Green wave traffic control system optimization based on adaptive genetic-artificial fish swarm algorithm

Ma, Changxi; He, Ruichun

doi:10.1007/s00521-015-1931-y

Cited by 83 publications

(39 citation statements)

References 18 publications

(19 reference statements)

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“…(2) Not all time and space (referred to as space-time, the same as followings) are suitable for transporting hazardous materials. e existing research results on the dispatching of fleets have not covered the topic of "space-time screening of alternative transport of hazardous materials" [111][112][113][114][115][116][117][118]. However, this topic must be determined before optimizing the dispatch plan of hazardous materials transport fleet.…”

Section: Problems In Current Researchmentioning

confidence: 99%

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Zhou

et al. 2020

Journal of Advanced Transportation

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To comprehensively understand the research progress of the fleet scheduling for hazardous materials, the study has summarized the corresponding research results from three aspects (a) hazardous materials transportation risk, (b) route optimization, and (c) fleet scheduling, and then pointed out potential problems from six aspects: (a) the coupling risk of the transport fleet; (b) the screening of time and space for the transport of hazardous materials; (c) the scheduling optimization for transport fleets; (d) taking insufficient account of transport risks fairness; (e) insufficient robustness of scheduling schemes; and (f) lacking of research results on fleet scheduling of transport in the context of antiterrorism. After that, by considering the existing shortcomings of the current research, five research directions are presented that should be further explored in the future. Subsequently, both rough set and association rule theory is applied to explore the cause chain of transportation accidents for hazardous materials, and analyze the mechanism of transport accident for hazardous materials. Next, the Bayesian network is presented to predict the accident rate of hazardous materials transportation under different temporal and spatial conditions, and the dynamic rolling scheduling method of hazardous materials transport fleet is constructed under normal and antiterrorism background.

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Section: Problems In Current Researchmentioning

confidence: 99%

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Zhou

et al. 2020

Journal of Advanced Transportation

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“…In this section, we propose FCMC-PSO algorithm to solve the multiobjective route optimization problem of hazmat transportation in uncertain environment. The demand points is clustered by the fuzzy C means algorithm, and the transportation route for each demand points is determined based on the adaptive archives grid multiobjective particle swarm optimization [28][29][30].…”

Section: Algorithmmentioning

confidence: 99%

A Multiobjective Route Robust Optimization Model and Algorithm for Hazmat Transportation

Hao

et al. 2018

Discrete Dynamics in Nature and Society

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Aiming at route optimization problem of hazardous materials transportation in uncertain environment, this paper presents a multiobjective robust optimization model by taking robust control parameters into consideration. The objective of the model is to minimize not only transportation risk but also transportation time, and a robust counterpart of the model is introduced through applying the Bertsimas-Sim robust optimization theory. Moreover, a fuzzy C-means clustering-particle swarm optimization (FCMC-PSO) algorithm is designed, and the FCMC algorithm is used to cluster the demand points. In addition the PSO algorithm with the adaptive archives grid is used to calculate the robust optimization route of hazmat transportation. Finally, the computational results show the multiobjective route robust optimization model with 3 centers and 20 demand points’ sample studied and FCMC-PSO algorithm for hazmat transportation can obtain different robustness Pareto solution sets. As a result, this study will provide basic theory support for hazmat transportation safeguarding.

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“…Recently, with the development of V2I technology [3][4][5] and wide-area radar technology [6,7], the low-latency, highprecision, and traceable techniques provide new ideas for the recognition of intersection traffic conditions, especially in judging the truth or falseness of intersection overflow. Although these new technologies have been widely used in traffic control [8][9][10], traffic guidance [11,12], and autonomous driving [13][14][15], no one has attempted to use them in the field of intersection overflow.…”

Section: Introductionmentioning

confidence: 99%

Research on Intersection Frequent Overflow Control Strategy Based on Wide-Area Radar Data

Zhang

Zhao

Wang

2020

Journal of Advanced Transportation

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Overflow identification and control at urban road intersection is a derivative problem of oversaturation control. The existing cross-section detector uses the road cross-section occupation of vehicles to identify the overflow state; then, the downstream road condition is often ignored. At present, more and more advanced traffic detection technologies, such as vehicle-to-infrastructure and wide-area radar, can provide reliable data for accurate overflow identification. In this paper, a new method of overflow identification and control at intersections is proposed by using advanced wide-area radar detection data. As a detector for specific segment of road, the wide-area radar can detect the traffic flow data in a certain range of road and provide more data types. Therefore, the average speed and space occupancy of the effective detection road segment are selected as subindicators to establish the comprehensive identification index of overflow identification. Then, the overflow control strategy is developed considering the traffic demand of the overflow phase and the nonoverflow phase. It is proved that the method is more accurate and effective in overflow identification and control by using simulation experiment of field data.

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Green wave traffic control system optimization based on adaptive genetic-artificial fish swarm algorithm

Cited by 83 publications

References 18 publications

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review

A Multiobjective Route Robust Optimization Model and Algorithm for Hazmat Transportation

Research on Intersection Frequent Overflow Control Strategy Based on Wide-Area Radar Data

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