maz_walk.csv - Walk times between close together MGRAs -
maz_stop_walk.csv - Walk times between MGRAs and transit stops -
taz_pmsa_xwalk.csv - Crosswalk file between pseudo-metropolitan statistical areas and TAZs -
traffic_skims_(period).omx -Auto skims by period (EA, AM, MD, PM, EV) -
transit_skims_(period).omx - Transit skims by period (EA, AM, MD, PM, EV) -
- - - - -#### Auto skims by period - -```TRAFFIC_SKIMS_