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First published online January 1, 2017

Preliminary Investigation of the Effectiveness of High-Visibility Crosswalks on Pedestrian Safety Using Crash Surrogates

M. Tawfiq Sarwar [email protected], Grigorios Fountas, Courtney Bentley, Panagiotis C. Anastasopoulos, Alan Blatt, John Pierowicz, Kevin Majka, and Robert LimogesView all authors and affiliations
Volume 2659, Issue 1
https://doi.org/10.3141/2659-20

Abstract

This paper, with the use of data from the SHRP 2 naturalistic driving study, provides a preliminary evaluation of the effectiveness of high-visibility crosswalks (HVCs) in improving pedestrian safety at un-controlled locations. This evaluation was accomplished by analyzing the driving behavior of SHRP 2 participants at three uncontrolled locations at the Erie County, New York, test site. In this context, crash surrogates (i.e., speed, acceleration, throttle pedal actuation, and brake application) were used to evaluate the participants’ driving behavior, primarily on the basis of data from before and after the HVC installation. The before–after analysis allowed the assessment of HVC effectiveness in driver behavior modification. Mixed logit and random parameters linear regression models were estimated, and panel effects and unobserved heterogeneity were accounted for. Several factors were explored and controlled for (e.g., vehicle and driver characteristics, roadside environment, weather conditions), and the preliminary exploratory results show that HVCs can improve pedestrian safety and positively modify driving behavior.

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References

1. NHTSA, 2015. Traffic Safety Facts, 2013 Data: Pedestrians. DOT HS 812 124. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812124. Accessed July 18, 2016.
Google Scholar
2. Centers for Disease Control and Prevention, 2015. Web-Based Injury Statistics Query and Reporting System (WISQARS). http://www.cdc.gov/injury/wisqars/index.html. Accessed July 18, 2016.
Google Scholar
3. New York State Highway Safety Strategic Plan FFY 2015. www.nhtsa.gov/links/StateDocs/FY15/FY15HSPs/NY_FY15HSP.pdf. Accessed July 18, 2016.
Google Scholar
4. Zegeer C. V., Steward J. R., Huang H. H., Lagerwey P. A., Feaganes J., and Campbell B. J. Safety Effects of Marked Versus Unmarked Crosswalks at Uncontrolled Locations. FHWA-HRT-04-100. FHWA, U.S. Department of Transportation, 2005.
Google Scholar
5. Aziz H. A., Ukkusuri S. V., and Hasan S. Exploring the Determinants of Pedestrian–Vehicle Crash Severity in New York City. Accident Analysis and Prevention, Vol. 50, 2013, pp. 1298–1309. https://doi.org/10.1016/j.aap.2012.09.034.
Google Scholar
6. Haleem K., Alluri P., and Gan A. Analyzing Pedestrian Crash Injury Severity at Signalized and Non-Signalized Locations. Accident Analysis and Prevention, Vol. 81, 2015, pp. 14–23. https://doi.org/10.1016/j.aap.2015.04.025.
Google Scholar
7. Olszewski P., Szagala P., Wolański M., and Zielińska A. Pedestrian Fatality Risk in Accidents at Unsignalized Zebra Crosswalks in Poland. Accident Analysis and Prevention, Vol. 84, 2015, pp. 83–91. https://doi.org/10.1016/j.aap.2015.08.008.
Google Scholar
8. Papadimitriou E., Yannis G., and Golias J. A Critical Assessment of Pedestrian Behaviour Models. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 12, No. 3, 2009, pp. 242–255. https://doi.org/10.1016/j.trf.2008.12.004.
Google Scholar
9. Mitman M. F., Cooper D., and DuBose B. Driver and Pedestrian Behavior at Uncontrolled Crosswalks in Tahoe Basin Recreation Area of California. Transportation Research Record: Journal of the Transportation Research Board, No. 2198, 2010, pp. 23–31. https://doi.org/10.3141/2198-04.
Google Scholar
10. Tefft B. C. Impact Speed and a Pedestrian’s Risk of Severe Injury or Death. Accident Analysis and Prevention, Vol. 50, 2013, pp. 871–878. https://doi.org/10.1016/j.aap.2012.07.022.
Google Scholar
11. Kröyer H. R. G., Jonsson T., and Várhelyi A. Relative Fatality Risk Curve to Describe the Effect of Change in the Impact Speed on Fatality Risk of Pedestrians Struck by a Motor Vehicle. Accident Analysis and Prevention, Vol. 62, 2014, pp. 143–152. https://doi.org/10.1016/j.aap.2013.09.007.
Google Scholar
12. Jurecki R. S., and Stanćzyk T. L. Driver Reaction Time to Lateral Entering Pedestrian in a Simulated Crash Traffic Situation. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 27, 2014, pp. 22–36. https://doi.org/10.1016/j.trf.2014.08.006.
Google Scholar
13. McGrane A., and Mitman M. An Overview and Recommendations of High-Visibility Crosswalk Marking Styles. University of North Carolina, Highway Safety Research Center, Pedestrian and Bicycle Information, Chapel Hill, 2013. http://www.pedbikeinfo.org/cms/downloads/PBIC_WhitePaper_Crosswalks.pdf. Accessed July 19, 2016.
Google Scholar
14. Dougald L. E. Effectiveness of a Rectangular Rapid-Flashing Beacon at a Midblock Crosswalk on a High-Speed Urban Collector. Transportation Research Record: Journal of the Transportation Research Board, No. 2562, 2016, pp. 36–44. https://doi.org/10.3141/2562-05.
Google Scholar
15. Knoblauch R. L., and Raymond P. D. The Effect of Crosswalk Markings on Vehicle Speeds in Maryland, Virginia, and Arizona. FHWA-RD-00-101, FHWA, U.S. Department of Transportation, 2000.
Google Scholar
16. Knoblauch R. L., Nitzburg M., and Seifert R. F. Pedestrian Crosswalk Case Studies: Sacramento, California; Richmond, Virginia; Buffalo, New York; Stillwater, Minnesota. FHA-RD-00-103. FHWA, U.S. Department of Transportation, 2001.
Google Scholar
17. Mead J., Zeeger C., and Bushell M. Evaluation of Pedestrian-Related Roadway Measures: A Summary of Available Research. DTFH61-11-H-00024. University of North Carolina at Chapel Hill and FHWA, U.S. Department of Transportation, 2014. http://www.pedbikeinfo.org/cms/downloads/PedestrianLitReview_April2014.pdf. Accessed June 16, 2016.
Google Scholar
18. Guo Y., Liu P., Liang Q., and Wang W. Effects of Parallelogram-Shaped Pavement Markings on Vehicle Speed and Safety of Pedestrian Crosswalks on Urban Roads in China. Accident Analysis and Prevention, Vol. 95, 2016, pp. 438–447. http://dx.doi.org/https://doi.org/10.1016/j.aap.2015.07.001.
Google Scholar
19. Gómez R. A., Samuel S., Romoser M. R., Gerardino L. R., Knodler M., Collura J., and Fisher D. L. A Driving Simulator Evaluation of Road Markings and Symbolic Signs on Vehicle-Pedestrian Conflicts. Presented at Road Safety on Four Continents: 16th International Conference, Beijing, 2013.
Google Scholar
20. Samuel S., Romoser M. R. E., Gerardino L. R., Hamid M., Gómez R. A., Knodler M. A. Jr., Collura J., and Fisher D. L. Effect of Advance Yield Markings and Symbolic Signs on Vehicle–Pedestrian Conflicts: Field Evaluation. Transportation Research Record: Journal of the Transportation Research Board, No. 2393, 2013, pp. 139–146. https://doi.org/10.3141/2393-16.
Google Scholar
21. SHRP 2. Accelerating Solutions for Highway Safety, Renewal, Reliability, and Capacity. http://www.trb.org/AboutTRB/SHRP2.aspx. Accessed July 16, 2016.
Google Scholar
22. Anderson I. B., and Krammes R. A. Speed Reduction as a Surrogate for Accident Experience at Horizontal Curves on Rural Two-Lane Highways. Transportation Research Record: Journal of the Transportation Research Board, No. 1701, 2000, pp. 86–94. https://doi.org/10.3141/1701-11.
Google Scholar
23. Hadi M. A., and Thakkar J. Speed Differential as a Measure to Evaluate the Need for Right-Turn Deceleration Lanes at Unsignalized Intersections. Transportation Research Record: Journal of the Transportation Research Board, No. 1847, 2003, pp. 58–65. https://doi.org/10.3141/1847-08.
Google Scholar
24. Guo F., Klauer S. G., Hankey J. M., and Dingus T. A. Near Crashes as Crash Surrogate for Naturalistic Driving Studies. Transportation Research Record: Journal of the Transportation Research Board, No. 2147, 2010, pp. 66–74. https://doi.org/10.3141/2147-09.
Google Scholar
25. Tarko A. P., Anastasopoulos P. C., and Pérez-Zuriaga A. M. Can Education and Enforcement Affect Behavior of Car and Truck Drivers on Urban Freeways? Presented at 3rd International Conference on Road Safety and Simulation, Indianapolis, Ind., 2011.
Google Scholar
26. Mohamed M. G., and Saunier N. Motion Prediction Methods for Surrogate Safety Analysis. Transportation Research Record: Journal of the Transportation Research Board, No. 2386, 2013, pp. 168–178. https://doi.org/10.3141/2386-19.
Google Scholar
27. Wang C., and Stamatiadis N. Derivation of a New Surrogate Measure of Crash Severity. Transportation Research Record: Journal of the Transportation Research Board, No. 2432, 2014, pp. 37–45. https://doi.org/10.3141/2432-05.
Google Scholar
28. Vedagiri P., and Killi D. V. Traffic Safety Evaluation of Uncontrolled Intersections Using Surrogate Safety Measures Under Mixed Traffic Conditions. Transportation Research Record: Journal of the Transportation Research Board, No. 2512, 2015, pp. 81–89. https://doi.org/10.3141/2512-10.
Google Scholar
29. Anastasopoulos P. C., and Mannering F. L. The Effect of Speed Limits on Drivers’ Choice of Speed: A Random Parameters Seemingly Unrelated Equations Approach. Analytic Methods in Accident Research, Vol. 10, 2016, pp. 1–11. https://doi.org/10.1016/j.amar.2016.03.001.
Google Scholar
30. Dougald L. E. Development of Guidelines for the Installation of Marked Crosswalks. Virginia Transportation Research Council, Charlottesville, Va., 2004.
Google Scholar
31. Choi S., and Oh C. Proactive Strategy for Variable Speed Limit Operations on Freeways Under Foggy Weather Conditions. Transportation Research Record: Journal of the Transportation Research Board, No. 2551, 2016, pp. 29–36. https://doi.org/10.3141/2551-04.
Google Scholar
32. Wu K.-F., and Jovanis P. P. Screening Naturalistic Driving Study Data for Safety-Critical Events. Transportation Research Record: Journal of the Transportation Research Board, No. 2386, 2013, pp. 137–146. https://doi.org/10.3141/2386-16.
Google Scholar
33. Shankar V., Jovanis P. P., Aguero-Valverde J., and Gross F. Analysis of Naturalistic Driving Data: Prospective View on Methodological Paradigms. Transportation Research Record: Journal of the Transportation Research Board, No. 2061, 2008, pp. 1–8. https://doi.org/10.3141/2061-01.
Google Scholar
34. Peesapati L. N., Hunter M., Rodgers M., and Guin A. A Profiling Based Approach to Safety Surrogate Data Collection. Presented at 3rd International Conference on Road Safety and Simulation, Indianapolis, Ind., 2011.
Google Scholar
35. Tarko A., Davis G., Saunier N., Sayed T., and Washington S. Surrogate Measures of Safety. White paper. Subcommittee on Surrogate Measures of Safety, Committee on Safety Data, Evaluation, and Analysis, Transportation Research Board, Washington, D.C., 2009.
Google Scholar
36. Shoarian-Sattari K., and Powell D. Measured Vehicle Flow Parameters as Predictors in Road Traffic Accident Studies. Traffic Engineering and Control, Vol. 28, No. 6, 1987, pp. 328–335.
Google Scholar
37. Klauer S. G., Dingus T. A., Neale V. L., Sudweeks J. D., and Ramsey D. J. The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data. DOT HS 810 594. NHTSA, U.S. Department of Transportation, 2006.
Google Scholar
38. Hamed M., and Mannering F. L. Modeling Travelers’ Post-Work Activity Involvement: Toward a New Methodology. Transportation Science, Vol. 27, No. 4, 1993, pp. 381–394. https://doi.org/10.1287/trsc.27.4.381.
Google Scholar
39. Young R. K., and Liesman J. Estimating the Relationship Between Measured Wind Speed and Overturning Truck Crashes Using a Binary Logit Model. Accident Analysis and Prevention, Vol. 39, No. 3, 2007, pp. 574–580. https://doi.org/10.1016/j.aap.2006.10.002.
Google Scholar
40. Sarwar M. T., Anastasopoulos P. C., Ukkusuri S. V., Murray-Tuite P., and Mannering F. L. A Statistical Analysis of the Dynamics of Household Hurricane-Evacuation Decisions. Transportation: Planning, Policy, Research, Practice, Vol. 43, No. 3, 2016, pp. 1–20. https://doi.org/10.1007/s11116-016-9722-6.
Google Scholar
41. Train K. Halton Sequences for Mixed Logit. Department of Economics. University of California, Berkley, 1999.
Google Scholar
42. Bhat C. Simulation Estimation of Mixed Discrete Choice Models Using Randomized and Scrambled Halton Sequences. Transportation Research Part B: Methodological, Vol. 37, No. 9, 2003, pp. 837–855. https://doi.org/10.1016/S0191-2615(02)00090-5.
Google Scholar
43. Anastasopoulos P. C., and Mannering F. L. An Empirical Assessment of Fixed and Random Parameter Logit Models Using Crash- and Non-Crash-Specific Injury Data. Accident Analysis and Prevention, Vol. 43, No. 3, 2011, pp. 1140–1147. https://doi.org/10.1016/j.aap.2010.12.024.
Google Scholar
44. Washington S., Karlaftis M. G., and Mannering F. L. Statistical and Econometric Methods for Transportation Data Analysis, 2nd ed. CRC Press, Boca Raton, Fla., 2011.
Google Scholar
45. McFadden D. Econometric Models of Probabilistic Choice. In Structural Analysis of Discrete Data with Econometric Applications (Manski C. and McFadden D., eds.), MIT Press, Cambridge, Mass., 1981.
Google Scholar
46. Anastasopoulos P. C., and Mannering F. L. A Note on Modeling Vehicle-Accident Frequencies with Random Parameter Count Models. Accident Analysis and Prevention, Vol. 41, No. 1, 2009, pp. 153–159. https://doi.org/10.1016/j.aap.2008.10.005.
Google Scholar
47. Russo B., Savolainen P., Schneider W. IV, and Anastasopoulos P. C. Comparison of Factors Affecting Injury Severity in Angle Collisions by Fault Status Using a Random Parameters Bivariate Ordered Probit Model. Analytic Methods in Accident Research, Vol. 2, 2014, pp. 21–29. https://doi.org/10.1016/j.amar.2014.03.001.
Google Scholar
48. Anastasopoulos P. C. Random Parameters Multivariate Tobit and Zero-Inflated Count Data Models: Addressing Unobserved and Zero-State Heterogeneity in Accident Injury-Severity Rate and Frequency Analysis. Analytic Methods in Accident Research, Vol. 11, 2016, pp. 17–32. https://doi.org/10.1016/j.amar.2016.06.001.
Google Scholar
49. Milton J., Shankar V., and Mannering F. L. Highway Accident Severities and the Mixed Logit Model: An Exploratory Empirical Analysis. Accident Analysis and Prevention, Vol. 40, No. 1, 2008, pp. 260–266. https://doi.org/10.1016/j.aap.2007.06.006.
Google Scholar
50. Anastasopoulos P. C., and Mannering F. L. Analysis of Pavement Overlay and Replacement Performance Using Random-Parameters Hazard-Based Duration Models. ASCE Journal of Infrastructure Systems, Vol. 21, No. 1, 2014, pp. 04014024 (1–13). https://doi.org/10.1061/(ASCE)IS.1943-555X.0000208.
Google Scholar
51. Sarwar M. T., and Anastasopoulos P. C. Three-Stage Least Squares Analysis of Postrehabilitation Pavement Performance. Transportation Research Record: Journal of the Transportation Research Board, No. 2589, 2016, pp. 97–109. https://doi.org/10.3141/2589-11.
Google Scholar
52. Anastasopoulos P. C., Sarwar M. T., and Shankar V. Safety-Oriented Pavement Performance Thresholds: Accounting for Unobserved Heterogeneity in a Multi-Objective Optimization and Goal Programming Approach. Analytic Methods in Accident Research, Vol. 12, 2016, pp. 35–47. https://doi.org/10.1016/j.amar.2016.10.001.
Google Scholar
53. Anwaar A., Van Boxel D., Volovski M., Anastasopoulos P. C., Labi S., and Sinha K. C. Using Lagging Headways to Estimate Passenger Car Equivalents on Basic Freeway Sections. Journal of Transportation of the Institute of Transportation Engineers, Vol. 2, No. 1, 2011, pp. 1–17.
Google Scholar
54. Sarwar M. T., and Anastasopoulos P. C. The Effect of Long Term Non-Evasive Pavement Deterioration on Accident Injury-Severity Rates: A Seemingly Unrelated and Multivariate Equations Approach. Analytic Methods in Accident Research, Vol. 13, 2017, pp. 1–15. https://doi.org/10.1016/j.amar.2016.10.003.
Google Scholar

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Volume 2659, Issue 1
Pages: 182 - 191
Article first published online: January 1, 2017
Issue published: January 2017

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Authors

Affiliations

M. Tawfiq Sarwar
Turner–Fairbank Highway Research Center, FHWA, U.S. Department of Transportation, 6300 Georgetown Pike, T-210, McLean, VA 22101
[email protected]
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Grigorios Fountas
Room 204, Department of Civil, Structural, and Environmental Engineering and Engineering Statistics and Econometrics Application Research Laboratory, State University of New York at Buffalo, Ketter Hall, Buffalo, NY 14260
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Courtney Bentley
Room 204B, Department of Civil, Structural, and Environmental Engineering and Engineering Statistics and Econometrics Application Research Laboratory, State University of New York at Buffalo, Ketter Hall, Buffalo, NY 14260
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Panagiotis C. Anastasopoulos
Room 241, Department of Civil, Structural, and Environmental Engineering, Institute for Sustainable Transportation and Logistics, and Engineering Statistics and Econometrics Application Research Laboratory, State University of New York at Buffalo, Ketter Hall, Buffalo, NY 14260
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Alan Blatt
Public Safety and Transportation Group, CUBRC, 4455 Genesee Street, Suite 106, Buffalo, NY 14225
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John Pierowicz
Public Safety and Transportation Group, CUBRC, 4455 Genesee Street, Suite 106, Buffalo, NY 14225
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Kevin Majka
Public Safety and Transportation Group, CUBRC, 4455 Genesee Street, Suite 106, Buffalo, NY 14225
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Robert Limoges
New York State Department of Transportation, 50 Wolf Road, POD 5-2, Albany, NY 12232
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Notes

M. T. Sarwar, [email protected].

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