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A Rule-Based Behaviour Planner for Autonomous Driving
- Source :
- Rules and Reasoning (2022) 263-279
- Publication Year :
- 2024
-
Abstract
- Autonomous vehicles require highly sophisticated decision-making to determine their motion. This paper describes how such functionality can be achieved with a practical rule engine learned from expert driving decisions. We propose an algorithm to create and maintain a rule-based behaviour planner, using a two-layer rule-based theory. The first layer determines a set of feasible parametrized behaviours, given the perceived state of the environment. From these, a resolution function chooses the most conservative high-level maneuver. The second layer then reconciles the parameters into a single behaviour. To demonstrate the practicality of our approach, we report results of its implementation in a level-3 autonomous vehicle and its field test in an urban environment.<br />Comment: Use https://link.springer.com/chapter/10.1007/978-3-031-21541-4_17 for citations
- Subjects :
- Computer Science - Artificial Intelligence
Computer Science - Robotics
Subjects
Details
- Database :
- arXiv
- Journal :
- Rules and Reasoning (2022) 263-279
- Publication Type :
- Report
- Accession number :
- edsarx.2407.00460
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/978-3-031-21541-4_17