Traffic Reconstruction and Analysis of Natural Driving Behaviors at Unsignalized Intersections
Year: 2023
Type: preprint
Abstract: This paper explores the intricacies of traffic behavior at unsignalized intersections through the lens of a novel dataset, combining manual video data labeling and advanced traffic simulation in SUMO. This research involved recording traffic at various unsignalized intersections in Memphis, TN, during different times of the day. After manually labeling video data to capture specific variables, we reconstructed traffic scenarios in the SUMO simulation environment. The output data from these simulations offered a comprehensive analysis, including time-space diagrams for vehicle movement, travel time frequency distributions, and speed-position plots to identify bottleneck points. This approach enhances our understanding of traffic dynamics, providing crucial insights for effective traffic management and infrastructure improvements.
Source: arXiv (Cornell University)
Authors: Sarker, Supriya, Poudel, Bibek, Villarreal, Michael, Li, Weizi
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4390214844