Review of Path Planning Algorithms for Unmanned Vehicles

Shen, Yunyi; Liu, Jian; Luo, Yasong

doi:10.1109/iciba52610.2021.9688064

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Dijkstra algorithm belongs to the traditional traversal algorithm, its core idea is to divide the nodes into two sets, one is the set of nodes for which the shortest path has been found, and the other is the set of nodes for which the shortest path has not yet been found. The algorithm works by continuously selecting the node that currently has the shortest distance from the source and updating the distance values of the neighboring nodes of that node until the shortest path is found for all the nodes or until there are no reachable nodes [4]. Solving for shortest paths using Dijkstra algorithm, as shown in Figure 1.…”

Section: Origin and Fundamentals Of Dijkstra Algorithmmentioning

confidence: 99%

“…(2) Cannot handle negatively weighted edges, requires that edge weights in the graph must be non-negative. [4] (3) Applies to global path planning and can solve the shortest path problem from a given starting point to all other vertices in the graph, i.e., single-source shortest path. [4] (4) Require that the graph cannot contain loops or circular paths.…”

Section: Applicable Environment and Conditionsmentioning

confidence: 99%

“…(4) For cases where you need to get a specific path. [4] In the article [11], the authors constructed Dijkstra's algorithmic program and A* algorithmic program, as shown in Figure 3 and Figure 4. By observing the code of these two path algorithms, we can observe more clearly and intuitively the different points of their calculation steps.…”

Section: A* Algorithmmentioning

confidence: 99%

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Dijkstra and A* algorithms in automated vehicle driving

Lin

2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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Path planning technology is one of the current hotspots of research in many intelligent technology fields, which has a broad application prospect and research value. With the rapid improvement of computer arithmetic power and the widespread popularization of automation, automatic driving has gradually become a hot topic of people's attention. Among them, path planning algorithms play a central role in the field of automatic driving. In this paper, firstly, it will summarize and introduce the development history and basic principles of the two basic path algorithms, Dijkstra algorithm and A* algorithm, list the advantages and disadvantages of these two path planning methods based on graph search and the application scenarios, and then analyze and compare Dijkstra algorithm and A* algorithm, discuss their advantages and disadvantages in the field of intelligent driving, and finally make an outlook of future development directions of the path planning technology in the field of intelligent driving. The research in this paper will provide certain reference value to the researchers of path planning algorithms for intelligent vehicles. It will be of great value to the research and application of new path planning algorithms based on Dijkstra and A* algorithms in the future.

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Section: Origin and Fundamentals Of Dijkstra Algorithmmentioning

confidence: 99%

Section: Applicable Environment and Conditionsmentioning

confidence: 99%