A control approach for automated highway driving is proposed in this study, which can learn from human driving data, and is applied to the longitudinal trajectory of an autonomous car. Naturalistic driving data are used as samples to train the model offline. Then, the model is used online to emulate what a human driver would do by computing acceleration. This reference acceleration is tracked by a predictive controller, which enforces a set of comfort and safety constraints before applying the final acceleration. The controller is designed to balance between maintaining vehicle safety and following the model's commands. Thus, the proposed controller can handle dynamic traffic situations while performing like a human driver. This approach is validated on two different scenarios using MATLAB simulations.
A personalized highway driving assistance system
2017 IEEE Intelligent Vehicles Symposium (IV) ; 1596-1601
2017-06-01
298193 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
A highway driving assistance system
Kraftfahrwesen | 1992
|PERSONALIZED SAFE DRIVING ASSISTANCE METHOD AND SYSTEM
Europäisches Patentamt | 2022
|Personalized safe driving assistance method and system
Europäisches Patentamt | 2024
|AUTONOMOUS EMERGENCY BRAKING SYSTEM INTERWORKING WITH HIGHWAY DRIVING ASSISTANCE SYSTEM
Europäisches Patentamt | 2019
AUTONOMOUS EMERGENCY BRAKING SYSTEM INTERWORKING WITH HIGHWAY DRIVING ASSISTANCE SYSTEM
Europäisches Patentamt | 2019
|