ROBOMECH Journal· 2014Q3· Review
A survey on motion prediction and risk assessment for intelligent vehicles
- 1,090citations
- Q3SCImago
- 2014year
Short summary
This survey classifies existing methods for intelligent vehicle motion prediction and risk assessment based on the semantics used to define motion and risk.
AI-generated from the title and abstract; the full text is not read.
Key points
- Surveys methods for motion prediction and risk assessment in intelligent vehicles.
- Classifies methods based on the semantics used for motion and risk definition.
- Highlights the trade-off between model completeness and real-time constraints.
- Notes that risk assessment method choice is influenced by the motion model.
AI-generated from the title and abstract; the full text is not read.
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 method is influenced by the selected motion model.
The authors' abstract, as published at the source. ROBOMECH Journal, 2014 · DOI ↗
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Field: Automotive Engineering
Automotive EngineeringEngineering