Safe and efficient DRL driving policies using fuzzy logic for urban lane changing scenarios

Safe and efficient DRL driving policies using fuzzy logic for urban lane changing scenarios

Lane changing is common in driving. Thus, the possibility of traffic accidents occurring during lane changes is high given the complexity of this process. One of the primary objectives of intelligent driving is to increase a vehicle’s behavior, making it more similar to that of a real driver. This s...

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Bibliographic Details
Main Authors: Ling Han, Xiangyu Ma, Yiren Wang, Lei He, Yipeng Li, Lele Zhang, Qiang Yi
Format: Article
Language:English
Published: Tsinghua University Press 2025-03-01
Series:Journal of Intelligent and Connected Vehicles
Subjects:
autonomous vehicles (avs)
decision-making
fuzzy logic
lane change
reinforcement learning
Online Access:https://www.sciopen.com/article/10.26599/JICV.2024.9210054
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