Abstract
In order to solve the problem of traffic congestion and emission optimization of urban multi-class expressways, a robust dynamic nondominated sorting multi-objective genetic algorithm DFCM-RDNSGA-III based on density fuzzy c-means clustering method is proposed in this paper. Considering the three performance indicators of travel time, ramp queue and traffic emissions, the ramp metering and variable speed limit control schemes of an expressway are optimized to improve the main road and ramp traffic congestion, therefore achieving energy conservation and emission reduction. In the VISSIM simulation environment, a multi-on-ramp and multi-off-ramp road network is built to verify the performance of the algorithm. The results show that, compared with the existing algorithm NSGA-III, the DFCM-RDNSGA-III algorithm proposed in this paper can provide better ramp metering and variable speed limit control schemes in the process of road network peak formation and dissipation. In addition, the traffic congestion of expressways can be improved and energy conservation as well as emission reduction can also be realized.
Highlights
The variable speed limit of cars is set as (60, 90), the variable speed limit of trucks is set as (50, 80) and the ramp metering rate is set in the range (0, 1)
The Davies–Bouldin Index (DBI) [29], known as the classification and suitabilindicator, was proposed by David Davies and Donald Bouldin to evaluate the effect of ity indicator, was proposed by David Davies and Donald Bouldin to evaluate the effect of the clustering algorithms
A static optimization framework is adopted in algorithm NSGA-III to statically optimize the variable speed limit and metering rate in the whole simulation, while a dynamic optimization framework is adopted to dynamically optimize these variables according to the environmental changes in the RDNSGA-III algorithm and the DFCM-RDNSGA-III algorithm
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Through adopting effective control strategies, congestion and traffic efficiency can be improved, and vehicle exhaust emissions and fuel consumption can be reduced. DFCM-RDNSGA-III is designed to optimize the variable speed limit strategy and ramp control scheme of urban expressway networks. The variable speed limit and ramp metering strategy of the expressway system with multi-on-ramps and multi-off-ramps are optimized, and the effect of the algorithm is verified through building road network under the VISSIM simulation environment. The ramp inflow rate and main road variable speed limit control scheme can be obtained with strong robustness and adaptability to the dynamic variation of traffic flow. It is verified that the proposed algorithm, DFCM-RDNSGA-III, can provide better traffic control strategies, and the freeway traffic congestion and environmental pollution can be improved effectively
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