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An improved path planning algorithm based on fuel consumption

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Abstract

Most path planning algorithms choose path length as the evaluation criterion for algorithm performance. However, considering the driving and environmental costs, the car’s fuel consumption is also critical. This paper proposes an improved A* algorithm based on fuel consumption. Because there are driving stages and idling stages in the driving process, the latter mainly occurs when the car meets the red lights. Accordingly, we make the same improvement to the A* algorithm; the fuel consumption of each part corresponds to the composition of the evaluation function of the A* algorithm. Finally, we use the abstract map and set different red light proportions to compare the algorithm’s performance. The experimental results show that with the red light proportion increase, the improved A* algorithm can reduce the fuel consumption by up to 16.949% compared with the original A* algorithm.

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All data, materials generated or used during the study appear in the submitted article.

Code availability

The codes used or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This study was supported by the National Key Research and Development Program of China (2017YFB0102500), the National Natural Science Foundation of China (61872158,62172186), the Science and Technology Development Plan Project of Jilin Province (20190701019GH), the Korea Foundation for Advanced Studies’ International Scholar Exchange Fellowship for the academic year of 2017-2018, the Fundamental Research Funds for the Chongqing Research Institute, and Jilin University (2021DQ0009).

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Tianbo Liu & Jindong Zhang

  2. Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Jilin University, Changchun, 130012, China

    Jindong Zhang

  3. State Key Laboratory of Automobile Simulation and Control, Jilin University, Changchun, 130025, China

    Jindong Zhang

Authors
  1. Tianbo Liu
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All authors contributed to the study conception and design. The first draft of the manuscript was written by [Tianbo Liu] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Jindong Zhang.

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Appendix A List of variables and abbreviations

Appendix A List of variables and abbreviations

See Tables 10 and 11

Table 10 The meaning of variables and abbreviations in the ant colony algorithm
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Table 11 The meaning of variables and abbreviations in the A* algorithm
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Liu, T., Zhang, J. An improved path planning algorithm based on fuel consumption. J Supercomput 78, 12973–13003 (2022). https://doi.org/10.1007/s11227-022-04395-6

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