The 2017/2018 Regional Travel Survey (RTS) collected demographic and travel information from a randomly selected representative sample of households in the National Capital Region Transportation Planning Board (TPB) jurisdictions and adjacent areas, which comprise the TPB model region. It is the primary source of observed data to estimate, calibrate, and validate the regional travel demand model. The model in turn is used for the travel forecasting and air quality conformity analysis of the region’s long-range transportation plan as well as to support other key program activities. The survey data is also used for analyzing regional travel trends and provides a comprehensive picture of travel patterns in the region. The RTS captured information on household, person, and vehicle characteristics in the recruitment survey, and actual observed trip information in a one-day travel diary, which household members recorded details of every trip taken on their assigned travel day.From October 2017 through December 2018, the Regional Travel Survey (RTS) collected information on demographic and travel behavior characteristics of persons living in households in the metropolitan Washington region and adjoining jurisdictions. Under the oversight of COG/TPB, the survey was conducted by a nationally recognized transportation survey research firm, Resource Systems Group, Inc. (RSG). Previous COG/TPB regional household surveys for the Washington area were conducted in 1968, 1987/1988, 1994, and 2007/2008. This document describes the technical approach used for the RTS. It provides a brief overview of the survey methodology. Additional information about the survey methodology, including the questionnaire design, survey sampling, survey administration, targeted outreach, and survey response can be found in the final report prepared by RSG (Appendix A). Due to the complexity of multi-modal travel patterns in the National Capital Region, review and editing of the RTS data files was performed internally by staff familiar with travel patterns in the region. This report is primarily focused on the post-survey data processing and survey expansion performed by COG/TPB staff. Appendices also contain file format and file frequency tables for the final public release files.For more information about the RTS, please visit the RTS webpage.To download the RTS Tabulations, please visit the Regional Travel Survey (RTS) Tabulations page.The RTS Public File is also available by request.

Frequent, reliable transit service is the foundation of a transportation system that empowers all travelers and makes Seattle a truly transit-friendly city. A robust transit network is essential if Seattle is to meet its climate goals and address transportation-related inequities. At its most fundamental level, a transit network is made up of transit infrastructure such as bus lanes, transit signals, and bus stops, often arranged in corridors. The transit service that travels on this infrastructure can be described as a series of routes that connect different parts of a community for a number of hours per day at a certain frequency (the number of trips at a bus stop per hour). SDOT’s vision for the service aspect of the transit network is followed by a vision for transit infrastructure in the sections below. Public input and surveys consistently point to transit frequency as the most critical factor that influences ridership behavior. This fundamental concept directly informs SDOT’s shared vision for a “Frequent Transit Network” (FTN), which builds from the 2016 Transit Master Plan (TMP) and establishes aspirational frequency targets for transit corridors throughout the city. A high-frequency transit network enables people to move through the city with confidence in a timely arrival—and without the need to consult a schedule—throughout the day and every single day of the week. Continual investment in improved transit frequency in Seattle is essential for many reasons: Post-pandemic transit is likely to remain less commuter-focused and oriented specifically to Downtown Seattle and must adapt to new travel behaviors and patterns. To support everyday trips by transit (not just commutes), people need reliable mobility at all times, such as early mornings, midday, evenings and at night all days of the week, not just at peak times on weekdays. Transit needs to accommodate work schedules of non-traditional and low-income workers including the times noted above. Transit should be attractive for all types of trips throughout the week, including education, shopping, and recreational trips, as well as cultural gatherings. An excellent transit network is necessary to accommodate the mode shift required to respond to the impacts of climate change in the next decade. Frequent transit reduces wait time, increases reliability, and values the time for existing and future riders. Frequent transit makes transfers more feasible and allows a network of routes to function as a system. A connected network of frequent transit services is also critical to achieve STP climate goals, which require dramatic increases in transit ridership and VMT reduction to support broader efforts to reduce greenhouse gas (GHG) emissions from transportation. High transit frequencies as part of a reliable, all-day service network can create a more equitable transportation system, making it possible for people of all ages, incomes, and abilities to get where they want to go regardless of when or where they need to travel. The Transit Element presents a vision for frequent transit service in Seattle that goes beyond the original Frequent Transit Network (FTN) presented in the 2016 Transit Master Plan. Refresh Cycle: None, Static. Manually as required.Original Publish: 5/23/2024Update Publish: 7/11/2024 per Policy and Planning teamContact: Policy and Planning team.

The Transportation Tomorrow Survey (TTS) is a travel survey conducted in Ontario's Greater Golden Horseshoe asking detailed questions about respondents' travel behaviour. You can learn more from the Data Management Group's website.This table shows a half-hour aggregation of trip start times as reported in the TTS. It should be noted that rounding of start times by participants can cause reported start times on the half-hour to be less frequent than on the full hour.

The transit service that travels on this infrastructure can be described as a series of routes that connect different parts of a community for a number of hours per day at a certain frequency (the number of trips at a bus stop per hour). SDOT’s vision for the service aspect of the transit network is followed by a vision for transit infrastructure in the sections below. Public input and surveys consistently point to transit frequency as the most critical factor that influences ridership behavior. This fundamental concept directly informs SDOT’s shared vision for a “Frequent Transit Network” (FTN), which builds from the 2016 Transit Master Plan (TMP) and establishes aspirational frequency targets for transit corridors throughout the city. A high-frequency transit network enables people to move through the city with confidence in a timely arrival—and without the need to consult a schedule—throughout the day and every single day of the week. Continual investment in improved transit frequency in Seattle is essential for many reasons: Post-pandemic transit is likely to remain less commuter-focused and oriented specifically to Downtown Seattle and must adapt to new travel behaviors and patterns. To support everyday trips by transit (not just commutes), people need reliable mobility at all times, such as early mornings, midday, evenings and at night all days of the week, not just at peak times on weekdays. Transit needs to accommodate work schedules of non-traditional and low-income workers including the times noted above. Transit should be attractive for all types of trips throughout the week, including education, shopping, and recreational trips, as well as cultural gatherings. An excellent transit network is necessary to accommodate the mode shift required to respond to the impacts of climate change in the next decade. Frequent transit reduces wait time, increases reliability, and values the time for existing and future riders. Frequent transit makes transfers more feasible and allows a network of routes to function as a system. A connected network of frequent transit services is also critical to achieve STP climate goals, which require dramatic increases in transit ridership and VMT reduction to support broader efforts to reduce greenhouse gas (GHG) emissions from transportation. High transit frequencies as part of a reliable, all-day service network can create a more equitable transportation system, making it possible for people of all ages, incomes, and abilities to get where they want to go regardless of when or where they need to travel. The Transit Element presents a vision for frequent transit service in Seattle that goes beyond the original Frequent Transit Network (FTN) presented in the 2016 Transit Master Plan. Refresh Cycle: None, Static. Manually as required.

This feature class represents the transects that were used for the Route Directness Index calculation. These lines were generated along the increasing state routes as represented by the 12/31/2021 WSDOT LRS. Transects were only generated within Population Centers as defined by the 2021 Active Transportaiton Plan. Every 250 feet along the route a transect was created perpendicular to the route extending 500 feet on each side of the route. The end points of each transect were then used to calculate the direct distance between the endpoints and were used to generate the shortest walking route between the endpoints.The Route Directness Index (RDI) is a ratio that compares the straight-line (crow-flies) distance across a barrier and between two points to the actual distance imposed by the network of paths available to a traveler. RDI data is particularly relevant to pedestrian and/or bicyclist trips due to the extra time, physical energy, and exposure to weather out of direction travel creates. Research indicates that pedestrians are especially sensitive to out of direction travel and Broach, 2016, found that "to avoid an additional unsignalized arterial crossing, a pedestrian would be willing to go over 70 meters (230 feet) farther via an alternate path." This finding suggests that route directness is relevant to considerations of both utility and safety with respect to active travel. A complete discussion of route directness, including potential applications to decision making, can be found Washington State Multimodal Permeability Pilot, August 2021.RDI can be analyzed at different scales. A high-level analysis of RDI can address questions that compare population centers across the state or consider whether the RDI values are generally similar within a given population center or tend to vary in different portions of a population center. High level data could be combined with other statewide data such as crash data, transit stops, level of traffic stress data, destination data, etc. to analyze potential correlations. High level RDI data is less useful for analyzing a particular crossing location or recommending solutions to address high RDI values. A more detailed analysis is likely required when questions involve corridor studies or project evaluations. Detailed location information can refer to key destinations and crossing locations that are not captured using higher level network maps.The lowest RDI is 1 because a trip between those points can be made directly along an existing roadway. The actual methodology analyzed hypothetical trips where the start and end points were about a quarter mile apart relative to a straight line. In such a situation, an RDI of 2 would mean the trip is twice the distance it might otherwise be, or about one-half mile. Although one-half mile is not particularly far, the RDI is independent of the actual distance. We might start further down the road and if the RDI remained a 2 our trip distance would be twice as long as it could have been. The RDI thus measures the real or perceived burden or travel cost incurred by a person walking or bicycling. An RDI of 2 was selected as the threshold where that travel cost makes it increasingly unlikely that an active travel trip would be completed. The “design vehicle” when selecting that threshold was a walking pedestrian. Selecting an RDI of 2 was an attempt to balance observed travel behavior and the realities of existing crossing opportunities along the state highway system. In addition, since this analysis used about a quarter-mile spacing between test destinations, an RDI of 2 corresponds to the one-half mile maximum distance transit planners assume a pedestrian will be willing to walk to catch a bus or train. (FHWA, Pedestrian Safety Guide for Transit, 2013) So with respect to multimodal trips, RDIs greater than 2 might make transit less attractive.

Developed in collaboration with Experian and YouGov to create a travel segmentation of the population of the West Midlands Combined Authority, in order to understand travel behaviour, service uptake and enabling modal shift behaviour change.The groups are:Traditional WaysStriving to Get AheadPressured FamiliesComfort in My CommunityProgressive FamiliesComfortable Empty NestersSmart Digital FamiliesCarefree Affluence

This feature class represents the routes that were used for the Route Directness Index calculation. These routes were generated by submitting the begin and end points of each RDI_Transect to the Esri routing service with a Walking travel mode. The service returns a route of the shortest pedestrian path between the two points. The routing service is dependent on the Esri network data available when the service was accessed in June 2022.The Route Directness Index (RDI) is a ratio that compares the straight-line (crow-flies) distance across a barrier and between two points to the actual distance imposed by the network of paths available to a traveler. RDI data is particularly relevant to pedestrian and/or bicyclist trips due to the extra time, physical energy, and exposure to weather out of direction travel creates. Research indicates that pedestrians are especially sensitive to out of direction travel and Broach, 2016, found that "to avoid an additional unsignalized arterial crossing, a pedestrian would be willing to go over 70 meters (230 feet) farther via an alternate path." This finding suggests that route directness is relevant to considerations of both utility and safety with respect to active travel. A complete discussion of route directness, including potential applications to decision making, can be found Washington State Multimodal Permeability Pilot, August 2021.RDI can be analyzed at different scales. A high-level analysis of RDI can address questions that compare population centers across the state or consider whether the RDI values are generally similar within a given population center or tend to vary in different portions of a population center. High level data could be combined with other statewide data such as crash data, transit stops, level of traffic stress data, destination data, etc. to analyze potential correlations. High level RDI data is less useful for analyzing a particular crossing location or recommending solutions to address high RDI values. A more detailed analysis is likely required when questions involve corridor studies or project evaluations. Detailed location information can refer to key destinations and crossing locations that are not captured using higher level network maps.The lowest RDI is 1 because a trip between those points can be made directly along an existing roadway. The actual methodology analyzed hypothetical trips where the start and end points were about a quarter mile apart relative to a straight line. In such a situation, an RDI of 2 would mean the trip is twice the distance it might otherwise be, or about one-half mile. Although one-half mile is not particularly far, the RDI is independent of the actual distance. We might start further down the road and if the RDI remained a 2 our trip distance would be twice as long as it could have been. The RDI thus measures the real or perceived burden or travel cost incurred by a person walking or bicycling. An RDI of 2 was selected as the threshold where that travel cost makes it increasingly unlikely that an active travel trip would be completed. The “design vehicle” when selecting that threshold was a walking pedestrian. Selecting an RDI of 2 was an attempt to balance observed travel behavior and the realities of existing crossing opportunities along the state highway system. In addition, since this analysis used about a quarter-mile spacing between test destinations, an RDI of 2 corresponds to the one-half mile maximum distance transit planners assume a pedestrian will be willing to walk to catch a bus or train. (FHWA, Pedestrian Safety Guide for Transit, 2013) So with respect to multimodal trips, RDIs greater than 2 might make transit less attractive.

The Transportation Tomorrow Survey (TTS) is a travel survey conducted in Ontario's Greater Golden Horseshoe asking detailed questions about respondents' travel behaviour. You can learn more from the Data Management Group's website.This map shows trips identified as work trips which at some point use the GO Transit network as a fraction of total work trips made. The GO Transit 2018 rail network is included to allow viewers to identify how rail corridors intensify go transit use. Geographically, the area is divided into traffic zones to allow for a greater level of detail in visualizing the spatial distribution of GO Transit use.