Driver Speed Control Modeling for Predictive Braking Assistance System Based on Risk Potential in Intersections
Author(s) -
Pongsathorn Raksincharoensak,
Yuta Akamatsu,
Katsumi Moro,
Masao NAGAI
Publication year - 2014
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2014.p0628
Subject(s) - pedestrian , simulation , driving simulator , advanced driver assistance systems , collision avoidance , model predictive control , computer science , collision avoidance system , braking system , collision , automotive engineering , engineering , brake , control (management) , artificial intelligence , transport engineering , computer security
Predictive braking assistance system This paper describes the assessment of a predictive braking assistance system, which is done using a driving simulator that reconstructs near-miss incident scenarios relevant to pedestrians. An autonomous braking assistance algorithm for collision avoidance is designed based on pedestrian movement prediction and an artificial risk potential field. A virtual spring connecting the vehicle and the pedestrian is used to determine the repulsive potential field and the intensity of the deceleration. The feasibility of the proposed braking assistance algorithm is examined through experiments using the driving simulator and a comparison to actual driving data. Near-miss incident data relevant to pedestrians in intersections are analyzed to get the basic parameters of a crash scenario model relevant to pedestrians. Driving simulator experiments are used to verify the effectiveness of the proposed system.
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