Longitudinal minimum safety distance (LMSD) is a key indicator to determinate the probability of longitudinal vehicular collision. A novel LMSD model based on fuzzy reasoning was designed with consideration of driver's intention and driving circumstance. The model simulation was realized in MATLAB/Simulink and the experimental tests were performed under various driver's intentions, weather conditions and pavement conditions. Based on the comparisons of safety distances achieved from the model simulations, the vehicular collision tendency can be estimated and some dedicated precautionary measures can thus be performed in advance. The experiential results show that this model can effectively reveals the influence of the driver's intentions and driving circumstance on the longitudinal minimum safety distance, and can improve the reliability, timeliness and accuracy of collision warning.
A longitudinal minimum safety distance model based on driving intention and fuzzy reasoning
01.08.2017
329783 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Longitudinal driving intention recognition method based on driving style influence
Europäisches Patentamt | 2024
|Vehicle longitudinal driving safety distance estimation method based on vehicle trust
Europäisches Patentamt | 2021
|Transverse and longitudinal coupled driving intention recognition method
Europäisches Patentamt | 2024
|