Highlights This study examined nearly 4-year emergency vehicle (EV) travel time data. A utility-based model is proposed to address the performance of EV routing. A good distribution for EV standardized travel time is Inv. Gaussian distribution. A map provides EV operators an entire picture of network travel time reliability.

    Abstract Travel time is very critical for emergency response and emergency vehicle (EV) operations. Compared to ordinary vehicles (OVs), EVs are permitted to break conventional road rules to reach the destination within shorter time. However, very few previous studies address the travel time performance of EVs. This study obtained nearly 4-year EV travel time data in Northern Virginia (NOVA) region using 76,000 preemption records at signalized intersections. First, the special characteristics of EV travel time are explored in mean, median, standard deviation and also the distribution, which display largely different characteristics from that of OVs in previous studies. Second, a utility-based model is proposed to quantify the travel time performance of EVs. Third, this paper further investigates two important components of the utility model: benchmark travel time and standardized travel time. The mode of the distribution is chosen as benchmark travel time, and its nonlinear decreasing relationship with the link length is revealed. At the same time, the distribution of standardized travel time is fitted with different candidate distributions and Inv. Gaussian distribution is proved to be the most suitable one. Finally, to validate the proposed model, we implement the model in case studies to estimate link and route travel time performance. The results of route comparisons also show that the proposed model can support EV route choice and eventually improve EV service and operations.


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    Title :

    Performance measure for reliable travel time of emergency vehicles


    Contributors:
    Zhang, Zhenhua (author) / He, Qing (author) / Gou, Jizhan (author) / Li, Xiaoling (author)


    Publication date :

    2016-01-16


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English