Risk indicators evaluation based on anticipated vehicle dynamics parameters


Improving road safety needs the assessment of risk indicators. Predicting these indicators is of major importance to in efforts to boost safety systems and to warn drivers of dangerous things. This article presents a prediction algorithm for risk indicators that mixes assumptions regarding a vehicle's trajectory, velocity, and acceleration with existing road info to calculate risk indicators and detect presumably risky conditions in imminent driving things. The algorithm is validated through experiments with a laboratory vehicle.

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