Abstract
The prediction of lane changes has been proven to be useful for collision avoidance support in road vehicles. This paper proposes an interactive multiple model (IMM)-based method for predicting lane changes in highways. The sensor unit consists of a set of low-cost Global Positioning System/inertial measurement unit (GPS/IMU) sensors and an odometry captor for collecting velocity measurements. Extended Kalman filters (EKFs) running in parallel and integrated by an IMM-based algorithm provide positioning and maneuver predictions to the user. The maneuver states Change Lane (CL) and Keep Lane (KL) are defined by two models that describe different dynamics. Different model sets have been studied to meet the needs of the IMM-based algorithm. Real trials in highway scenarios show the capability of the system to predict lane changes in straight and curved road stretches with very short latency times.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Intelligent Transportation Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
