Emergency vehicle route oriented signal coordinated control model with two-level programming
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To minimize travel time of emergency vehicles on the way and improve efficiency of emergency response, an emergency vehicle route oriented signal coordinated control model with two-level programming was proposed based on the different priority types and priority levels of emergency vehicles. The upper level is the dynamic offset model of emergency vehicles, and the lower level is the green wave model of emergency vehicles. At dynamic offset level, latter phase was calculated based on the queue length ahead of the emergency vehicles and their arrival time, in which the former phase was the reference object. At route green wave level, maximum bandwidth of the route of emergency vehicles was calculated, based on the turning movement characteristics and its corresponding capacity reduction. Furthermore, the two-level programming model solution is obtained with genetic algorithm. Finally, simulation results of three control strategies, which are no-signal priority control strategy, isolated control priority strategy and coordinated priority control strategy in this paper, were obtained in micro-traffic simulation software VISSIM, with the case including three intersections in Suzhou roads as the emergency vehicles route. From the simulation results we can conclude that compared to no-signal priority control strategy, coordinated priority strategy can reduce delay, travel time, queue length and stops of emergency vehicles by 27,18, 36 and 38%, respectively, and the average delay of total vehicles at intersection can be reduced by 20%; compared to isolated control priority strategy, these numbers are 14, 6, 12, 21 and 22%, respectively, which means great improvement, and influence on social background traffic was also considered in it.
KeywordsEmergency traffic Coordinated control Route Green wave Two-level programming Dynamic offset of phase Genetic algorithm
This study was funded by MOE (Ministry of Education in China) Project of Humanities and Social Sciences (17YJCZH225) “Emergency oriented multi-objective traffic management and control model at urban area in the environment of big data”. This study was funded by the humanistic and social science research funding of University of Shanghai for Science and Technology (SK17YB05).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
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