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Improved Optimal Reciprocal Collision Avoidance Algorithm in Racing Games

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Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 279))

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Abstract

Autonomous character behavior design is a key to the development of game artificial intelligence. Currently, collision avoidance technology, which is widely used in the field of robotics, cannot be directly applied to the autonomous character behavior design in racing games without specific adjustment. This paper makes some improvements to the classical Optimal Reciprocal Collision Avoidance (ORCA) algorithm to propose a novel collision avoidance algorithm (IORCA) suitable for racing games. Relevant concepts unique to racing games are put forward. The collision handling principles followed by racing AI on the straight lines and curves are further presented. By implementing the two systems equipped with ORCA and IORCA, the collision avoidance behavior of the racing AI in multiple scenarios are compared. It could be found that the collision avoidance behavior under IORCA is more suitable for racing games, and is able to give players a better gaming experience.

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Author information

Authors and Affiliations

  1. Software College, Northeastern University, Shenyang, China

    Wenyu Zhang & Tianhan Gao

Authors
  1. Wenyu Zhang
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  2. Tianhan Gao
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Contributions

The authors declare that there is no conflict of interest regarding the publication of this paper.

Corresponding author

Correspondence to Tianhan Gao .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Information Security Engineering, Soonchunhyang University, Asan, Korea (Republic of)

    Kangbin Yim

  3. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

    Hsing-Chung Chen

Ethics declarations

This work was supported by the National Natural Science Foundation of China under [Grant Number N180716019 and N182808003].

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Zhang, W., Gao, T. (2022). Improved Optimal Reciprocal Collision Avoidance Algorithm in Racing Games. In: Barolli, L., Yim, K., Chen, HC. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2021. Lecture Notes in Networks and Systems, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-79728-7_21

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