Abstract

This paper presents a driver lane change model that adapts to individuals with different driving behavior. For lane change assistance systems, its acceptance by customers greatly relies on the assistant algorithm which can accurately reflect drivers’ individual characteristics. By analyzing the real world vehicle data and drivers’ characteristic parameters, such as time to lane change (TTLC), the steering angle and lateral offset were obtained, and consequently a lane change model was proposed. The inputs of the model are the vehicles’ current state (e.g. velocity) and drivers’ characteristic parameters (e.g. TTLC, lateral offset), and the output is the steering angle. Drivers’ individual differences can be demonstrated by the variation of model parameters. Comparing the simulation results to the real world vehicle data indicates that the developed model is able to imitate driver operations during lane changes, and it can be integrated into the control algorithm of the lane change assistance system embodying drivers’ characteristics.

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 call

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.