Deriving Pedestrian Risk Index by Vehicle Type and Road Geometry at Midblock Crosswalks under Heterogeneous Traffic Conditions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 10
Abstract
Pedestrian crash data are not available in sufficiently large quantity and suffer from known problems such as a low-mean small sample, underreporting, and misclassification. Moreover, under heterogeneous traffic conditions, due to the involvement of multiple classes of vehicles, pedestrian–vehicle interactions become even more complex. To address this limitation, a pedestrian risk index (PRI) linking the probability of a crash between vehicle and pedestrian and the severity of the conflict was developed for varying road and traffic conditions. Data were analyzed from nine locations in different parts of India, accounting for variations in geographical distribution and pedestrian–vehicle interactions. The derived values of PRI were assessed by vehicle type and road geometry. The PRI value was significantly higher when the approaching vehicle was three-wheelers (3W), two-wheelers (2W), and cars compared with heavy vehicles such as buses and trucks. This indicates that the severity of conflicts is higher for lighter vehicles. Furthermore, the addition of lanes increases the PRI value. As an important outcome, variation in PRI values was modeled as a function of vehicle speed, pedestrian volume, and vehicle volume using a multilinear regression approach. The developed model can enable planners and engineers to compute PRI using the independent variables and to evaluate pedestrian safety at urban midblock crossings. Overall, this research contributes immensely to assessing the prevailing level of safety at crosswalks under heterogeneous traffic conditions, thereby improving pedestrian safety.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request, including pedestrian–vehicle trajectory data and PET data.
Acknowledgments
The work described in this article is supported by Council of Scientific & Industrial Research–Central Road Research Institute (CSIR–CRRI) Supra Institutional Network Project for Development of Indian Highway Capacity (INDO-HCM) Manual funded by Planning Commission, Government of India under 12th five-year plan.
References
Agarwal, N. K. 2011. “Estimation of pedestrian safety at intersections using simulation and surrogate safety measures.” Ph.D. dissertation, Dept. of Civil Engineering, Univ. of Kentucky.
Allen, B. L., B. T. Shin, and P. J. Cooper. 1978. Analysis of traffic conflicts and collisions. Washington, DC: Transportation Research Board.
Cafiso, S., A. Garcia, R. Cavarra, and A. R. Rojas. 2011. “Crosswalk safety evaluation using a pedestrian risk index as traffic conflict measure.” In Proc., 3rd Int. Conf. on Road Safety and Simulation. Indianapolis: Purude Univ., Transportation Research Board.
Chaudhari, A., N. Gore, S. Arkatkar, G. Joshi, and S. Pulugurtha. 2020. “Exploring pedestrian surrogate safety measures by road geometry at midblock crosswalks: A perspective under mixed traffic conditions.” IATSS Res. https://doi.org/10.1016/j.iatssr.2020.06.001.
Chin, H. C., and S. T. Quek. 1997. “Measurement of traffic conflicts.” Saf. Sci. 26 (3): 169–185. https://doi.org/10.1016/S0925-7535(97)00041-6.
Chung, Y. 2018. “Injury severity analysis in taxi-pedestrian crashes: An application of reconstructed crash data using a vehicle black box.” Accid. Anal. Prev. 111 (2018): 345–353. https://doi.org/10.1016/j.aap.2017.10.016.
Davis, G. 2001. “Relating severity of pedestrian injury to impact speed in vehicle-pedestrian crashes: Simple threshold model.” Transp. Res. Rec. 1773 (1): 108–113. https://doi.org/10.3141/1773-13.
Davis, G., K. Sanderson, and S. Davuluri. 2003. “A vehicle-pedestrian collision model for neighborhood traffic control.” In Proc., 82nd Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Gettmann, D., L. Pu, T. Sayed, and S. Shelby. 2008. Surrogate safety assessment model and validation: Final report. Rep. No. FHWA-HRT-08-051. Washington, DC: Federal Highway Administration.
Hannawald, L., and F. Kauer. 2004. Equal effectiveness study on pedestrian protection. Dresden, Germany: Technische Univ.
Hayward, J. C. 1972. Near-miss determination through use of a scale of danger. Rep. No. TTSC 7115. State College, PA: Pennsylvania State Univ.
Jiang, X., W. Wang, K. Bengler, and W. Guo. 2015. “Analyses of pedestrian behavior on mid-block unsignalized crosswalk comparing Chinese and German cases.” Adv. Mech. Eng. 7 (11): 168781401561046. https://doi.org/10.1177/1687814015610468.
Jones, D. K., K. R. Evenson, D. A. Rodriguez, and S. A. Aytur. 2010. “Addressing pedestrian safety: A content analysis of pedestrian master plans in North Carolina.” Traffic Inj. Prev. 11 (1): 57–65. https://doi.org/10.1080/15389580903434199.
Kenneth, D. L., and K. K. Ronald. 1982. Advances in business and management forecasting. Bingley, UK: Emerald Books.
Khanna, S. K., and C. E. G. Justo. 1991. Highway engineering. Roorkee, India: Nem Chand & Bros.
Laureshyn, A., A. Svensson, and C. Hydén. 2010. “Evaluation of traffic safety based on micro-level behavioural data: Theoretical framework and first implementation.” Accid. Anal. Prev. 42 (6): 1637–1646. https://doi.org/10.1016/j.aap.2010.03.021.
Maurya, A. K., and P. S. Bokare. 2012. “Study of deceleration behaviour of different vehicle types.” Int. J. Traffic Transp. Eng. 2 (3): 253–270. https://doi.org/10.7708/ijtte.2012.2(3).07.
Migletz, D. J., W. D. Glauz, and K. M. Bauer. 1985. Relationships between traffic conflicts and accidents. Washington, DC: USDOT, Federal Highway Administration.
MoRTH (Ministry of Road Transport and Highways). 2013. Study on road accidents in India. New Delhi, India: MoRTH.
NCSA (National Center for Statistics and Analysis). 2013. Pedestrians: Traffic safety facts, 2011 data. Washington, DC: National Highway Traffic Safety Administration.
Nhan, C., L. Rothman, M. Slater, and A. Howard. 2009. “Back-over collisions in child pedestrians from the Canadian Hospitals Injury Reporting and Prevention Program.” Traffic Inj. Prev. 10 (4): 350–353. https://doi.org/10.1080/15389580902995166.
NHTSA (National Highway Traffic Safety Administration). 2015. “Pedestrian safety enforcement operations: A how-to guide.” Accessed October 31, 2017. http://www.nhtsa.gov/staticfiles/nti/pdf/812059-PedestrianSafetyEnforceOperaHowToGuide.pdf.
Pasanen, E., and H. Salmivaara. 1997. “Driving speed and pedestrian safety in the City of Helsinki.” Traffic Eng. Control 34 (6): 308–310.
Pulugurtha, S. S., V. R. Duddu, and Y. Kotagiri. 2013. “Traffic analysis zone level crash estimation models based on land use characteristics.” Accid. Anal. Prev. 50 (Jan): 678–687. https://doi.org/10.1016/j.aap.2012.06.016.
Raju, N., P. Kumar, C. Reddy, S. Arkatkar, and G. Joshi. 2017. “Examining smoothening techniques for developing vehicular trajectory data under heterogeneous conditions.” J. East. Asia Soc. Transp. Stud. 12 (2017): 1549–1568. https://doi.org/10.11175/easts.12.1549.
Salamati, K., B. Schroeder, N. M. Rouphail, C. Cunningham, R. Long, and J. Barlow. 2012. “Development and implementation of a conflict-based assessment of pedestrian safety (CAPS) to evaluate accessibility of complex intersections.” Transp. Res. Rec. 2264 (1): 148–155. https://doi.org/10.3141/2264-17.
Sayed, T., M. H. Zaki, and J. Autey. 2013. “A novel approach for diagnosing road safety issues using automated computer vision techniques.” In Proc., 16th Road Safety on Four Continents Conf., 15–17. Beijing: Road Safety on Four Continents.
Silcock, D. T., R. Walker, and T. Selby. 1998. “Pedestrians at risk.” In Proc., European Transport Conf., 209–220. London: PTRC Education and Research Services Limited.
St-Aubin, P., N. Saunier, L. F. Miranda-Moreno, and K. Ismail. 2013. “Use of computer vision data for detailed driver behaviour analysis and trajectory interpretation at roundabouts.” Transp. Res. Board 2389 (1): 65–77. https://doi.org/10.3141/2389-07.
Tarko, A., and G. Davis. 2009. “Surrogate measures of safety.” In Proc., 88th Transportation Research Board Annual Meeting. Washington, DC: Transportation Research Board.
Toran Pour, A., S. Moridpour, R. Tay, and A. Rajabifard. 2017. “Modelling pedestrian crash severity at mid-blocks.” Transportmetrica A: Transp. Sci. 13 (3): 273–297. https://doi.org/10.1080/23249935.2016.1256355.
Turner, S., K. Fitzpatrick, M. Brewer, and E. S. Park. 2006. “Motorist yielding to pedestrians at unsignalized intersections: Findings from a national study on improving pedestrian safety.” Transp. Res. Rec. 1982 (1): 1–12. https://doi.org/10.1177/0361198106198200102.
van der Horst A. R. A., and J. H. Kraay. 1986. “The Dutch conflict observation technique ‘DOCTOR’.” In Proc., ICTCT Workshop. Budapest, Hungary: KTI Institute for Transport Sciences.
Varhelyi, A. 1996. Dynamic speed adaptation based on information technology—A theoretical background. Lund, Sweden: Lund Univ.
Vaughn, R. 1997. Avoiding the emerging pedestrian: A mathematical model. SAE Technical Paper 970962. Warrendale, PA: SAE International.
Venthuruthiyil, S. P., and C. Mallikarjuna. 2018. “Trajectory reconstruction using locally weighted regression: A new methodology to identify the optimum window size and polynomial order.” Transportmetrica A: Transp. Sci. 14 (10): 881–900. https://doi.org/10.1080/23249935.2018.1449032.
Wu, J., E. Radwan, and H. Abou-Senna. 2018. “Assessment of pedestrian-vehicle conflicts with different potential risk factors at midblock crossings based on driving simulator experiment.” Adv. Transp. Stud. 44 (Apr): 33–46.
Yao, J., J. Yang, and D. Otte. 2007. “Head injuries in child pedestrian accidents in depth case analysis and reconstructions.” Traffic Inj. Prev. 8 (1): 94–100. https://doi.org/10.1080/15389580600944243.
Zegeer, C., J. R. Stewart, H. H. Huang, and P. A. Lagerwey. 2001. Safety effects of marked vs. unmarked crosswalks at uncontrolled locations: Executive summary and recommended guidelines. Washington, DC: Federal Highway Administration.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 10 • October 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 24, 2019
Accepted: May 4, 2020
Published online: Aug 14, 2020
Published in print: Oct 1, 2020
Discussion open until: Jan 14, 2021
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