Cycling has been considered as a healthy, environmentally friendly, and economical alternative mode of travel to motorized vehicles (especially private motorized vehicles). However, bicycles have often been neglected in the transportation planning and travel demand forecasting modeling processes. The current practice in modeling bicycle trips in a network is either nonexistent or too simplistic. Current practices are simply based on the all-or-nothing (AON) assignment method using single attributes such as distance, safety, or a composite measure of safety multiplied by distance. The purpose of this paper is to develop a two-stage traffic assignment model by considering key factors (or criteria) in cyclist route choice behavior. As an initial effort, the first stage considers two key criteria (distance-related attributes and safety-related attributes) to generate a set of nondominated (or efficient) paths. These two criteria are a composite function of subcriteria. Route distance consists of link distances and intersection turning penalties combined to give the distance-related attribute, while route safety makes use of the bicycle level of service (BLOS) measure developed by the Highway Capacity Manual (HCM) to determine the safety-related attribute. Efficient paths are generated based on the above two key criteria with a biobjective shortest path algorithm. The second stage determines the flow allocation to the set of efficient paths. Several traffic assignment methods are adopted to determine the flow allocations in a network. Numerical experiments are then conducted to demonstrate the two-stage approach for bicycle traffic assignment. Overall, the results of the Winnipeg network demonstrate the applicability of the two-stage bicycle traffic assignment procedure with the flexibility of using different criteria in the first stage to generate efficient paths and different traffic assignment methods in the second stage to allocate flows.


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    Title :

    Two-Stage Bicycle Traffic Assignment Model


    Contributors:


    Publication date :

    2017-12-13




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown



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