This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Effects of a Probability-Based Green Light Optimized Speed Advisory on Dilemma Zone Exposure
Technical Paper
2020-01-0116
ISSN: 0148-7191,
e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data. By utilizing this advisory method, real-time communications from the vehicle to infrastructure (V2I) become unnecessary, eliminating data-loss related issues. The effects of three different advice approaches (conservative, balanced, and aggressive) on dilemma zone exposure are analyzed. Proof of concept is carried out by simulating drives through a test-route composed of an arterial that had historical high-resolution traffic signal event logs for a series of actuated-coordinated traffic signals during different TOD and DOW. A comparison was performed between unadvised and GLOSA advised trips obtained from approximately 486,000 simulated trajectories. Results were obtained by analyzing the vehicle’s probability of stopping from utilizing Traffic Engineering dilemma zone theory. Reductions of 93% in the amount of hard brakings and 96% in the number of crossings through red light were observed with the proposed system. This data suggests the feasibility of a probability-based advisory, as well as the viability of utilizing the proposed GLOSA system to minimize dilemma zone exposure.
Authors
Citation
Saldivar-Carranza, E., Li, H., Kim, W., Mathew, J. et al., "Effects of a Probability-Based Green Light Optimized Speed Advisory on Dilemma Zone Exposure," SAE Technical Paper 2020-01-0116, 2020.Data Sets - Support Documents
| Title | Description | Download |
|---|---|---|
| Table 1 | ||
| [Unnamed Dataset 2] | ||
| [Unnamed Dataset 3] | ||
| [Unnamed Dataset 4] |
Also In
References
- Zimmerman, K., Tolani, D., Xu, R., Qian, T. et al. , “Detection, Control, and Warning System for Mitigating Dilemma Zone Problem,” Transportation Research Record: Journal of the Transportation Research Board 2298:30-37, 2012, doi:10.3141/2298-04.
- Li, H., Wolf, J., Mathew, J., Navali, N. et al. , “Leveraging Connected Vehicles to Provide Enhanced Roadway Condition Information,” in 98th Annual Meeting of the Transportation Research Board, Washington, DC, January 13-17, 2019, 19-02137.
- Massera, C., Terra, M., and Wolf, D. , “Safe Optimization of Highway Traffic with Robust Model Predictive Control-Based Cooperative Adaptive Cruise Control,” IEEE Transactions on Intelligent Transportation Systems 18(11):3193-3203, 2017, doi:10.1109/TITS.2017.2679098.
- Nguyen, V., Kim, O., Dang, T., Moon, S. et al. , “An Efficient and Reliable Green Light Optimal Speed Advisory System for Autonomous Cars,” in 2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS) 2016, Kanazawa, Japan, October 5-7, 2016, 10.1109/APNOMS.2016.7737260.
- Shinde, S. , “Adaptive Traffic Light Control System,” in 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM), Aurangabad, India, October 5-6, 2017, 300-306 10.1109/ICISIM.2017.8122189.
- Li, J., Dridi, M., and El-Moudni, A. , “Multi-Vehicles Green Light Optimal Speed Advisory Based on the Augmented Lagrangian Genetic Algorithm,” in 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), Qigdao, China, October 8-11, 2014, 2434-2439, 10.1109/ITSC.2014.6958080.
- Lebre, M.-A., Le Mouël, F., Ménard, E., Garnault, A. et al. , “Real Scenario and Simulations on GLOSA Traffic Light System for Reduced CO2 Emissions, Waiting Time and Travel Time,” in 22nd ITS World Congress, Bordeaux, France, October 5-9, 2015, paper number: ITS-2736.
- Sharara, M., Ibrahim, M., and Chalhoub, G. , “Impact of Network Performance on GLOSA,” in 2019 16th IEEE Annual Consumer Communications and Networking Conference (CCNC), Las Vegas, USA, January 11-14, 2019, 10.1109/CCNC.2019.8651787.
- Bodenheimer, R., Brauer, A., Eckhoff, D., and German, R. , “Enabling GLOSA for Adaptive Traffic Lights,” in 2014 IEEE Vehicular Networking Conference (VNC), Paderborn, Germany, December 3-5, 2014, 167-174, 10.1109/VNC.2014.7013336.
- Stahlmann, R., Möller, M., Brauer, A., German, R. et al. , “Exploring GLOSA Systems in the Field: Technical Evaluation and Results,” Computer Communications. 120:112-124, 2018, doi:10.1016/j.comcom.2017.12.006.
- Savolainen, P., Sharma, A., and Gates, T. , “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,” Accident Analysis and Prevention 96:351-360, 2016, doi:10.1016/j.aap.2015.08.020.
- Sharma, A., Bullock, D., and Peeta, S. , “Recasting Dilemma Zone Design as a Marginal Cost-Benefit Problem,” Transportation Research Record: Journal of the Transportation Research Board 2035:88-96, 2007, doi:10.3141/2035-10.
- Federal Highway Administration , “Signalized Intersections,” https://safety.fhwa.dot.gov/intersection/conventional/signalized/#overview, accessed October 2019.
- Day, C., Bullock, D., Li, H., Remias, S. et al. , “Performance Measures for Traffic Signal Systems: An Outcome-Oriented Approach,” 2014, 10.5703/1288284315333.
- Mathew, J., Li, H., Morgan, W., Kim, W. et al. , “Probabilistic Distributions of Coordinated Traffic Signal Phase Indications for Connected Vehicle Applications,” in 98th Annual Meeting of the Transportation Research Board, Washington, DC, January 13-17, 2019, paper number: 19-04708.
- SAE International , “J2735D: Dedicated Short Range Communications (DSRC) Message Set Dictionary™ - SAE International,” Warrandale, PA, 2016.
- Mathew, J., Li, H., and Bullock, D. , “Populating SAE J2735 Message Confidence Values for Traffic Signal Transitions along a Signalized Corridor,” submitted to the 99th Annual Meeting of the Transportation Research Record, Washington, DC, 2020, paper number: 20-04533.
- Parsonson, P. , “Signalization of High Speed, Isolated Intersections,” Transportation Research Record 681:34-42, 1978.
- Zegeer, C. and Deen, R. , “Green-Extension Systems at High-Speed Intersections,” ITE Journal 48(11), 1978.
- Archer, J. and Young, W. , “Signal Treatments to Reduce Heavy Vehicle Crash-Risk at Metropolitan Highway Intersections,” Accident Analysis Prevention 41:404-411, 2009, doi:10.1016/j.aap.2008.12.015.
- Sharma, A., Bullock, D., and Peeta, S. , “Estimating Dilemma Zone Hazard Function at High Speed Isolated Intersection,” Transportation Research Part C 19:400-412, 2011, doi:10.1016/j.trc.2010.05.002.
- Lee, S., Brown, S., Perez, M., Doerzaph, Z. et al. , “Normal and Hard Braking Behavior at Stop Signs and Traffic Signals,” Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting 49(22):1897-1901, 2005, doi:10.1177/154193120504902203.