Lane-Change Intention Estimation for Car-Following Control in Autonomous Driving

Yihuan Zhang, Qin Lin, Jun Wang, Sicco Verwer, John M. Dolan

Research output: Contribution to journalArticleScientificpeer-review

22 Citations (Scopus)
153 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)276-286
Number of pages11
JournalIEEE Transactions on Intelligent Vehicles
Issue number3
Publication statusPublished - 2018

Bibliographical note

Accepted author manuscript


  • Cooperative car-following
  • driving behavior estimation
  • lane change prediction
  • model predictive control


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