# Adaptive Spatio-Temporal Voxels Based Trajectory Planning for Autonomous Driving in Highway Traffic Flow

arXiv: https://arxiv.org/abs/2310.02625 · HTML: https://mlsanity.com/paper/2310.02625/

## Key facts

- No citing papers in the map yet (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 7 of its 24 references that are in the map.
- First posted on arXiv 4 Oct 2023.

## 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, 7 of 7)

- [Baidu Apollo EM Motion Planner](https://mlsanity.com/paper/1807.08048/) (2018)
- [CitySim: A Drone-Based Vehicle Trajectory Dataset for Safety Oriented Research and Digital Twins](https://mlsanity.com/paper/2208.11036/) (2022)
- [EPSILON: An Efficient Planning System for Automated Vehicles in Highly Interactive Environments](https://mlsanity.com/paper/2108.07993/) (2021)
- [Safe Trajectory Generation for Complex Urban Environments Using Spatio-temporal Semantic Corridor](https://mlsanity.com/paper/1906.09788/) (2019)
- [Diverse Critical Interaction Generation for Planning and Planner Evaluation](https://mlsanity.com/paper/2103.00906/) (2021)
- [Move Beyond Trajectories: Distribution Space Coupling for Crowd Navigation](https://mlsanity.com/paper/2106.13667/) (2021)
- [Domain Knowledge Driven Pseudo Labels for Interpretable Goal-Conditioned Interactive Trajectory Prediction](https://mlsanity.com/paper/2203.15112/) (2022)

## Abstract (arXiv)

Trajectory planning is crucial for the safe driving of autonomous vehicles in highway traffic flow. Currently, some advanced trajectory planning methods utilize spatio-temporal voxels to construct feasible regions and then convert trajectory planning into optimization problem solving based on the feasible regions. However, these feasible region construction methods cannot adapt to the changes in dynamic environments, making them difficult to apply in complex traffic flow. In this paper, we propose a trajectory planning method based on adaptive spatio-temporal voxels which improves the construction of feasible regions and trajectory optimization while maintaining the quadratic programming form. The method can adjust feasible regions and trajectory planning according to real-time traffic flow and environmental changes, realizing vehicles to drive safely in complex traffic flow. The proposed method has been tested in both open-loop and closed-loop environments, and the test results show that our method outperforms the current planning methods.