Identifying High-Risk Situations in Right-Turn Phase of Heavy-Duty Vehicles Using Naturalistic Driving Data Southeast University

Format:

Book

Conference/Event

Author/Creator:

Zhang, Hedi, author.

Contributor:

Chen, Shuyan

Fu, Yuanhang

Ma, Yongfeng

Conference Name:

2024 International Conference on Smart Transportation Interdisciplinary Studies (2024-12-13 : Nanjing, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

The interaction between heavy-duty vehicles turning right and non-motor vehicles going straight has led to severe traffic crashes. It is essential to evaluate the driving risk of heavy-duty vehicles in the right-turn phase. Increasingly, studies have explored some indicators associated with driving risk. Based on naturalistic driving data of 121 heavy-duty vehicles in Nanjing, this research combined factor analysis and K-means cluster algorithm to assess the driving risk of two scenarios, one without a blind spot warning and another with a blind spot warning during the right-turn phase. The results have concluded the driving characteristics of heavy-duty vehicles under different risk levels. It formed a set of driving risk level assessment methods for heavy-duty vehicles in the right-turn phase. This evaluation method is expected to identify high-risk right-turn behaviors of heavy-duty vehicles and provide some insights to practitioners for traffic management

Notes:

Vendor supplied data

Publisher Number:

2025-01-7209

Access Restriction:

Restricted for use by site license