Commercial vehicles on highway networks are only permitted to use routes that are designed to accommodate their sizes and weights. When issuing an over-height permit, agencies consider vertical clearances on all route options on a highway network before directing a vehicle to the optimal route. Inefficient routing of commercial vehicles could cause excessive delays, which would result in undesirable economic impacts. Moreover, inaccurate assignment of vehicles to routes where the road infrastructure cannot handle the vehicle’s size could cause significant damage to the roadway, resulting in potential safety risks. Although routing programs and permit-issuing agencies try to avoid inaccurate assignments, this is not always possible since they rely on a database of information prone to human error and one which is not always up to date. To create a more reliable database of information, Departments of Transport need more efficient methods to collect information on highways. This paper aims to increase the efficiency of collecting data required to issue over-height permits by utilizing LiDAR data to automatically assess vertical clearance on highways. The method used involves detecting all overhead objects on a highway corridor and estimating the clearance at each object before mapping the data on a GIS map. The method was tested on three different highway corridors in Alberta, Canada ranging in length from 130 to 400 km. Testing revealed that the proposed method is effective in performing network-level assessment of vertical clearance, which has significant impacts on the efficiency of routing over-height vehicles on a network.


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    Title :

    Network Level Clearance Assessment using LiDAR to Improve the Reliability and Efficiency of Issuing Over-Height Permits on Highways


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-05-05




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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