Version 1
: Received: 21 October 2023 / Approved: 23 October 2023 / Online: 23 October 2023 (10:28:27 CEST)
How to cite:
Ansariyar, A. Providing a Comprehensive Traffic Safety Analysis Collected by Two LiDAR Sensors at a Signalized Intersection. Preprints2023, 2023101401. https://doi.org/10.20944/preprints202310.1401.v1
Ansariyar, A. Providing a Comprehensive Traffic Safety Analysis Collected by Two LiDAR Sensors at a Signalized Intersection. Preprints 2023, 2023101401. https://doi.org/10.20944/preprints202310.1401.v1
Ansariyar, A. Providing a Comprehensive Traffic Safety Analysis Collected by Two LiDAR Sensors at a Signalized Intersection. Preprints2023, 2023101401. https://doi.org/10.20944/preprints202310.1401.v1
APA Style
Ansariyar, A. (2023). Providing a Comprehensive Traffic Safety Analysis Collected by Two LiDAR Sensors at a Signalized Intersection. Preprints. https://doi.org/10.20944/preprints202310.1401.v1
Chicago/Turabian Style
Ansariyar, A. 2023 "Providing a Comprehensive Traffic Safety Analysis Collected by Two LiDAR Sensors at a Signalized Intersection" Preprints. https://doi.org/10.20944/preprints202310.1401.v1
Abstract
This study investigates the application of Light Detection and Ranging (LiDAR) sensor technology for data collection at signalized intersections characterized by a high rate of traffic crashes. The research aims to provide valuable insights into the potential of LiDAR-based data analysis to enhance road safety and traffic management at signalized intersections. The research methodology involved the deployment of LiDAR sensors at Marlboro Pike & Brooks Dr. signalized intersection in Coral Hills, Maryland. Two LiDAR sensors installed in this intersection to collect high-resolution, three-dimensional data of the intersection area from June, 1st to July, 7th 2023. The data included information on vehicle trajectories, speeds, and behaviors, as well as pedestrian and cyclist movement patterns. Concurrently, historical traffic crashes recorded and traffic flow data were obtained for the same intersection.The analysis of LiDAR data involved several key aspects including LiDAR data allowed for a precise evaluation of traffic flow patterns, including congestion points, traffic volume fluctuations, and peak-hour behavior. This information provided insights into potential factors contributing to crashes. By analyzing LiDAR data, the study identified near-miss incidents, which are often precursors to actual crashes. This proactive approach could assist in identifying crash-prone areas within the intersection. The LiDAR data analysis also focused on pedestrian and cyclist movements, including jaywalking and bike lane usage. The aim was to identify areas where infrastructure improvements could enhance safety for vulnerable road users. LiDAR data was compared with historical crash data to identify specific locations within the intersection that exhibited a high frequency of crashes. This information can guide targeted safety interventions. Last but not least, the study explored opportunities to optimize traffic signal timings based on real-time traffic data from LiDAR. Adaptive signal control could help mitigate congestion and reduce the risk of crashes.The results of this study demonstrated the potential of LiDAR sensor technology in collecting detailed data for traffic analysis in signalized intersections. By combining LiDAR data with historical crash records and traffic flow data, traffic engineers and urban planners can develop evidence-based strategies to reduce the frequency and severity of crashes in high-risk areas. Ultimately, this research contributes to a comprehensive understanding of how LiDAR technology can be employed to enhance road safety and traffic management, providing valuable insights for traffic engineers, urban planners, and policymakers seeking to improve the safety and efficiency of signalized intersections with a history of high traffic crashes.
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
