Highlights Noncompliance behavior against vehicle restriction policy is analyzed. Empirical data and quantitative models are used to investigate the behavior. Trip characteristics show statistically significant effects on the behavior. Methods for preventing noncompliance and improving the policy are discussed.

    Abstract To alleviate traffic congestion, vehicle restriction policies have been widely used globally. However, noncompliance behavior undermines the effectiveness and sustainability of such policies. This study focuses on investigating the characteristics of noncompliance behavior under two vehicle restriction policies, namely, one-day-per-week (ODPW) and odd-and-even (OAE) policies. On the basis of license plate recognition data that record the traffic condition under ODPW and OAE policies in Langfang, China, descriptive statistics are used to illustrate the characteristics of noncompliance with the policies. Furthermore, a zero-inflated model is used to determine the manner in which influencing factors (i.e., local versus external indicator, unrestricted travel rate, daily travel distance within the urban restriction area, and distance between the source intersection and central business district) affect noncompliance frequency. Results show that under the two policies, holding a nonlocal license plate, traveling a long distance daily in the urban restriction area, and departing from a location far from the city center increase the probability of noncompliance behavior of individuals. However, unrestricted travel rate, which represents the frequency of vehicle trips on unrestricted days, exhibits different influences on noncompliance behavior under the two policies. This study provides an in-depth interpretation to noncompliance behavior under vehicle restriction policies and aids improve the long-term effectiveness of the policies.


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    Title :

    Noncompliance behavior against vehicle restriction policy: A case study of Langfang, China


    Contributors:


    Publication date :

    2020-01-07


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English