Parking Path Optimization Model for Parking Robots Based on Vehicle Specifications

Myeonggeun Jang; Sunghee Lee; Jooyoung Kim

doi:10.7470/jkst.2025.43.1.077

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2025 Vol.43, Issue 1 Preview Page Next Page

Article

Parking Path Optimization Model for Parking Robots Based on Vehicle Specifications 차량 제원에 따른 주차로봇 주차 경로 최적화 모델

28 February 2025. pp. 77-91

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Abstract

The rapid pace of urbanization has resulted in a severe shortage of parking spaces and inefficient parking management, leading to traffic congestion in modern cities. While parking robot technology has attracted attention as an innovative solution, current commercialized systems have limitations in generating paths tailored to vehicle size or shape, restricting their practical effectiveness. This challenge is particularly relevant in the context of diverse vehicle sizes and shapes as seen in Korea. To optimize parking efficiency, it is essential to incorporate more accurate representations of vehicle dimensions and obstacles within parking lots. Such optimization enhances space utilization, reduces operational costs, and improves user satisfaction. This study proposes a hybrid parking path generation model that combines Hybrid A-star and RRT algorithms, aiming to reduce path generation time even with a finer grid resolution. The model integrates real-time vehicle size measurement using LiDAR sensors. Simulations are based on a real public parking lot, featuring scenarios with obstacles in constrained spaces as well as general parking conditions. The proposed model is evaluated for improvements in path shortening, time reduction, and obstacle avoidance over existing algorithms. Future research will expand this approach to encompass more complex urban layouts and diverse parking conditions.

Keywords

hybrid model

obstacle avoidance

parking robots

path optimization

vehicle specifications

도시화의 가속화로 인해 주차 공간의 부족과 비효율적인 주차로 인한 교통 혼잡은 현대 도시에서 심각한 문제로 대두되고 있다. 이를 해결하기 위한 혁신적인 대안으로 주차로봇 기술이 주목받고 있으나, 현재 상용화된 주차로봇은 차량의 크기나 형태에 맞춘 개별적인 경로 생성이 미흡해 실질적인 효율성 증대에 한계가 있다. 특히, 다양한 차량 크기와 형태를 사용하는 국내 환경에서, 차량의 제원과 주차장 내 장애물의 크기를 더 정밀하게 반영하는 경로 생성이 필요하다. 이러한 경로 최적화는 주차 공간의 효율적 활용을 가능하게 하고, 주차장 운영 비용 절감 및 사용자 만족도를 향상시키는데 기여할 수 있다. 본 연구는 Hybrid A-star 알고리즘과 RRT 알고리즘을 혼합하여 격자를 더욱 세분화하더라도 경로 생성 시간을 감소할 수 있는 혼합 주차 경로 생성 모델을 제안한다. 또한, 라이다(LiDAR) 센서를 이용하여 실시간으로 차량의 크기를 측정하고 이를 경로 생성에 반영한다. 시뮬레이션 환경은 실제 운영 중인 공영주차장을 기반으로, 장애물이 있는 제한적인 시나리오와 장애물이 없는 일반적인 시나리오를 구축하여 분석을 진행하였다. 제안된 모델은 기존 알고리즘과 비교하여 주차 경로 거리 단축, 시간 단축, 장애물 회피 능력 측면에서 효용성을 평가하였다. 향후 연구에서는 더 복잡한 도심 구조와 다양한 주차 조건을 고려한 확장 연구가 이루어질 것이다.

키워드

혼합 모델

장애물 회피

주차 로봇

경로 최적화

차량 제원

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Information

Publisher :Korean Society of Transportation
Publisher(Ko) :대한교통학회
Journal Title :Journal of Korean Society of Transportation
Journal Title(Ko) :대한교통학회지
Volume : 43
No :1
Pages :77-91
Received Date : 2024-11-01
Revised Date : 2024-11-28
Accepted Date : 2024-12-18
DOI :https://doi.org/10.7470/jkst.2025.43.1.077

Journal of Korean Society of Transportation ISSN:1229-1366(Print) 2234-4217(Online) 대한교통학회지

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