Preventing Intersection Rear-End Collisions with an Optimized Dynamic Two-Stage Actuated Control
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 9
Abstract
To minimize the likelihood of having rear-end collisions at signalized intersections, this study presents two algorithms for use with an actuated signal controller and the wide-ranger sensor, deployed for dynamic all-red extension. The first algorithm features its replacement of conventional gap-out control with vehicles detected in a field-calibrated dilemma zone and executes a phase transition only if no vehicle is within the detected zone. To further assure no rear-end collisions occur during either the defaulted green max-out or extended max-out, this study has further proposed a dynamic two-stage control algorithm that can optimally divide the duration between the minimum and maximum greens into two stages, where the signal within stage-1 duration will operate the first algorithm for green termination to ensure its efficiency, but shall execute the phase transition within stage-2 only at the time point projected to have the least likelihood of incurring rear-end collisions between any pairs of leading-following vehicles within the sensor’s monitoring zone. Because the effectiveness of such algorithms depends on the accuracy and reliability of their key parameters, the study has detailed their operational logic and the procedures for system calibration with field data, traffic simulator, and optimal searching heuristics. A predeployment evaluation at one candidate intersection has also been conducted with field data and a well-calibrated traffic simulator. Results of extensive experimental analyses with both peak and midday data convincingly confirm the effectiveness of both proposed algorithms, based on the surrogate variable of vehicle conflicts for potential read-end collisions as used both in research and practice.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research is funded by Applied Technology and Traffic Analysis Program of Maryland Department of Transportation State Highway Administration.
References
AASHTO. 2010. Highway safety manual. Washington, DC: AASHTO.
Abadi, M. G., D. S. Hurwitz, P. Marnell, and S. Quayle. 2017. “Evaluation of red clearance extension designs with hardware-in-the-loop simulation.” Transp. Lett. 11 (5): 264–274. https://doi.org/10.1080/19427867.2017.1336860.
Abbas, M. M., Q. Wang, B. Higgs, D. Z. Sarabi, S. G. Machiani, and M. N. Mladenovic. 2016. “High-resolution field evaluation of radar-based dilemma zone protection system.” Transp. Res. Rec. 2557 (1): 11–23. https://doi.org/10.3141/2557-02.
Bhatnagar, S., H. Prasad, and L. Prashanth. 2013. “Gradient schemes with simultaneous perturbation stochastic approximation.” In Stochastic recursive algorithms for optimization, 41–76. London: Springer.
Bonneson, J., D. Middleton, K. Zimmerman, H. Charara, and M. Abbas. 2002. Intelligent detection-control system for rural signalized intersections. College Station, TX: Texas A&M Transportation Institute.
Bonneson, J. A., and P. T. Mccoy. 1996. “Traffic detector designs for isolated intersections.” ITE J. 66 (8): 42–47.
Chang, M. S., C. J. Messer, and A. J. Santiago. 1985. “Timing traffic signal change intervals based on driver behavior.” Transp. Res. Rec. 1027 (1): 20–30.
Chau, M., and M. C. Fu. 2015. “An overview of stochastic approximation.” In Handbook of simulation optimization, 149–178. New York: Springer.
Chiou, Y. C., and C. H. Chang. 2010. “Driver responses to green and red vehicular signal countdown displays: Safety and efficiency aspects.” Accid. Anal. Prev. 42 (4): 1057–1065. https://doi.org/10.1016/j.aap.2009.12.013.
Elhenawy, M., A. Jahangiri, H. A. Rakha, and I. El-Shawarby. 2015. “Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions.” Accid. Anal. Prev. 83 (Oct): 90–100. https://doi.org/10.1016/j.aap.2015.06.016.
FHWA (Federal Highway Administration). 2008. Surrogate safety assessment model (SSAM) software user manual. Washington, DC: FHWA.
Gates, T. J., D. A. Noyce, L. Laracuente, and E. V. Nordheim. 2007. “Analysis of driver behavior in dilemma zones at signalized intersections.” Transp. Res. Rec. 2030 (1): 29–39. https://doi.org/10.3141/2030-05.
Gazis, D., R. Herman, and A. Maradudin. 1960. “The problem of the amber signal light in traffic flow.” Oper. Res. 8 (1): 112–132. https://doi.org/10.1287/opre.8.1.112.
Gettman, D., and L. Head. 2003a. Surrogate safety measures from traffic simulation models. Washington, DC: Federal Highway Administration.
Gettman, D., and L. Head. 2003b. “Surrogate safety measures from traffic simulation models.” Transp. Res. Rec. 1840 (1): 104–115. https://doi.org/10.3141/1840-12.
Gettman, D., L. Pu, T. Sayed, S. Shelby, and I. T. S. Siemens. 2008. Surrogate safety assessment model and validation. Washington, DC: FHWA.
Hastie, T., R. Tibshirani, and J. Friedman. 2009. The elements of statistical learning: Data mining, inference, and prediction. New York: Springer.
Hurwitz, D. S., M. A. Knodler Jr., and B. Nyquist. 2011. “Evaluation of driver behavior in type II dilemma zones at high-speed signalized intersections.” J. Transp. Eng. 137 (4): 277–286. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000219.
Hurwitz, D. S., H. Wang, M. A. Knodler Jr., D. Ni, and D. Moore. 2012. “Fuzzy sets to describe driver behavior in the dilemma zone of high-speed signalized intersections.” Transp. Res. Part F Psychol. Behav. 15 (2): 132–143. https://doi.org/10.1016/j.trf.2011.11.003.
Kronborg, P., and F. Davidsson. 1993. “MOVA and LHOVRA: Traffic signal control for isolated intersections.” Traffic Eng. Control 34 (4): 195–200.
Kronborg, P., F. Davidsson, and J. Edholm. 1997. SOS-self optimising signal control. Stockholm, Sweden: Transport Research Institute.
Law, A. M., and W. D. Kelton. 2000. Simulation modeling and analysis. 3rd ed. New York: McGraw-Hill.
Liu, Y., G. L. Chang, and J. Yu. 2012. “Empirical study of driver responses during the yellow signal phase at six Maryland intersections.” J. Transp. Eng. 138 (1): 31–42. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000278.
Maryland State Police. 2019. “Maryland statewide vehicle crashes.” Accessed December 12, 2019. https://opendata.maryland.gov/Public-Safety/Maryland-Statewide-Vehicle-Crashes/65du-s3qu.
NGSIM (Next Generation Simulation). 2017. Open source SSAM computation engine API. Florence, KY: NGSIM.
NHTSA (National Highway Traffic Safety Administration). 2009. Novice teen driver education and training administrative standards. Washington, DC: NHTSA.
NHTSA (National Highway Traffic Safety Administration). 2019. Traffic safety facts 2017—A compilation of motor vehicle crash data. Washington, DC: NHTSA.
Papaioannou, P. 2007. “Driver behaviour, dilemma zone and safety effects at urban signalised intersections in Greece.” Accid. Anal. Prev. 39 (1): 147–158. https://doi.org/10.1016/j.aap.2006.06.014.
Park, S. Y., C. L. Lan, G. L. Chang, D. Tolani, and P. Huang. 2016. “Design and predeployment assessment of an integrated intersection dilemma zone protection system.” J. Transp. Eng. 142 (12): 04016063. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000894.
Park, S. Y., C. L. Lan, R. S. Rao, and G. L. Chang. 2018. “Field evaluation of the dilemma zone protection system at suburban intersections.” Transp. Res. Rec. 2672 (21): 51–62. https://doi.org/10.1177/0361198118774235.
Parsonson, P. S., R. A. Day, J. A. Gawlas, and G. W. Black. 1979. “Use of EC-DC detector for signalization of high-speed intersections.” Transp. Res. Rec. 737 (1): 17–23.
Parsonson, P. S., R. W. Roseveare, and J. R. Thomas Jr. 1974. “Small-area detection at intersection approaches.” Traffic Eng. 44 (N5): 8–17.
Peterson, A., T. Bergh, and K. Steen. 1986. “LHOVRA—A new traffic signal control strategy for isolated junctions.” Traffic Eng. Control 27 (7–8): 388–389.
Savolainen, P. T., A. Sharma, and T. J. Gates. 2016. “Driver decision-making in the dilemma zone—Examining the influences of clearance intervals, enforcement cameras and the provision of advance warning through a panel data random parameters probit model.” Accid. Anal. Prev. 96 (Nov): 351–360. https://doi.org/10.1016/j.aap.2015.08.020.
Sharma, A., D. Bullock, and S. Peeta. 2011. “Estimating dilemma zone hazard function at high speed isolated intersection.” Transp. Res. Part C Emerging Technol. 19 (3): 400–412. https://doi.org/10.1016/j.trc.2010.05.002.
Sharma, A., D. M. Bullock, and S. Peeta. 2007. “Recasting dilemma zone design as a marginal cost–benefit problem.” Transp. Res. Rec. 2035 (1): 88–96. https://doi.org/10.3141/2035-10.
Sheffi, Y., and H. Mahmassani. 1981. “A model of driver behavior at high speed signalized intersections.” Transp. Sci. 15 (1): 50–61. https://doi.org/10.1287/trsc.15.1.50.
Simpson, C. L., M. W. Harrison, and S. A. Troy. 2017. “Implementation of a dynamic all-red extension at signalized intersections in North Carolina: Evaluation of driver adaptation and operational performance.” Transp. Res. Rec. 2624 (1): 19–27. https://doi.org/10.3141/2624-03.
Spall, J. C. 1992. “Multivariate stochastic approximation using a simultaneous perturbation gradient approximation.” IEEE Trans. Autom. Control 37 (3): 332–341. https://doi.org/10.1109/9.119632.
Tarko, A., W. Li, and L. Laracuente. 2006. “Probabilistic approach to controlling dilemma occurrence at signalized intersections.” Transp. Res. Rec. 1973 (1): 55–63. https://doi.org/10.1177/0361198106197300107.
Urbanik, T., and P. Koonce. 2007. “The dilemma with dilemma zones.” Accessed December 16, 2020. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.557.4791&rep=rep1&type=pdf.
Vincent, R. A., and J. R. Peirce. 1988. ‘MOVA’: Traffic responsive, self-optimising signal control for isolated intersections. Berkshire, UK: Traffic Management Div., Traffic Group, Transport and Road Research Laboratory.
Wang, X., and M. Abdel-Aty. 2007. “Right-angle crash occurrence at signalized intersections.” Transp. Res. Rec. 2019 (1): 156–168. https://doi.org/10.3141/2019-19.
Wavetronix. 2016. Smart sensor advance user guide. Provo, UT: Wavetronix.
Webster, F., and P. Ellson. 1965. Traffic signals for high speed roads. Berkshire, UK: Road Research Laboratory.
Wood, J., and E. T. Donnell. 2016. “Safety evaluation of continuous green T intersections: A propensity scores-genetic matching-potential outcomes approach.” Accid. Anal. Prev. 93 (Aug): 1–13. https://doi.org/10.1016/j.aap.2016.04.015.
Zegeer, C. V., and R. C. Deen. 1978. Green-extension systems at high-speed intersections. Frankfort, KY: Dept. of Transportation, Commonwealth of Kentucky.
Zhang, L., L. Wang, K. Zhou, and W. B. Zhang. 2012. “Dynamic all-red extension at a signalized intersection: A framework of probabilistic modeling and performance evaluation.” IEEE Trans. Intell. Transp. Syst. 13 (1): 166–179. https://doi.org/10.1109/TITS.2011.2166070.
Zimmerman, K. 2007. “Additional dilemma zone protection for trucks at high-speed signalized intersections.” Transp. Res. Rec. 2009 (1): 82–88. https://doi.org/10.3141/2009-11.
Zimmerman, K., and J. A. Bonneson. 2004. “Intersection safety at high-speed signalized intersections: Number of vehicles in dilemma zone as potential measure.” Transp. Res. Rec. 1897 (1): 126–133. https://doi.org/10.3141/1897-16.
Zimmerman, K., D. Tolani, R. Xu, T. Qian, and P. Huang. 2012. “Detection, control, and warning system for mitigating dilemma zone problem.” Transp. Res. Rec. 2298 (1): 30–37. https://doi.org/10.3141/2298-04.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 9 • September 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Sep 25, 2020
Accepted: Feb 19, 2021
Published online: Jul 7, 2021
Published in print: Sep 1, 2021
Discussion open until: Dec 7, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.