Adaptive Multi-Mode Path Planning for Four-Wheel Independent Steering Vehicles

Abstract

This study proposes an adaptive multi-mode graph search algorithm that integrates spatial previewing with terminal analytics to address node proliferation and terminal oscillation in path planning for four-wheel independent steering (4WIS) vehicles under complex, low-speed conditions. By employing line-of-sight checking and the Douglas–Peucker algorithm to extract the environmental topological skeleton, the proposed method generates Predictive Spatial Profiling (PSP) fields that precisely quantify channel safety margins. Departing from conventional soft-weight arbitration, a dynamic driving state machine leverages these rigid spatial constraints to deterministically prune redundant expansion branches—including Ackermann steering, crab steering, and in-place rotation—prior to node generation. Furthermore, a comprehensive cost function incorporating a mode-switching penalty and a gradient-heading heuristic is formulated to accelerate search convergence. To circumvent reliance on traditional empirical distance thresholds, a topology-triggered, multi-dimensional terminal analytical strategy is introduced, enabling a seamless transition from discrete search node expansion to continuous curve generation near the target. Extensive simulations demonstrate that the proposed algorithm reduces both the node expansion scale and optimization time by over 80% compared with conventional unconstrained methods, while effectively mitigating chaotic motion-mode transitions. Ultimately, integrating environmental spatial dimensionality reduction with terminal analytics yields a highly efficient and smooth global path-planning solution for 4WIS vehicles.