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Model-based predictive control for bicycling in urban intersections
Institution:1. Zachry Department of Civil Engineering, Texas A&M University, College Station, 77843, TX, United States;2. Graduate student at Zachry Department of Civil Engineering, Texas A&M University, College Station, 77843, TX, United States;3. WuXi Transportation Research Institute, Jiangsu Province, China
Abstract:In this paper, a model predictive control approach for improving the efficiency of bicycling as part of intermodal transportation systems is proposed. Considering a dedicated bicycle lanes infrastructure, the focus in this paper is to optimize the dynamic interaction between bicycles and vehicles at the multimodal urban traffic intersections. In the proposed approach, a dynamic model for the flows, queues, and number of both vehicles and bicycles is explicitly incorporated in the controller. For obtaining a good trade-off between the total time spent by the cyclists and by the drivers, a Pareto analysis is proposed to adjust the objective function of the MPC controller. Simulation results for a two-intersections urban traffic network are presented and the controller is analyzed considering different methods of including in the MPC controller the inflow demands of both vehicles and bicycles.
Keywords:Bicycle traffic model  Multi-modal traffic control  Model predictive control
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