ArticleScientific reports2025
Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Improved Immune Moth-Flame Algorithm for Intelligent Vehicle Parking Path Optimization.Biomimetics (Basel, Switzerland) · 2026Article
- Rule-adaptive lane-changing trajectory planning method for autonomous vehicles driven by dynamic risk information.Scientific reports · 2025Article
- An Overview of Autonomous Parking Systems: Strategies, Challenges, and Future Directions.Sensors (Basel, Switzerland) · 2025Review
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Authors and funding
7 authors.
Funding
Abstract
The rapid acceleration of urbanization and the surge in car ownership necessitate efficient automatic parking solutions in constricted spaces to address the escalating urban parking issue. To optimize space utilization, enhance traffic efficiency, and mitigate accident risks, a method is proposed for smooth, comfortable, and adaptable automatic parking trajectory planning. This study initially employs a hybrid A* algorithm to generate a preliminary path, then fits the velocity and acceleration based on a cubic polynomial. The kinematic constraints of the vehicle and obstacle avoidance constraints are then meticulously defined, and a coupled nonlinear model predictive control (NMPC) method is employed to optimize the trajectory. Compared to the hybrid A* algorithm, the optimized trajectory demonstrates superior space utilization and improved smoothness. The experimental results indicate that the proposed method performs effectively in automated parking tasks in confined spaces, suggesting promising applications and broad prospects for future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.