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analyze high-level systemic safety and user acceptance of state highways for active transportation users. This data was also intended to inform high-level prioritization of active transportation improvements. Level of Traffic Stress (LTS) data rank highway segments from 1 to 4 based on roadway characteristics, with LTS 1 being most suited to active travel. LTS 1 was deemed suitable for all ages and abilities by WSDOT. LTS 2 is considered suitable for most active travelers. LTS 3 and 4 represent functional gaps in active transportation networks that present systemic safety issues and likely deter use of active modes. The data provided is not a substitute for detailed investigation of a location when specific investment decisions are being considered. The specific characteristics of locations with the same LTS rankings could vary considerably. It is important to note that an LTS 1 or 2 location might have additional, unmeasured characteristics that reduce its presumed suitability for active travel.Level of Traffic Stress (LTS) was described in the 2021 WSDOT Active Transportation Plan (ATP) with methodology outlined in Appendix D. This data updates the data and methods used for the ATP with additional considerations based on:Furth, P. G., Putta, T. V., & Moser, P. (2018). Measuring low-stress connectivity in terms of bike-accessible jobs and potential bike-to-work trips: A case study evaluating alternative bike route alignments in northern Delaware. Journal of Transport and Land Use, 11(1). https://doi.org/10.5198/jtlu.2018.1159. The current methodology assigns LTS rankings to roadway segments based on a combination of posted speed, traffic volume, and number of travel lanes. In addition, the presence of bike lanes of 5\u2019 or greater was used to generate Bicycle Level of Traffic Stress (BLTS) rankings. Pedestrian Level of Traffic Stress (PLTS) was calculated using the presence of sidewalks as indicated in WSDOT enterprise sidewalk data. Ramp segments are included in the dataset with a default LTS ranking of 999. This ranking indicates that all ramps are to be considered high LTS (3 or 4) unless a manual evaluation of the roadway characteristics indicates otherwise. Datasets were not available that would enable ramp rankings to be determined systematically based on posted speed, traffic volume, and number of travel lanes, however a manual review of many ramp configurations across the state indicated that most ramps present LTS concerns.For additional information regarding ranking methodology or other questions about WSDOT\u2019s Level of Traffic Stress dataset, contact: Brian.D.Wood@wsdot.wa.gov. 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These points were generated along the increasing state routes as represented by the 12/31/2021 WSDOT LRS. Points 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. These points represent the midpoint of each transect. 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 \u201cdesign vehicle\u201d 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. 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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 \u201cdesign vehicle\u201d 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. 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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 \u201cdesign vehicle\u201d 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. 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This data was also intended to inform high-level prioritization of active transportation improvements. Level of Traffic Stress (LTS) data rank highway segments from 1 to 4 based on roadway characteristics, with LTS 1 being most suited to active travel. LTS 1 was deemed suitable for all ages and abilities by WSDOT. LTS 2 is considered suitable for most active travelers. LTS 3 and 4 represent functional gaps in active transportation networks that present systemic safety issues and likely deter use of active modes. The data provided is not a substitute for detailed investigation of a location when specific investment decisions are being considered. The specific characteristics of locations with the same LTS rankings could vary considerably. It is important to note that an LTS 1 or 2 location might have additional, unmeasured characteristics that reduce its presumed suitability for active travel.Level of Traffic Stress (LTS) was described in the 2021 WSDOT Active Transportation Plan (ATP) with methodology outlined in Appendix D. This data updates the data and methods used for the ATP with additional considerations based on:Furth, P. G., Putta, T. V., & Moser, P. (2018). Measuring low-stress connectivity in terms of bike-accessible jobs and potential bike-to-work trips: A case study evaluating alternative bike route alignments in northern Delaware. Journal of Transport and Land Use, 11(1). https://doi.org/10.5198/jtlu.2018.1159. The current methodology assigns LTS rankings to roadway intersections based on a combination of posted speed and traffic volumes. Ramp segments are included in the dataset with a default LTS ranking of 999. This ranking indicates that all ramps are to be considered high LTS (3 or 4) unless a manual evaluation of the roadway characteristics indicates otherwise. Datasets were not available that would enable ramp rankings to be determined systematically based on posted speed and traffic volume, however a manual review of many ramp configurations across the state indicated that most ramps present LTS concerns.For additional information regarding ranking methodology or other questions about WSDOT\u2019s Level of Traffic Stress dataset, contact: Brian.D.Wood@wsdot.wa.gov. 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"description": "This analysis scores Census Block Groups in Washington based on their degree of equity and environmental justice need for the purpose of identifying and prioritizing investment locations for the Connecting Communities Pilot Program. Each Block Group receives a score based on several factors related to vulnerable populations and environmentally burdened communities, and these scores are added together to create the final score. See the accompanying methodology word document for a full list of factors. Original data sources are the U.S. Census 2016-2020 American Community Survey (ACS) and the Washington Environmental Health Disparities (EHD) Map.Individual scores are calculated for each measure, which then sum up to aggregate scores for vulnerable populations and overburdened communities as well as a combined final score. Block Group scores based on demographic measures from the ACS data are calculated relative to other Block Groups in similarly sized population centers or in tribal areas. If a Block Group\u2019s value for a given demographic measure is at or above the 80th percentile within its population center size category, it is given 2 points for that factor. If its value is at or above the 60th percentile within its population center size category, it is given 1 point. All other Block Groups receive 0 points for that factor. Block groups that overlap with or touch multiple population centers that have different sizes are assigned the highest possible point value based on all overlapping population centers. For the health and environmental measures sourced from the EHD map, scores are applied based on the measure\u2019s rank value. Block Groups with a rank of 9 or 10 are given 2 points, and Block Groups with a rank of 7 or 8 are given 1 point. This is applied statewide without any scaling within population center sizes, as is performed for the demographic metrics, to ensure that Block Groups with similar environmental or health burdens across the state are scored evenly. Here is a list of measures (included in attribute table), used to calculate the final score: 1. Population less than 18 years of age; 2. Population age 65 or older; 3. Housing cost-burdened households (spending over 30% of income on housing); 4. Black, Indigenous, People of color; 5. Households with 1 or more persons with a disability; 6. Ability to speak English \u2013 less than very well; 7. Household income below 200% of the federal poverty level; 8. Zero to one car households; 9. Unemployment; 10. Transportation expense (%) for moderate income families; 11. Limited access to healthy food; 12. Low birthweight (<2500 grams); 13. High rate of hospitalization, based on the maximum rank value from the following variables; (a) Death from cardiovascular disease, (b) Cancer deaths, (c) Lower life expectancy at birth, (d) Premature death; 14. Environmental exposures; 15. Environmental effects; 16. Diesel pollution burdenFinally, 1 additional point is given to Block Groups that fall within or touch a tribal area to give a slight priority to areas serving tribal populations. This score, along with the demographic measures from the ACS as well as the transportation expense, limited access to healthy food, low birthweight, and high rate of hospitalization measures from the EHD Map are summed together to create the total vulnerable population score. The three environmental measures from the EHD Map are summed together to create the total overburdened communities score. These two totals are summed to create the Block Group\u2019s final score. 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