Adaptive congestion index-based A* algorithm for dynamic vehicle path planning optimization
Yulun Du,
Gang Liu,
Yunhao Jiang,
Siteng Cai and
Jing He
Physica A: Statistical Mechanics and its Applications, 2025, vol. 672, issue C
Abstract:
To enhance traffic efficiency of urban transportation networks, it is essential to comprehensively consider factors such as the congestion index and road network topology. The congestion index serves as a core metric for objectively evaluating urban traffic conditions, primarily used to assess the traffic performance of transportation networks. This study introduces the principle of probability density segmentation to address the limitations of existing congestion index models, which inadequately account for the spatiotemporal characteristics of traffic flow speed. By segmenting vehicle speed based on distance and time, a congestion index model with adaptive adjustment capabilities is established. Based on this, an improved A* algorithm (MVPP-ACI-IA) is proposed based on dynamic multi-objective path-planning mechanism and adaptive congestion index. Results demonstrate that, compared to the traditional A* algorithm, the proposed method dynamically adjusts vehicle routes, improving traffic efficiency by approximately 10.95 %. Our approach significantly mitigates road congestion under high traffic load scenarios.
Keywords: Congestion index; Probability density segmentation; Dynamic path optimization algorithm; Optimized A* algorithm; Urban traffic flows; Road traffic efficiency (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437125003541
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:672:y:2025:i:c:s0378437125003541
DOI: 10.1016/j.physa.2025.130702
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().