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.

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.

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 Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Lun Zhang ◽  
Meng Zhang ◽  
Wenchen Yang ◽  
Decun Dong
Keyword(s):  
Genetic Algorithm ◽  
Road Network ◽  
Road Traffic ◽  
Golden Ratio ◽  
Hybrid Genetic Algorithm ◽  
Capacity Expansion ◽  
Network Capacity ◽  
Traffic Network ◽  
Effective Measure ◽  
Urban Road

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers’ route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity.

scholarly journals Investigating the Effect of Traffic Flow on Pollution, Noise for Urban Road Network

2022 ◽  
Vol 961 (1) ◽  
pp. 012067
Author(s):  
Ali I Mansour ◽  
Hamid A Aljamil
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Vehicle Emissions ◽  
Solid Particles ◽  
Sulfur Oxides ◽  
Urban Road ◽  
Unburned Hydrocarbons ◽  
Carbon Dioxide Co2 ◽  
Atmospheric Phenomena

Abstract Congestion has a significant impact on the environment. It’s the predominant source of pollution, as noise and air pollution. The sound produced by vehicles as well as horns creates the worst possible environment. High motorized traffic flow nowadays is the major contributor to rising externalities, vehicle emissions, and other pollutants that impact the environment and the atmosphere, which result in negative atmospheric phenomena, global warming, and climate change. Vehicle emissions cause numerous vulnerabilities, so a serious consequence may arise in the long term, both regional and global. This study investigated Noise and pollution for different roads in the different cities based on field data at peak periods of traffic flow, shows that the major pollutants that are emitted from engines are: nitrogen oxides (NOX), carbon monoxide (CO), unburned hydrocarbons (CxHy), sulfur oxides (SOX), solid particles, including aerosols, as well as carbon dioxide (CO2).

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