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access icon free Colouring vehicle threat and minimising threat avoidance trajectory cost for adaptive vehicle collision defence system in active safe driving

  • Author(s): Ben-Jye Chang 1 ; Bo-Han Yu 1 ; Ying-Hsin Liang 2
    • View affiliations
    • Affiliations: 1: Computer Science and Information Engineering, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan ;
      2: Multimedia Animation and Application, Nan Kai University of Technology, 568 Chung-Cheng Road, Caotun, Nantou 54243, Taiwan
  • Source: Volume 11, Issue 6, August 2017, p. 309 – 318
    DOI:  10.1049/iet-its.2016.0181 , Print ISSN 1751-956X, Online ISSN 1751-9578
© The Institution of Engineering and Technology
Received 14/07/2016, Accepted 28/02/2017, Revised 23/01/2017, Published 03/03/2017

The Advanced Driver Assistance Systems (ADASs) have been proposed to avoid vehicular accidents by using the inter-vehicle cooperation mechanism, the real-time-based sharing of the road and traffic information, automatic controls of braking and acceleration and so on. Several critical challenges in ADAS are seldom discussed in related studies, including unstable driving in velocity or the road lane, driving assistance without driving path prediction, suddenly happening of human abnormal driving or mechanical vehicle accident and so on. Thus, this study proposes the Adaptive vehicle Collision Defence (ACD) system to minimise the driving threat under critical driving threats. The proposed ACD consists of three phases: the adaptive time-to-collision (TTC) determination phase, the threat probability analysis with colouring phase, and the threat avoidance phase. The main objectives are to minimise the driving threat probability and to achieve active safe driving for the advanced driver assistance systems. Numerical results indicate that the proposed ACD outperforms the compared approaches in TTC probability, driving threat probability, and region boundary.

Inspec keywords: driver information systems; real-time systems; road accidents; road safety; minimisation; probability; collision avoidance

Other keywords: traffic information; automatic acceleration controls; inter-vehicle cooperation; advanced driver assistance systems; critical driving threats; adaptive vehicle collision defence system; automatic braking controls; driving threat probability minimisation; ADAS; road lane; adaptive time-to-collision determination; threat avoidance trajectory cost minimisation; active safe driving; road information; ACD system; unstable driving; adaptive TTC determination; threat probability analysis; vehicular accident avoidance; real-time-based information sharing; colouring vehicle threat

Subjects: Optimisation techniques; Traffic engineering computing; Other topics in statistics

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