# Autonomous Vehicle Parking in Dynamic Environments: An Integrated System with Prediction and Motion Planning

arXiv: https://arxiv.org/abs/2204.10383 · HTML: https://mlsanity.com/paper/2204.10383/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Placed in Imitation-learning end-to-end planners, one of 9 directions in End-to-end autonomous driving.
- Builds on 8 of its 67 references that are in the map.
- First posted on arXiv 21 Apr 2022.

## Placed in

- End-to-end autonomous driving / [Imitation-learning end-to-end planners](https://mlsanity.com/driving/imitation-learning-end-to-end-planners/)

## Builds on (most cited first, 8 of 8)

- [How would surround vehicles move? A Unified Framework for Maneuver Classification and Motion Prediction](https://mlsanity.com/paper/1801.06523/) (2018)
- [Optimization-Based Collision Avoidance](https://mlsanity.com/paper/1711.03449/) (2017)
- [Search-based optimal motion planning for automated driving](https://mlsanity.com/paper/1803.04868/) (2018)
- [ParkPredict: Motion and Intent Prediction of Vehicles in Parking Lots](https://mlsanity.com/paper/2004.10293/) (2020)
- [An Efficient B-spline-Based Kinodynamic Replanning Framework for Quadrotors](https://mlsanity.com/paper/1906.09785/) (2019)
- [Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach](https://mlsanity.com/paper/2011.00413/) (2020)
- [Trajectory Replanning for Quadrotors Using Kinodynamic Search and Elastic Optimization](https://mlsanity.com/paper/1903.01139/) (2019)
- [Improving Trajectory Optimization using a Roadmap Framework](https://mlsanity.com/paper/1811.02044/) (2018)

## Built on by (most cited first, 5 of 5)

- [ParkDiffusion: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction for Automated Parking using Diffusion Models](https://mlsanity.com/paper/2505.00586/) (2025)
- [A Multi-Heuristic Search-based Motion Planning for Automated Parking](https://mlsanity.com/paper/2307.07857/) (2023)
- [Integrated Intention Prediction and Decision-Making with Spectrum Attention Net and Proximal Policy Optimization](https://mlsanity.com/paper/2408.03191/) (2024)
- [SEG-Parking: Towards Safe, Efficient, and Generalizable Autonomous Parking via End-to-End Offline Reinforcement Learning](https://mlsanity.com/paper/2509.13956/) (2025)
- [Learning Reliable Parking Policies via Offline Reinforcement Learning with Quantized Action Representations](https://mlsanity.com/paper/2609.19894/) (2026)

## Abstract (arXiv)

This paper presents an integrated motion planning system for autonomous vehicle (AV) parking in the presence of other moving vehicles. The proposed system includes 1) a hybrid environment predictor that predicts the motions of the surrounding vehicles and 2) a strategic motion planner that reacts to the predictions. The hybrid environment predictor performs short-term predictions via an extended Kalman filter and an adaptive observer. It also combines short-term predictions with a driver behavior cost-map to make long-term predictions. The strategic motion planner comprises 1) a model predictive control-based safety controller for trajectory tracking; 2) a search-based retreating planner for finding an evasion path in an emergency; 3) an optimization-based repairing planner for planning a new path when the original path is invalidated. Simulation validation demonstrates the effectiveness of the proposed method in terms of initial planning, motion prediction, safe tracking, retreating in an emergency, and trajectory repairing.