Open Access

ARTICLE

Research on Parking Path Planing Based on A-Star Algorithm

Zhiliang Deng, Dong Wang^*

Nanjing University of Information Science & Technology, Nanjing, 210044, China

* Corresponding Author: Dong Wang. Email:

Journal of New Media 2023, 5(1), 55-64. https://doi.org/10.32604/jnm.2023.040252

Received 10 February 2023; Accepted 14 March 2023; Issue published 14 June 2023

Abstract

The issue of finding available parking spaces and mitigating congestion during parking is a persistent challenge for numerous car owners in urban areas. In this paper, we propose a novel method based on the A-star algorithm to calculate the optimal parking path to address this issue. We integrate a road impedance function into the conventional A-star algorithm to compute path duration and adopt a fusion function composed of path length and duration as the weight matrix for the A-star algorithm to achieve optimal path planning. Furthermore, we conduct simulations using parking lot modeling to validate the effectiveness of our approach, which can provide car drivers with a reliable optimal parking navigation route, reduce their parking costs, and enhance their parking experience.

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