Optimizing Traffic Signal Settings for Public Transport Priority

In order to promote public transport many municipalities use traffic signal control with a priority for buses or trams. In this paper, we address the problem of finding optimal passive transit signal priority settings. Building on a cyclically time-expanded network model for the combined traffic assignment traffic signal coordination problem, we introduce a suitable queuing model and several modifications to model public transport vehicles appropriately. We evaluate the applicability of this approach by computing and analyzing optimal solutions for several instances of a real-world scenario

Adaptive performance optimization for large-scale traffic control systems

In this paper, we study the problem of optimizing (fine-tuning) the design parameters of large-scale traffic control systems that are composed of distinct and mutually interacting modules. This problem usually requires a considerable amount of human effort and time to devote to the successful deployment and operation of traffic control systems due to the lack of an automated well-established systematic approach. We investigate the adaptive fine-tuning algorithm for determining the set of design parameters of two distinct mutually interacting modules of the traffic-responsive urban control (TUC) strategy, i.e., split and cycle, for the large-scale urban road network of the city of Chania, Greece. Simulation results are presented, demonstrating that the network performance in terms of the daily mean speed, which is attained by the proposed adaptive optimization methodology, is significantly better than the original TUC system in the case in which the aforementioned design parameters are manually fine-tuned to virtual perfection by the system operators

Green Wave Traffic Optimization - A Survey

The objective of this survey is to cover the research in the area of adaptive traffic control with emphasis on the applied optimization methods. The problem of optimizing traffic signals can be viewed in various ways, depending on political, economic and ecological goals. The survey highlights some important conflicts, which support the notion that traffic signal optimization is a multi-objective problem, and relates this to the most common measures of effectiveness. A distinction can be made between classical systems, which operate with a common cycle time, and the more flexible, phase-based, approach, which is shown to be more suitable for adaptive traffic control. To support this claim three adaptive systems, which use alternatives to the classical optimization procedures, are described in detail.

Adaptive traffic signal control for real-world scenarios in agent-based transport simulations

This study provides an open-source implementation of a decentralized, adaptive signal control algorithm in the agent-based transport simulation MATSim, which is applicable for large-scale real-world scenarios. The implementation is based on the algorithm proposed by Lämmer and Helbing (2008), which had promising results, but was not applicable to real-world scenarios in its published form. The algorithm is extended in this paper to cope with realistic situations like different lanes per signal, small periods of overload, phase combination of non-conflicting traffic, and minimum green times. Impacts and limitations of the adaptive signal control are analyzed for a real-world scenario and compared to a fixed-time and traffic-actuated signal control. It can be shown that delays significantly reduce and queue lengths are lower and more stable than with fixed-time signals. Another finding is that the adaptive signal control behaves like a fixed-time control in overload situations and, therefore, ensures system-wide stability

Traffic Signal Controller Optimization Through VISSIM to Minimize Traffic Congestion, CO and NOx Emissions, and Fuel Consumption

In developing countries with heterogeneous traffic, such as Sri Lanka, it is possible to observe severe traffic congestion at intersections and traffic corridors. The main objective of this study was to demonstrate the optimization of traffic signal controllers using VISSIM microsimulation software. It aimed to minimize traffic congestion, emissions, and fuel consumption. This study focused on developing a traffic signal controller optimization program for a congested traffic corridor which consisted of a three-legged signalized intersection, a four-legged unsignalized intersection, and a three-legged unsignalized intersection. The entire corridor was modeled here, and the already signalized three-legged intersection was optimized. Traffic signal controller optimization was done separately through the built-in optimization features in VISSIM and Webster’s Method. The results showed that emissions and fuel consumption were reduced by 14.89 % in VISSIM optimization and 14.11% in optimization using Webster’s Method. Through the comparison between the VISSIM optimized signal timing and manually calculated signal timing, it was found that the signal timing optimization provides much more improved results than the manual signal timing calculations. Using the proposed methodology, the traffic signal controllers can be optimized within a short duration in very few steps without any iterations compared to the existing traffic signal controller optimization techniques. Therefore, the proposed methodology is a good alternative method to optimize the traffic signal controllers