Study of Energy Dissipation and Satisfaction Rates in Mixed Traffic Flow with Lights: A Two-Lane Cellular Automaton Approach

Abstract

Traffic lights in cities play a crucial role in regulating the complex dynamics of diverse vehicles, giving priority to certain users or vehicles on the road. However, the alternating stop-and-go patterns induced by these lights have an impact on desired speed of vehicles and energy dissipation. In this paper, we examine the impacts of traffic signals, focusing on a two-lane cellular automaton model. Our model accounts for traffic heterogeneity by differentiating vehicles based on speed (slow and fast) and size (large, slow vehicles and small, fast vehicles). In our study, we concentrated on a case in which the lane-changing rules were asymmetric., this regulation stipulates that slower-moving traffic should keep to the righthand lane (or the left-hand lane in countries where driving is on the left) to allow faster vehicles to pass. Although these vehicles occasionally change lanes, they revert to their preferred lane at the earliest opportunity. Hence, we examined two traffic light control strategies: the green wave and synchronized methods. Our findings indicate that both strategies exhibit comparable performance for vehicles in terms of traffic flow parameters. However, differences emerge when comparing the two lanes or vehicle types. Specifically, the slow lane demonstrates a higher traffic flow for slower vehicles and a reduced flow for faster vehicles. When examining satisfaction rates and energy dissipation, notable variations emerge, especially in extremely low densities. The green wave demonstrates marginally superior performance compared to the synchronized traffic light control. This investigation deepens our understanding of the impact of various control strategies on performance. The findings can serve as a foundation for exploring more intricate aspects of traffic management, enhancing the potential for creating efficient and adaptive urban transportation systems.