Publications:On Path Planning Methods for Automotive Collision Avoidance
From ISLAB/CAISR
| Title | On Path Planning Methods for Automotive Collision Avoidance |
|---|---|
| Author | David Madås and Mohsen Nosratinia and Mansour Keshavarz and Peter Sundström and Roland Philippsen and Andreas Eidehall and Karl-Magnus Dahlén |
| Year | 2013 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | 2013 IEEE Intelligent Vehicles Symposium: IV 2013: Gold Coast City, Australia, 23-26 June 2013 |
| Conference | IEEE Intelligent Vehicles Symposium, IEEE IV 2013, June 23-26, 2013, Gold Coast, Australia |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:642063 |
| Abstract | There is a strong trend for increasingly sophisticated Advanced Driver Assistance Systems (ADAS) such as Autonomous Emergency Braking (AEB) systems, Lane Keeping Aid (LKA) systems, or indeed autonomous driving. This trend generates a need for online maneuver generation, for which numerous approaches can be found in the large body of work related to path planning and obstacle avoidance. In order to ease the challenge of choosing a method, this paper reports quantitative and qualitative insights about three different path planning methods: a state lattice planner, model predictive control, and spline-based search tree. Each method is described, implemented and compared on two specific traffic situations. In addition, qualitative merits and drawbacks are discussed for each method. The paper will not provide a final answer about which method is best. This depends on several factors such as computational constraints and the formulation of maneuver optimality that is appropriate for a given assistance or safety function. Instead, the conclusions will provide guidance for choosing a method for a specific application. |
