# Autonomous Vehicles Path Planning under Temporal Logic Specifications

arXiv: https://arxiv.org/abs/2410.07845 · HTML: https://mlsanity.com/paper/2410.07845/

## 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 5 of its 19 references that are in the map.
- First posted on arXiv 10 Oct 2024.

## 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, 5 of 5)

- [On Robustness Metrics for Learning STL Tasks](https://mlsanity.com/paper/2003.06041/) (2020)
- [Arithmetic-Geometric Mean Robustness for Control from Signal Temporal Logic Specifications](https://mlsanity.com/paper/1903.05186/) (2019)
- [Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization](https://mlsanity.com/paper/2110.00339/) (2021)
- [Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models](https://mlsanity.com/paper/1811.07489/) (2018)
- [Optimizing Demonstrated Robot Manipulation Skills for Temporal Logic Constraints](https://mlsanity.com/paper/2209.03001/) (2022)

## Abstract (arXiv)

Path planning is an essential component of autonomous driving. A global planner is responsible for the high-level planning. It basically performs a shortest-path search on a known map, thereby defining waypoints used to control the local (low-level) planner. Local planning is a runtime verification method which is repeatedly run on the vehicle itself in real-time, so as to find the optimal short-horizon path which leads to the desired waypoint in a way which is both efficient and safe. The challenge is that the local planner has to take into account repeatedly incoming updates about the information available of the environment. In addition, it performs a complex task, as it has to take into account a large variety of requirements, originating from the necessity of collision avoidance with obstacles, respecting traffic rules, sticking to regulatory requirements, and lastly to reach the next waypoint efficiently. In this paper, we describe a logic-based specification mechanism which fulfills all these requirements.