Welcome to Journal of Automotive Safety and Energy,
汽车安全与节能学报

Journal Of Automotive Safety And Energy ›› 2018, Vol. 9 ›› Issue (4): 449-455.DOI: 10.3969/j.issn.1674-8484.2018.04.012

• Automotive Energy Efficiency & Environment Protection • Previous Articles     Next Articles

Path planning optimization-algorithm for a self-driving vehicle based on UTMD principle

LI Xueyun1,2   

  1. (1. School of Vehicle Engineering, Hubei University of Automotive Technology, Shiyan 442002, China; 2. Key Laboratory of Automotive Power Train and Electronics, Hubei University of Automotive Technology, Shiyan 442002, China)
  • Received:2018-07-29 Online:2018-12-31 Published:2019-01-02

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Abstract:

A path-planning optimization-algorithm for self-driving vehicles was designed by using some bionic intelligent algorithms to take account of the real-time and the reliability in computation. The path planning algorithm based on the basic principles of ultrasound-targeted microbubble destruction (UTMD). Divided the
iterative operation into target circle, microbubble iteration and micro-RNAs (miRNAs) iteration with the target delineation to reduce effectively the path search range. Verified the algorithm by using the Rastrigin function. Analyzed the setting of iteration numbers when they were set artificially. And used a self-test program to jump by itself. The algorithm was applied to 2-D path planning and simulated in Matlab. The results show that the path length planned by the UTMD algorithm is reduced by 4.52% compared with the length by Dijkstra algorithm. Therefore, the path-planning algorithm is effective for self-driving vehicles.

Key words: self-driving vehicle, path-planning, ultrasound-targeted microbubble destruction (UTMD), algorithm design, target delineation, micro-RNAs (miRNAs)