A survey on motion prediction and risk assessment for intelligent vehicles
Institut national de recherche en sciences et technologies du numérique · Centre Inria de l'Université Grenoble Alpes · +1 more institution
Abstract
Abstract With the objective to improve road safety, the automotive industry is moving toward more “intelligent” vehicles. One of the major challenges is to detect dangerous situations and react accordingly in order to avoid or mitigate accidents. This requires predicting the likely evolution of the current traffic situation, and assessing how dangerous that future situation might be. This paper is a survey of existing methods for motion prediction and risk assessment for intelligent vehicles. The proposed classification is based on the semantics used to define motion and risk. We point out the tradeoff between model completeness and real-time constraints, and the fact that the choice of a risk assessment…
Citation impact
- FWCI
- 37.41
- Percentile
- 100%
- References
- 90
Authors
3- SLStéphanie LefèvreCorresponding
Institut national de recherche en sciences et technologies du numérique, Centre Inria de l'Université Grenoble Alpes, University of California, Berkeley
- DVDizan Vasquez
Institut national de recherche en sciences et technologies du numérique, Centre Inria de l'Université Grenoble Alpes
- CLChristian Laugier
Institut national de recherche en sciences et technologies du numérique, Centre Inria de l'Université Grenoble Alpes
Topics & keywords
- Automotive industry
- Motion (physics)
- Computer science
- Mechatronics
- Risk analysis (engineering)
- Artificial neural network
- Computational intelligence
- Artificial intelligence
- Sustainable cities and communities