Vision-Based Lane Crossing Point Tracking for Motorcycles - Archive ouverte HAL
Communication Dans Un Congrès Année : 2019

Vision-Based Lane Crossing Point Tracking for Motorcycles

Résumé

In this paper, we investigate a vision-based approach for online lane change prediction and detection dedicated Powered Two-Wheeled Vehicles. The approach is composed of two steps. First, the road geometry (clothoid model) and the motorcycle position with respect to the road markers are deduced based an inverse perspective mapping algorithm. The relative position is represented by the vehicle lateral displacement and heading estimated by means of an Inertial Measurement Unit and a monocular camera. The second step consists of predicting the Lane Crossing Point which allows to predict the distance and time before the motorcycle crosses the lane. The algorithm is achieved without the use of any steering sensor. To assess the effectiveness of the proposed approach, the estimation and the prediction schemes are validated on the BikeSim framework. To this end, two scenarios are discussed : 1-straight road with non-zero relative heading, and 2-curved road and circular vehicle trajectory.
Fichier principal
Vignette du fichier
itsc2019_PMD_v6.pdf (892.36 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02173364 , version 1 (04-07-2019)

Identifiants

  • HAL Id : hal-02173364 , version 1

Citer

Pierre-Marie Damon, Majda Fouka, Hicham Hadj-Abdelkader, Hichem Arioui. Vision-Based Lane Crossing Point Tracking for Motorcycles. IEEE Intelligent Transportation Systems Conference (ITSC 2019), Oct 2019, Auckland, New Zealand. ⟨hal-02173364⟩
75 Consultations
190 Téléchargements

Partager

More