Car-following is the most general behavior in highway driving. It is crucial to recognize the cut-in intention of vehicles from an adjacent lane for safe and cooperative driving. In this paper, a method of behavior estimation is proposed to recognize and predict the lane change intentions based on the contextual traffic information. A model predictive controller is designed to optimize the acceleration sequences by incorporating the lane-change intentions of other vehicles. The public data set of next generation simulation is labeled and then published as a benchmarking platform for the research community. Experimental results demonstrate that the proposed method can accurately estimate vehicle behavior and therefore outperform the traditional car-following control.
Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving
IEEE Transactions on Intelligent Vehicles ; 3 , 3 ; 276-286
2018-09-01
2045726 byte
Article (Journal)
Electronic Resource
English
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