Truck parking shortage is currently one of the trucking industry's main issues. The lack of adequate rest locations for long-haul truck drivers can lower driver productivity, and increase accident risk, operational costs and carbon emissions. In this paper, we model the behavior of a region's driver population and study how parking demand can be estimated and influenced. We introduce a variant of the TDSP (Truck Driver Scheduling Problem) mixed-integer programming model which tracks parking usage by dividing time into time-slots and charging drivers per time slot. We then propose a non-cooperative game formulation using the TDSP variant to model individual driver behavior, with agent interaction happening through penalty functions dependent on parking occupancy. Finally, we use computational experiments to illustrate how the TDSP variant can be used to estimate parking demand across a route, as well as to simulate drivers' expected reaction to parking cost changes.
Parking Costs and Long-Haul Truck Parking Demand This work has been supported by the METRANS Transp. Center under the following grants: National Center for Sustainable Transp, (USDOT/Caltrans)
2024-09-24
706368 byte
Conference paper
Electronic Resource
English