Analysis of Left-Turn Mixed Traffic Flow Dynamics at Y-Shaped Signalized Intersections Using Cellular Automata
2025-01-7204
02/21/2025
- Features
- Event
- Content
- Through the method of on-site video observation, this study divides the intersection area into three parts according to the road traffic characteristics of the Y-shaped signalized intersections, and at the same time obtains the relevant parameters. These parameters include the left-turn speed and traffic density of motor vehicles within both the internal and exit areas, the frequency of lane-changing and queuing behaviors of non-motorized vehicles in the internal area, and the left-turn speed and traffic density of non-motorized vehicles in both the internal and exit areas. The data extraction and analysis of the parameters provide strong data support for further analysis of the subsequent mixed traffic flow. A cellular automaton model is developed using the intersection’s exit area as the scenario. The exit area is divided into three lanes based on the queuing patterns of mixed traffic. Corresponding traffic rules are established according to the traffic density of motorized and non-motorized vehicles and the queuing behaviors of non-motorized vehicles in the exit area. Cyclists are categorized into three behavioral types based on their queuing patterns. Matlab software is used to analyze lane-specific traffic conditions under varying traffic densities, focusing on overall traffic conflicts. The analysis incorporates three key indicators: lane-changing frequency, vehicle conflict frequency, and vehicle delay, to evaluate the traffic flow across the three exit lanes under different traffic density levels. This analysis assists road managers in devising effective strategies to enhance the overall safety of mixed traffic flow at the exit of Y-shaped signalized intersections.
- Pages
- 11
- Citation
- Yuan, L., and Liu, X., "Analysis of Left-Turn Mixed Traffic Flow Dynamics at Y-Shaped Signalized Intersections Using Cellular Automata," SAE Technical Paper 2025-01-7204, 2025, https://doi.org/10.4271/2025-01-7204.