Bandwidth Optimization for Coordinated Signal Control Systems for Improved Traffic Flow Efficiency

Abstract: Urban traffic networks are becoming increasingly complex, which calls for more effective strategies for managing traffic flow and congestion. Conventional fixed-time signal systems often fall short, especially during peak traffic hours, leading to a growing interest in adaptive solutions. Bandwidth-based models, designed to optimize signal coordination for uninterrupted vehicle movement, present a viable alternative. Among the various strategies, progression-based methods like bandwidth maximization stand out for their simplicity and ease of implementation, requiring fewer parameters and constraints. This study introduces a methodology for determining the optimal bandwidth in a fully vehicle-actuated, coordinated traffic environment by establishing key variables, identifying critical parameters, and utilizing statistical models alongside optimization techniques and simultaneously also builds on this approach by optimizing traffic signal coordination along a corridor with multiple number of intersections having a phase sequence of four, using real-time data and adaptive green time allocation to maximize bandwidth for heterogeneous vehicle platoons.
The research aims to enhance the "green wave" effect to facilitate smooth traffic flow through coordinated signals. A Vehicle Actuated Architecture (VAA) was put into place, allowing the system to adjust the duration of green signals based on current traffic conditions. A simulator interface continuously gathered real-time traffic data, offering accurate insights on when to start and stop green signals at each intersection. This real-time information was then analyzed to understand how different platoon compositions affected signal coordination, utilizing a bandwidth-based model. The system considered factors like average platoon speeds and intersection cycle lengths, enabling the evaluation of how various signal offsets influenced the effective bandwidth or 'green wave.' Adjustments to signal offsets were tested to enhance traffic flow, leading to better coordination along the corridor.
The VISSIM simulation software was employed to replicate real-time traffic conditions, accommodating fluctuating vehicle demands during peak and non-peak periods. The VAA, developed using VisVAP, an extension of VISSIM, was deployed across five intersections. Standard loop detectors, installed before stop lines, enabled real-time modification of green signal durations in response to changing traffic flows. Various optimization techniques, including Mixed-Integer Linear Programming (MILP), Sequential Quadratic Programming (SQP), and traditional methods, were applied to determine the optimal signal offsets. Among these, traditional methods proved to be most effective, allowing for precise adjustments to signal timings that improved the flow of heterogeneous vehicle platoons, thereby enhancing overall traffic efficiency.
The results demonstrate that the maximum bandwidth was allocated to a heavy commercial vehicle (HCV)-dominated platoons, followed by partial HCV-Bus-dominated platoons. After adjusting the bandwidth and modifying the offsets, the coordinated signal control showed significant improvements in urban traffic flow. Future research could expand this work to network-level vehicle-actuated signal control systems by integrating advanced measures like Degree Centrality. This would streamline the coordination of signals across multiple intersections, offering more efficient tools for managing traffic congestion in larger urban areas.