Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision

The proposed model was validated on the Simulation of Urban Mobility (SUMO) platform, underscoring its superior performance in improving lane-change safety.

Authors

Z. Chen
Kai Zhu (ORCID: https://orcid.org/0000-0002-8779-8865)

Institutions

Jiangsu University of Technology (CN)

Publication Details

Journal: Traffic Injury Prevention
Published: 2026-01-20
DOI: https://doi.org/10.1080/15389588.2025.2607637
Primary Topic: Traffic control and management
Type: article
Field-Weighted Citation Impact: 0.00

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article

Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision

Z. Chen, Kai Zhu

Jan 20, 2026

Traffic Injury Prevention

Traffic control and management

article

Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision

Z. Chen, Kai Zhu

January 20, 2026article en

Abstract

The proposed model was validated on the Simulation of Urban Mobility (SUMO) platform, underscoring its superior performance in improving lane-change safety.

Traffic Injury Prevention

Jiangsu University of Technology (CN)

Sustainable cities and communities

Openalex Percentile: Top 83%

Traffic control and management

DOI Source OpenAlex

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Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision — Z. Chen, Kai Zhu · Traffic Injury Prevention (2026) | TGRS Research Map | TGRS