Application of an Improved A* Algorithm for the Path Analysis of Urban Multi-Type Transportation Systems

Abstract

The modern urban transportation service network could be split into unrestricted and restricted networks depending on whether travelers face limitations in route selection. Along with the continuous expansion of the city, it is difficult for travelers to find a more reasonable travel solution when confronted with such a complex transportation service network, which combines both unrestricted and restricted networks, especially for the park-and-ride (P&R) travel mode. This paper addresses the issue of route analysis in modern urban transportation service systems to provide travelers with reasonable travel solutions based on multiple types of transportation services. An improved A* algorithm is proposed to address the optimal path analysis for restricted networks to provide reasonable travel solutions for public transportation trips. Furthermore, by establishing the topological relationship between restricted and unrestricted networks, this paper presented an improved A* algorithm based on hybrid networks that solves the optimal path analysis problem for P&R trips, bringing convenience to many urban travelers.

Path Planning Algorithm of Orchard Fertilization Robot Based on Multi-Constrained Bessel Curve

“…According to the simulated orchard environment map established above, as shown in Figure 4, the starting point of the fertilization robot is set as (1,3), and the target point is set as (5,3). Multi-constrained Bessel curve, unconstrained Bessel curve, improved A* full coverage, and comb full coverage path planning algorithms were used for planning, and the planned path was tracked using the improved pure tracking algorithm [24][25][26][27] proposed in Section 2.…”

“…Path planning is a hotspot and key issue in the research concerning orchard fertilizer robots, i.e., to find a continuous path for the robot to meet its motion requirements in the complex orchard environment. Path point search is the basis of path planning; the current mainstream method is based on the raster path planning algorithms, such as Dijkstra's algorithm, A* algorithm [2][3][4][5][6][7], D* algorithm, etc. Dijksta's algorithm, as a greedy algorithm, can produce the optimal solution of the path, but traversal times, memory occupation, long running time remain an issue [8].…”