Published
2021-01-05
Issue
Section
Articles
License
Copyright (c) 2021 Robert James Schneider, Rebecca Sanders, Frank Proulx, Hamideh Moayyed
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with JTLU agree to the following terms: 1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution-Noncommercial License 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. 2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. 3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
How to Cite
United States fatal pedestrian crash hot spot locations and characteristics
Robert James Schneider
University of Wisconsin-Milwaukee
https://orcid.org/0000-0002-6225-3615
Rebecca Sanders
Arizona State University
https://orcid.org/0000-0002-9259-471X
Frank Proulx
Toole Design Group, LLC
Hamideh Moayyed
University of Wisconsin-Milwaukee
DOI: https://doi.org/10.5198/jtlu.2021.1825
Keywords: Pedestrian, Fatalities, Hot Spots, Multilane, High Speed
Abstract
US pedestrian fatalities are at their highest level in nearly three decades and account for an increasing share of total traffic fatalities (16%). To achieve the vision of a future transportation system that produces zero deaths, pedestrian safety must be improved. In this study, we screened the entire US roadway network to identify fatal pedestrian crash “hot spot” corridors: 1,000-meter-long sections of roadway where six or more fatal pedestrian crashes occurred during an eightyear period. We identified 34 hot spot corridors during 2001-2008 and 31 during 2009-2016. While only five corridors were hot spots during both analysis periods, the 60 unique hot spots had remarkably consistent characteristics. Nearly all (97%) were multilane roadways, with 70% requiring pedestrians to cross five or more lanes. More than three-quarters had speed limits of 30 mph or higher, and 62% had traffic volumes exceeding 25,000 vehicles per day. All had adjacent commercial retail and service land uses, 72% had billboards, and three-quarters were bordered by low-income neighborhoods. Corridors with these characteristics clearly have the potential to produce high numbers of pedestrian fatalities. We also used hierarchical clustering to classify the hot spots based on their roadway and surrounding landuse characteristics into three types: regional highways, urban primary arterial roadways, and New York City thoroughfares. Each context may require different safety strategies. Our results support a systemic approach to improve pedestrian safety: Agencies should identify other roadway corridors with similar characteristics throughout the US and take actions to reduce the risk of future pedestrian fatalities.
References
Ambros, J., Havránek, P., Valentová, V., Křivánková, Z., & Striegler, R. (2016). Identification of hazardous locations in regional road network–Comparison of reactive and proactive approaches. Transportation Research Procedia, 14, 4209–4217.
American Association of State Highway Transportation Professionals (AASHTO). (2010). Highway safety manual (first ed.). Washington, DC: AASHTO
Blackburn, L., Zegeer, C., & Brookshire, K. (2017). Guide for improving pedestrian safety at uncontrolled crossing locations (FHWA-SA-17-072). Washington, DC: Federal Highway Administration.
Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. https://doi.org/10.1016/j.compenvurbsys.2017.05.004
City of Oakland, California. (2017). 2017 City of Oakland pedestrian plan update. Retrieved from https://cao-94612.s3.amazonaws.com/documents/Ped-Plan-2017-rev-mar2018-edited-HIN.pdf
Clifton, K. J. & Kreamer-Fults, K. (2007). An examination of the environmental attributes associated with pedestrian-vehicular crashes near public schools. Accident Analysis & Prevention, 39(4), 708–715.
Dai, D. (2012). Identifying clusters and risk factors of injuries in pedestrian–vehicle crashes in a GIS environment. Journal of Transport Geography, 24, 206–214.
DiMaggio, C., Mooney, S., Frangos, S., & Wall, S. (2016). Spatial analysis of the association of alcohol outlets and alcohol-related pedestrian/cyclist Injuries in New York City. Injury Epidemiology, 3(1), 11.
Dumbaugh, E., & Li, W. (2010). Designing for the safety of pedestrians, cyclists, and motorists in urban environments. Journal of the American Planning Association, 77(1), 69–88.
Ecola, L., Popper, S. W., Silberglitt, R., & Fraade-Blanar, L. (2018). The road to zero: A vision for achieving zero roadway deaths by 2050, Rand Corporation, prepared for National Safety Council. Retrieved from https://www.rand.org/content/dam/rand/pubs/research_reports/RR2300/RR2333/RAND_RR2333.pdf
Elvik, R. (2008). A survey of operational definitions of hazardous road locations in some European countries. Accident Analysis & Prevention, 40(6), 1830–1835.
Ewing, R., Schieber, R. A., & Zegeer, C. V. (2003). Urban sprawl as a risk factor in motor vehicle occupant and pedestrian fatalities. American Journal of Public Health, 93(9), 1541–1545.
Ewing, R., & Dumbaugh, E. (2009). The built environment and traffic safety: A review of empirical evidence. Journal of Planning Literature, 23(4), 347–367.
Geyer, J., Raford, N., Pham, T., & Ragland, D. R. (2006). Safety in numbers: Data from
Oakland, California. Transportation Research Record: Journal of the Transportation Research Board, 1982, 150–154.
Griswold, J., Fishbain, B., Washington, S., & Ragland, D. R. (2011). Visual assessment of pedestrian crashes. Accident Analysis & Prevention, 43(1), 301–306.
Governors Highway Safety Association (GHSA). (2019). Pedestrian fatalities by state: 2018 preliminary data, spotlight on highway safety. Retrieved from https://www.ghsa.org/resources/Pedestrians19
IBM Corp. (2018). IBM SPSS statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.
Jacobsen, P. L. (2003). Safety in numbers: More walkers and bicyclists, safer walking and bicycling. Injury Prevention, 9, 205–209.
Jang, K., Park, S. H., Kang, S., Song, K. H., Kang, S., & Chung, S. (2013). Evaluation of pedestrian safety: Pedestrian crash hot spots and risk factors for injury severity. Transportation Research Record: Journal of the Transportation Research Board, 2393, 104–116.
Kim, K., & Yamashita, E. Y. (2007). Using a K-means clustering algorithm to examine patterns of pedestrian involved crashes in Honolulu, Hawaii. Journal of Advanced Transportation, 41(1), 69–89.
Lee, C., & Abdel-Aty, M. (2005). Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accident Analysis & Prevention, 37(4), 775–786.
Lefler, D. E., & Gabler, H. C. (2003). The fatality and injury risk of light truck impacts with pedestrians in the United States. Accident Analysis and Prevention, 949, 1–10.
Loukaitou-Sideris, A., Liggett, R., & Sung, H. (2007). Death on the crosswalk: A study of pedestrian-automobile collisions in Los Angeles. Journal of Planning Education and Research, 26, 338–351.
Mansfield, T., Peck, D., Morgan, D., McCann, B., & Teicher, P. (2018). The effects of roadway and built environment characteristics on pedestrian fatality risk: A national assessment at the neighborhood scale. Accident Analysis and Prevention, 121, 166–176.
Manson, S., Schroeder, J., Van Riper, D., & Ruggles, S. (2018). IPUMS national historical geographic information system: Version 13.0. Minneapolis: University of Minnesota. Retrieved from http://https://doi.org/10.18128/D050.V13.0
Miranda‐Moreno, L., Morency, P., & El-Geneidy, A. (2011). The link between built environment, pedestrian activity and pedestrian-vehicle collision occurrence at signalized intersections. Accident Analysis & Prevention, 43(5), 1624–1634.
Montella, A. (2010). A comparative analysis of hotspot identification methods. Accident Analysis & Prevention, 42(2), 571–581.
Morency, P., & Cloutier, M.-S. (2006). From targeted ‘black spots’ to area-wide pedestrian safety. Injury Prevention, 12, 360–364.
National Highway Traffic Safety Administration. (NHTSA). (1993). Traffic safety facts 1993: Pedestrians. Retrieved from https://crashstats.nhtsa.dot.gov/Api/Public/Publication/93F7
National Highway Traffic Safety Administration (NHTSA). (2007). Automated enforcement: A compendium of worldwide evaluations of results. Retrieved from http://www.nhtsa.gov/DOT/NHTSA/Traffic%20Injury%20Control/Articles/Associated%20Files/HS810763.pdf
National Highway Traffic Safety Administration (NHTSA). (2018). Fatality analysis reporting system (FARS) analytical user’s manual, 1975-2017 (DOT HS 812 602). Washington, DC: NHTSA.
National Highway Traffic Safety Administration (NHTSA). (2019a). Fatality analysis reporting system (FARS) encyclopedia, FARS data tables. Retrieved from https://www-fars.nhtsa.dot.gov/Main/index.aspx.
National Highway Traffic Safety Administration (NHTSA). (2019b). Traffic safety facts, 2017 data: Pedestrians (DOT HS 812 681). Washington, DC: NHTSA.
National Transportation Safety Board (NTSB). (2019). Accidents involving passenger fatalities: US airlines (Part 121) 1982 – present. Retrieved from https://www.ntsb.gov/investigations/data/Pages/paxfatal.aspx.
Owens, D., & Sivak, M. (1993). The role of reduced visibility in nighttime road fatalities, University of Michigan Transportation Research Institute (UMTRI-93-33). Retrieved from https://deepblue.lib.umich.edu/bitstream/handle/2027.42/49541/UMTRI-93-33.pdf?sequence=1&isAllowed=y
Owens, J. M., Dingus, T. A., Guo, F., Fang, Y., Perez, M., McClafferty, J., & Tefft, B. (2018). Prevalence of drowsy driving crashes: Estimates from a large-scale naturalistic driving study (research brief). Washington, DC: AAA Foundation for Traffic Safety.
Rankavat, S., & Tiwari, G. (2013). Pedestrian accident analysis in Delhi using GIS. Journal of the Eastern Asia Society for Transportation Studies, 10, 1446–1457.
Schneider, R. J., Khattak, A. J. & Zegeer, C. V. (2002). A proactive method of improving pedestrian safety using GIS: Example from a college campus. Transportation Research Record: Journal of the Transportation Research Board, 1773, 97–107.
Schneider, R. J., Ryznar, R. M., & Khattak, A. J. (2004). An accident waiting to happen: A spatial approach to proactive pedestrian planning. Accident Analysis and Prevention, 36, 193–211.
Schneider, R. J., Vargo, J., & Sanatizadeh, A. (2017). Comparison of US metropolitan region pedestrian and bicyclist fatality rates. Accident Analysis and Prevention, 106, 82–98.
Schuurman, N., Cinnamon, J., Crooks, V. A., & Hameed, S. M. (2009). Pedestrian injury and the built environment: An environmental scan of hotspots. BMC Public Health, 9. https://doi.org/10.1186/1471-2458-9-233
Siddiqui, N. A., Chu, X., & Guttenplan, M. (2006). Crossing locations, light conditions, and pedestrian injury severity. Transportation Research Record: Journal of the Transportation Research Board, 1982, 141–149.
Smart Growth America. (2014). Measuring sprawl 2014. Retrieved from https://www.smartgrowthamerica.org/app/legacy/documents/measuring-sprawl-2014.pdf
Smart Growth America and National Complete Streets Coalition. (2017). Dangerous by design 2016. Retrieved from https://smartgrowthamerica.org/resources/dangerous-by-design-2016/
Solano County, California. (2018). 2018 Solano County travel safety plan. Retrieved from https://sta.ca.gov/wp-content/uploads/2019/01/Solano-Travel-Safety-Plan-2018.pdf
Stimpson, J. P., Wilson, F. A., &. Muelleman, R. L. (2013). Fatalities of pedestrians, bicycle riders, and motorists due to distracted driving motor vehicle crashes in the US, 2005–2010. Public Health Reports, 128(6), 436–442.
Stoker, P., Garfinkel-Castro, A., Khayesi, M., Odero, W., Mwangi, M. N., Peden, M., & Ewing, R. (2015). Pedestrian safety and the built environment: A review of the risk factors. Journal of Planning Literature, 30(4), 377–392.
Sullivan, J. M., & Flannagan, M. J. (2001). The role of ambient light level in fatal crashes: Inferences from daylight saving time transitions. Accident Analysis & Prevention, 34(4), 487–498.
Tang, X., Eftelioglu, E., Oliver, D., & Shekhar, S. (2017). Significant linear hotspot discovery. IEEE Transactions on Big Data, 3(2).
Tefft, B. (2013). Impact speed and a pedestrian’s risk of severe injury or death. Accident Analysis and Prevention, 50, 871–878.
Thomas, L., Lan, B., Sanders, R. L., Frackelton, A., Gardner, S., & Hintze, M. (2017). Changing the future? Development and application of pedestrian safety performance functions to prioritize locations in Seattle, WA. Transportation Research Record: Journal of the Transportation Research Board, 2659, 212–223.
Thomas, L., Sandt, L., Zegeer, C., Kumfer, W., Lang, K., Lan, B., … & Schneider, R. J. (2018). Systemic pedestrian safety analysis (National Cooperative Highway Research Program, report 893). Washington, DC: National Cooperative Highway Research Program.
Toward Zero Deaths, National Strategy on Highway Safety. (2011). American Association of State Highway and Transportation Officials toward zero deaths resolution. Retrieved from http://www.towardzerodeaths.org/resource/aashto-toward-zero-deaths-resolution/
Van Houten, R., Malenfant, L., Blomberg, R. D., & Huitema, B. E. (2017). The effect of high-visibility enforcement on driver compliance with pedestrian right-of-way laws: 4-year follow-up. Washington, DC: National Highway Traffic Safety Administration.
Vision Zero Network. (2019). Vision zero cities. Retrieved from https://visionzeronetwork.org/about/vision-zero-network/elevating-efforts-in-vision-zero-cities-across-the-u-s/
Wedagama, D. P., Bird, R. N., & Metcalfe, A. V. (2006). The influence of urban land-use on non-motorized transport casualties. Accident Analysis & Prevention, 38(6), 1049–1057.
Wier, M., Weintraub, J., Humphreys, E. H., Seto, E., & Bhatia, R. (2009). An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accident Analysis & Prevention, 41(1), 137–145.
US Census Bureau. (2019). 2018 TIGER/line shapefiles. Retrieved from https://www2.census.gov/geo/tiger/TIGER2018/ROADS/
Zegeer, C. V., Nabors, D., Lagerwey, P., Sundstrom, C., Lovas, D., Huber, T., ... & Bushell, M. (2013). PEDSAFE: Pedestrian safety guide and countermeasure selection system. Washington, DC: Federal Highway Administration.
Zegeer, C., Srinivasan, R., Lan, B., Carter, D. Smith, S., Sundstrom, C., … & Van Houten, R. (2016). Development of crash modification factors for uncontrolled pedestrian crossing treatments (National Cooperative Research Program, report 841). Washington, DC: NCRP.
