Path Planning using Model Predictive Controller based on Potential Field for Autonomous Vehicles


Elmi Z., EFE M. Ö.

44th Annual Conference of the IEEE Industrial-Electronics-Society (IECON), Washington, Kiribati, 20 - 23 October 2018, pp.2613-2618 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/iecon.2018.8591282
  • City: Washington
  • Country: Kiribati
  • Page Numbers: pp.2613-2618
  • Hacettepe University Affiliated: Yes

Abstract

In recent decades, one of the challenging problems is path planning for autonomous vehicle in dynamic environments with along static or moving obstacles. The main aim of these researches is to reduce congestion, accidents and improve safety. We propose an optimal path planning using model predictive controller (MPC) which automatically decides about the mode of maneuvers such as lane keeping and lane changing. For ensuring safety, we have additionally used two different potential field functions for road boundary and obstacles where the road potential field keeps the vehicle for going out of the road boundary and the obstacle potential field keep the vehicle away from obstacles. We have tested the proposed path planning on the different scenarios. The obtained results represent that the proposed method is effective and makes reasonable decision for different maneuvers by observing road regulations while it ensures the safety of autonomous vehicle.