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Risk indicators evaluation based on anticipated vehicle dynamics parameters

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4 Author(s)
Raymond Ghandour ; Université de Technologie de Compiègne ; Alessandro Victorino ; Ali Charara ; Daniel Lechner

Improving road safety requires the assessment of risk indicators. Predicting these indicators is of major importance to in efforts to enhance safety systems and to warn drivers of dangerous situations. This article presents a prediction algorithm for risk indicators that combines assumptions about a vehicle's trajectory, velocity, and acceleration with existing road information to calculate risk indicators and detect possibly risky conditions in imminent driving situations. The algorithm is validated through experiments with a laboratory vehicle.

Published in:

IEEE Intelligent Systems  (Volume:27 ,  Issue: 2 )