Real-time route diversion control in a model predictive control framework with multiple objectives: Traffic efficiency,emission reduction and fuel economy |
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| Institution: | 1. College of Transport and Communications, Shanghai Maritime University, 1550 Haigang Avenue, Pudong, Shanghai 201306, China;2. Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180, USA;1. Jiangsu Key Laboratory of Urban ITS, Southeast University, 2 Si Pai Lou, Nanjing 210096, China;2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, 2 Si Pai Lou, Nanjing 210096, China;1. School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China;2. School of Economics and Management, Beihang University, Beijing, 100191, China;1. Beijing Institute of Technology, School of Mechanical Engineering, Beijing 100081, China;2. Michigan State University, Department of Mechanical Engineering, East Lansing, MI 48823, USA |
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| Abstract: | In this paper, the route recommendation provided by the traffic management authority, rather than the uncontrollable bifurcation splitting rate, is directly considered as the control variable in the route guidance system; a real-time en-route diversion control strategy with multiple objectives is designed in a Model Predictive Control (MPC) framework with regard to system uncertainties and disturbances. The objectives include not only traffic efficiency, but also emission reduction and fuel economy, which respectively correspond to minimizing the total time spent (TTS), total amount of emissions and fuel consumption for all vehicles moving through a network. In the MPC framework, the routing control problem is transformed to be a constrained combinational optimization, which is solved by the parallel Tabu Search algorithm. Two representative traffic scenarios are tested, and the simulation results show: (1) The room for improvement in each objective by means of route diversion control is not consistent with each other and varies with the utilized traffic scenario. In the peak hour, the routing control can lead to significant improvements in TTS and fuel economy, while a relatively small improvement in emission reduction is achieved; in the off-peak hour, however, it is opposite, which indicates that routing is possibly dispensable from the aspect of improving traffic efficiency, but is required from the aspect of emission reduction. (2) The conflict among the multiple objectives varies with the utilized traffic scenario in route diversion control. Improving traffic efficiency often conflicts with emission reduction in both scenarios. For the objectives of traffic efficiency and fuel economy, they are not conflicting in peak hour, while in the off-peak hour, the two objectives are likely conflicting, and the improvement in one objective can lead to the degradation in the other objective. (3) Regardless of the scenarios of peak hour or off-peak hour, the proposed control strategy can result in a proper trade-off among the three chosen objectives. |
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| Keywords: | Real-time en-route diversion control Traffic efficiency Emission reduction Fuel economy Model predictive control |
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