Optimal Matching between Vehicle Speed and Lighting at Intersection Based on Traffic Risk Analysis
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 2
Abstract
Smart streetlamps, which can automatically adjust luminance by sensing information about passing vehicles, are gradually becoming an integral part of smart cities. However, when choosing a matching scheme between intersection lighting and vehicle speed, the matching performance and traffic safety can be compromised if the traffic risks caused by various conflicting events are not fully considered. Because it is difficult for drivers to spot pedestrians, cyclists, and motorcyclists at night, their accident mortality is relatively high. We designed conflicting events among pedestrians, cyclists, motorcyclists, and vehicles, and addressed this problem in three stages. First, the reserved reaction time (RRT), corresponding to the moment when a driver applies brakes in response to an emergency, was used as a quantitative index of the nighttime risk at intersections. Second, we selected the most dangerous conflict event using RRT. Finally, under the most dangerous conflicting conditions, the optimal lighting and vehicle speed matching scheme was designed with minimum illumination as the optimization objective and considering an RRT greater than or equal to zero as the constraint. As the research object, we considered a two-way/two-lane and two-way/four-lane major–minor intersection. We then constructed an indoor simulation test platform based on the road and lighting parameters of the actual intersection, and validated the matching optimization method of intersection lighting and vehicle speed in the simulation environment. The results indicate that when the average road surface illuminance (ARSI) is less than 3.3 lx, a cyclist approaching an intersection from the right side is in the most hazardous situation. If the ARSI is greater than 3.3 lx, the most dangerous situation is a pedestrian approaching from the right side of an intersection.
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Data Availability Statement
Some or all data, models, and code generated or used during the study are available from the corresponding author by request. Available items include visual recognition distance data collected through the experiments, and program codes.
Acknowledgments
Authors Hongtao Li and Linhong Wang contributed equally to the work. This study was supported in part by the National Natural Science Foundation of China under Grant 71971097, in part by the Youth Program of National Natural Science Foundation of China under Grant 52002143, in part by the National Natural Science Foundation of China under Grant 52172385, in part by the National Natural Science Foundation of China under Grant 52272417, and in part by the Natural Science Foundation of Jilin Province under Grant 20210101064JC.
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Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 2 • June 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: May 12, 2022
Accepted: Dec 6, 2022
Published online: Jan 27, 2023
Published in print: Jun 1, 2023
Discussion open until: Jun 27, 2023
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