Enhanced Genetic Algorithm for Signal-Timing Optimization of Oversaturated Intersections

2000 ◽  
Vol 1727 (1) ◽  
pp. 32-41 ◽  
Author(s):  
Byungkyu “Brian” Park ◽  
Carroll J. Messer ◽  
Thomas Urbanik
Keyword(s):  
Genetic Algorithm ◽  
Operating Conditions ◽  
Throughput Maximization ◽  
Signal Timing ◽  
Timing Optimization ◽  
Average Delay ◽  
Delay Minimization ◽  
Traffic Conditions ◽  
Cycle Lengths ◽  
Oversaturated Intersections

Enhancements were provided to a previously developed genetic algorithm (GA) for traffic signal optimization for oversaturated traffic conditions. A broader range of optimization strategies was provided to include modified delay minimization with a penalty function and throughput maximization. These were added to the initial delay minimization strategy and were further extended to cover all operating conditions. The enhanced program was evaluated at different intersection spacings. The optimization strategies were evaluated and compared with their counterpart from TRANSYT-7F, version 8.1. A microscopic stochastic simulation program, CORSIM, was used as the unbiased evaluator. Hypothesis testing indicated that the GA-based program with average delay minimization produced a superior signal-timing plan compared with those produced by other GA strategies and the TRANSYT-7F program in terms of queue time. It was also found from the experiments that TRANSYT-7F tended to select longer cycle lengths than the GA program to reduce random plus oversaturation delay.

scholarly journals Urban Traffic Signal Control Based on Multiobjective Joint Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yongrong Wu ◽  
Yijie Zhou ◽  
Yanming Feng ◽  
Yutian Xiao ◽  
Shaojie He ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing Algorithm ◽  
Urban Traffic ◽  
Joint Optimization ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Timing Optimization ◽  
Average Delay ◽  
Annealing Algorithm

This paper proposes two algorithms for signal timing optimization of single intersections, namely, microbial genetic algorithm and simulated annealing algorithm. The basis of the optimization of these two algorithms is the original timing scheme of the SCATS, and the optimized parameters are the average delay of vehicles and the capacity. Experiments verify that these two algorithms are, respectively, improved by 67.47% and 46.88%, based on the original timing scheme.

scholarly journals Signal Timing Optimization Model of Urban Road Intersection Based on Multi-factor

2019 ◽  
Vol 259 ◽  
pp. 02004
Author(s):  
Qiuping Wang ◽  
Kai Wang ◽  
Shuaiqi Zhou ◽  
Qiongjie Shi ◽  
Qi zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cycle Time ◽  
Road Network ◽  
Vehicle Emissions ◽  
Stopping Time ◽  
Capacity Utilization ◽  
Signal Timing ◽  
Timing Optimization ◽  
Urban Road ◽  
Road Capacity

As the congestion point of urban road network, it is critical to keep the intersection traffic clear. The model was built targeting on decreasing vehicle delays and vehicle emissions, taking traffic queens, stopping time, road capacity and capacity utilization as verification indicators with two constraint conditions which are cycle time length and green ratio by means of genetic algorithm. And the dynamic vehicle emissions rate was taken into account. According to the data of Ke Ji Road-Feng Huinan Road intersection and Tong Yi Road-Tong De Road intersection, which show that the method is practical, and traffic queens, stopping time, vehicle delays, vehicle emissions decrease 34.03%,28.79%,48.73% and 28.04% at most, road capacity and capacity utilization increase 15.67% and 7.74% at most.

Assessment of Arterial Signal Timings Based on Various Operational Policies and Optimization Tools

2021 ◽  
pp. 036119812110111
Author(s):  
Suhaib Al Shayeb ◽  
Nemanja Dobrota ◽  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Travel Time ◽  
Heavy Traffic ◽  
Future Research ◽  
Signal Timing ◽  
Highway Capacity ◽  
Average Delay ◽  
Highway Capacity Manual ◽  
Simulation And Optimization ◽  
Fort Lauderdale ◽  
Design Engineers

Traffic simulation and optimization tools are classified, according to their practical applicability, into two main categories: theoretical and practical. The performance of the optimized signal timing derived by any tool is influenced by how calculations are executed in the particular tool. Highway Capacity Software (HCS) and Vistro implement the procedures defined in the Highway Capacity Manual, thus they are essentially utilized by traffic operations and design engineers. Considering its capability of timing diagram drafting and travel time collection studies, Tru-Traffic is more commonly used by practitioners. All these programs have different built-in objective function(s) to develop optimized signal plans for intersections. In this study, the performance of the optimal signal timing plans developed by HCS, Tru-Traffic, and Vistro are evaluated and compared by using the microsimulation software Vissim. A real-world urban arterial with 20 intersections and heavy traffic in Fort Lauderdale, Florida served as the testbed. To eliminate any bias in the comparisons, all experiments were performed under identical geometric and traffic conditions, coded in each tool. The evaluation of the optimized plans was conducted based on average delay, number of stops, performance index, travel time, and percentage of arrivals on green. Results indicated that although timings developed in HCS reduced delay, they drastically increased number of stops. Tru-Traffic signal timings, when only offsets are optimized, performed better than timings developed by all of the other tools. Finally, Vistro increased arrivals on green, but it also increased delay. Optimized signal plans were transferred manually from optimization tools to Vissim. Therefore, future research should find methods for automatically transferring optimized plans to Vissim.

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