Lane Change Decision Algorithm based on Risk Prediction and Fuzzy Logic Method

Autor: Moussa Boukhnifer, Ahmed Chaibet, Vincent Judalet, Amin Mechernene
Rok vydání: 2021
Předmět:
Zdroj: ICSTCC
DOI: 10.1109/icstcc52150.2021.9607228
Popis: One major objective of the autonomous driving is to act similarly to a real driver for two main reasons: to be comprehensible by the surrounding drivers, and to be accepted by the passengers. In this work, a decision algorithm for lane changing in highways and arterial road is elaborated. The first step consists of a risk assessment based on predicted trajectories to determine the optimal moment to start the maneuver. Based on the level of risk and a coefficient called “Gain” that measures the driver’s interest in changing lane, a fuzzy logic model decides if the maneuver should be performed or not.
Databáze: OpenAIRE