Despite significant advancements in motor vehicle safety, the number of fatalities resulting from road crashes has been increasing in recent years. The resultant injuries from roadway crashes are more severe for vulnerable road users (VRUs), that is, pedestrians and cyclists. High disparity is observed in the distribution of the burden of these crashes across areas and ethnic and race groups; therefore Federal Highway Administration (FHWA) requires states to incorporate equity-related variables in the assessment of VRU safety. Conventionally, the Highway Safety Manual (HSM) provides methodologies for identifying locations with high risks of crashes, but those methods have limited applications in prioritizing low-volume sites with a higher crash rate, as in the case of VRUs. This study first explores a wide range of equity-related variables at an area level in addition to site characteristics of state-maintained signalized intersections in Connecticut. This study also proposed a framework to combine site-level and area-level risk analysis to generate an aggregate network screening result, using a Bayesian Thurstonian model and a mean score ranking method. The proposed data-driven safety assessment framework is a novel practice in transportation safety analysis and shows promising results for network screening based on systemic safety principles.
National Safety Council. Position/Policy Statement Vulnerable Road Users. National Safety Council, 2018.
2.
National Highway Traffic Safety Administration. Traffic Safety Facts 2021 Data. U.S. Department of Transportation, Washington, D.C., 2023.
3.
Federal Highway Administration. VRU Safety Assessment Guidance. US Department of Transportation, Washington, D.C., 2022.
4.
LindseyG.TaoT.WangJ.CaoJ.Pedestrian and Bicycle Crash Risk and Equity: Implications for Street Improvement Projects. Road Safety Institute, University of Minnesota, Minneapolis, 2019.
5.
NantulyaV. M.ReichM. R.Equity Dimensions of Road Traffic Injuries in Low- and Middle-Income Countries. International Journal of Injury Control and Safety Promotion, Vol. 10, No. 1–2, 2003, pp. 13–20.
QinX.ShaonM. R.ChenZ.Developing Analytical Procedures for Calibrating the Highway Safety Manual Predictive Methods. Transportation Research Record: Journal of the Transportation Research Board, 2016. 2583: 91–98.
8.
RollJ.McNeilN.Race and Income Disparities in Pedestrian Injuries: Factors Influencing Pedestrian Safety Inequity. Transportation Research Part D: Transport and Environment, Vol. 107, 2022, p. 103294.
9.
ElvikR.HøyeA.VaaT.SørensenM.Vehicle Design and Protective Devices. In The Handbook of Road Safety Measures, Emerald Group Publishing Limited, Leeds, 2009, pp. 543–731. https://doi.org/10.1108/9781848552517-017.
10.
MohaiP.PellowD.RobertsJ. T.Environmental Justice. Annual Review of Environment and Resources, Vol. 34, No. 1, 2009, pp. 405–430.
11.
MoradiA.AmeriP.RahmniK.NajafiM.JamshidiE.FakhriY.Factors Affecting the Severity of Pedestrian Traffic Crashes. Archives of Trauma Research, Vol. 8, 2019, p. 46.
12.
SchneiderR. J.RyznarR. M.KhattakA. J.An Accident Waiting to Happen: A Spatial Approach to Proactive Pedestrian Planning. Accident Analysis and Prevention, Vol. 36, No. 2, 2004, pp. 193–211.
13.
WierM.WeintraubJ.HumphreysE. H.SetoE.BhatiaR.An Area-Level Model of Vehicle-Pedestrian Injury Collisions with Implications for Land Use and Transportation Planning. Accident Analysis and Prevention, Vol. 41, No. 1, 2009, pp. 137–145.
14.
TeschkeK.HarrisM. A.ReynoldsC. C. O.WintersM.BabulS.ChipmanM.Route Infrastructure and the Risk of Injuries to Bicyclists: A Case-Crossover Study. American Journal of Public Health, Vol. 102, No. 12, 2012, pp. 2336–2343.
RothmanL.HowardA.BuliungR.MacarthurC.RichmondS. A.MacphersonA.School Environments and Social Risk Factors for Child Pedestrian-Motor Vehicle Collisions: A Case-Control Study. Accident Analysis and Prevention, Vol. 98, 2017, pp. 252–258.
19.
BalakrishnanS.MoridpourS.TayR.Sociodemographic Influences on Injury Severity in Truck-Vulnerable Road User Crashes. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Vol. 5, No. 4, 2019, p. 04019015.
20.
ShaonM. R. R.ZhaoS.WangK.JacksonE.Developing a Data-Driven Network Screening Procedure for Systemic Safety Approach. Transportation Research Record: Journal of the Transportation Research Board, 2024. 267: 348–364.
21.
Texas Department of Transportation. Traffic and Safety Analysis Procedures Manual. TxDOT, Austin, TX, 2023.
ChapmanJ.FoxE.BachmanW.FrankL.Smart Location Database Technical Documentation and User Guide Version 3.0. U.S. Environment Protection Agency, Washington, D.C., 2021.
25.
DumbaughE.LiY.SahaD.MarshallW.Why Do Lower-Income Areas Experience Worse Road Safety Outcomes? Examining the Role of the Built Environment in Orange County, Florida. Transportation Research Interdisciplinary Perspectives, Vol. 16, 2022, p. 100696.
26.
TefftB. C.ArnoldL. S.Estimating Cannabis Involvement in Fatal Crashes in Washington State Before and After the Legalization of Recreational Cannabis Consumption Using Multiple Imputation of Missing Values. American Journal of Epidemiology, Vol. 190, No. 12, 2021, pp. 2582–2591.
27.
United States Department of Transportation, National Highway Traffic Safety Administration, and Office of Behavioral Safety Research. Quantifying Drowsy Driving [Traffic Safety Facts Research Note]. NHTSA, 2020. https://doi.org/10.21949/1525984.
28.
van BuurenS.Groothuis-OudshoornK.mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, Vol. 45, 2011, pp. 1–67.
DengK.HanS.LiK. J.LiuJ. S.Bayesian Aggregation of Order-Based Rank Data. Journal of the American Statistical Association, Vol. 109, No. 507, 2014, pp. 1023–1039.
31.
ThurstoneL. L.The Measurement of Social Attitudes. Journal of Abnormal and Social Psychology, Vol. 26, No. 3, 1931, pp. 249–269.
32.
GilesO. T.RomanoR.MarkkulaG.Bayesian Analysis of Subjective Ranking Data Using Thurstonian Models: Tutorial, Novel Methods, and an Open-Source Library. Open Science Framework, 2018.
33.
PlummerM.JAGS: A Program for Analysis of Bayesian Graphical Models Using Gibbs Sampling. Proc., 3rd International Workshop on Distributed Statistical Computing, Vienna, Austria, 2003, pp. 1–10.
34.
HauerE.Traffic Conflicts and Exposure. Accident Analysis and Prevention, Vol. 14, No. 5, 1982, pp. 359–364.
35.
OsamaA.AlbitarM.SayedT.BigazziA.Determining If Walkability and Bikeability Indices Reflect Pedestrian and Cyclist Safety. Transportation Research Record: Journal of the Transportation Research Board, 2020. 2674(9): 767–775.
