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Discrete Dynamics in Nature and Society
Volume 2013 (2013), Article ID 283207, 10 pages
http://dx.doi.org/10.1155/2013/283207
Research Article

Development of Degree-of-Priority Based Control Strategy for Emergency Vehicle Preemption Operation

Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China

Received 22 August 2013; Accepted 5 November 2013

Academic Editor: Huimin Niu

Copyright © 2013 Jiawen Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper proposes a degree-of-priority based control strategy for emergency vehicle preemption operation to decrease the impacts of emergency vehicles on normal traffic. The proposed model features its effectiveness to the following three aspects: (1) a multilayer fuzzy model was established to determine the degree-of-priority based on emergency vehicle preemption demand intensity and preemption influence intensity; (2) for emergency vehicles with proper classification, a travel time estimation model for emergency traffic was formulated, an optimal emergency route determines model based on the level of priority of emergency events, and the emergency vehicle travel time was developed to minimize evacuation time as well as minimize the adverse impacts of preemption on normal traffic; and (3) a conditional traffic signals priority control method at each intersection of the evacuation route was built, so that traffic queue at each intersection can be cleared before the arrival of emergency vehicles. A simulation model based on field data was developed, and the performance of the proposed strategy was compared with the conventional local detection based method under the microscopic simulation model. The results validated the efficiency of the proposed strategy in terms of minimizing the delay of emergency vehicles and reducing adverse impacts on normal traffic.