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Communication Dans Un Congrès Année : 2020

Multisensor Tracking of Lane Boundaries based on Smart Sensor Fusion

Résumé

Lane detection plays a crucial role in any autonomous driving system. Currently commercialized vehicles offer lane keep assist and lane departure warning via integrated smart cameras, deployed for road markings detection. These sensors alone, however, do not generally ensure adequate performance for higher autonomy levels. In this paper, a multi-sensor tracking approach for generic lane boundaries is proposed. This solution is based on well-established filtering techniques and supports a flexible clothoid spline representation. It relies on fine-tuned measurement models, tailored on collected data from both off-the-shelf and prototype smart sensors. The implementation takes into account real-time constraints and ADAS ECUs scarcity of resources. The result is finally validated against lane-level ground truth and experimental data acquisitions.
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Dates et versions

hal-02556103 , version 1 (15-06-2020)

Identifiants

  • HAL Id : hal-02556103 , version 1

Citer

Federico Camarda, Franck Davoine, Veronique Cherfaoui, Bruno Durand. Multisensor Tracking of Lane Boundaries based on Smart Sensor Fusion. 31st IEEE Intelligent Vehicles Symposium (IV 2020), Oct 2020, Las Vegas, United States. pp.1649-1654. ⟨hal-02556103⟩
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