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Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making

Transportation research. Part B: methodological, 2020-11, Vol.141, p.223 [Peer Reviewed Journal]

ISSN: 0191-2615 ;EISSN: 1879-2367 ;DOI: 10.1016/j.trb.2020.09.011

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  • Title:
    Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making
  • Author: Wu, Jiaming ; Kulcsár, Balázs Adam ; Ahn, Soyoung ; Qu, Xiaobo
  • Subjects: A algorithm ; Connected vehicles ; Cooperative control ; Emergency vehicles ; Optimization ; traffic flow ; transportation
  • Is Part Of: Transportation research. Part B: methodological, 2020-11, Vol.141, p.223
  • Description: Emergency vehicles (EVs) play a crucial role in providing timely help for the general public in saving lives and avoiding property loss. However, very few efforts have been made for EV prioritization on normal road segments, such as the road section between intersections or highways between ramps. In this paper, we propose an EV lane pre-clearing strategy to prioritize EVs on such roads through cooperative driving with surrounding connected vehicles (CVs). The cooperative driving problem is formulated as a mixed-integer nonlinear programming (MINP) problem aiming at (i) guaranteeing the desired speed of EVs, and (ii) minimizing the disturbances on CVs. To tackle this NP-hard MINP problem, we formulate the model in a bi-level optimization manner to address these two objectives, respectively. In the lower-level problem, CVs in front of the emergency vehicle will be divided into several blocks. For each block, we developed an EV sorting algorithm to design optimal merging trajectories for CVs. With resultant sorting trajectories, a constrained optimization problem is solved in the upper-level to determine the initiation time/distance to conduct the sorting trajectories. Case studies show that with the proposed algorithm, emergency vehicles are able to drive at a desired speed while minimizing disturbances on normal traffic flows. We further reveal a linear relationship between the optimal solution and road density, which could help to improve EV routing decision makings when high-resolution data is not available.
  • Language: English
  • Identifier: ISSN: 0191-2615
    EISSN: 1879-2367
    DOI: 10.1016/j.trb.2020.09.011
  • Source: SWEPUB Freely available online
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