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Ms. Yue Zhang
Tongji University

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Research Keywords & Expertise

0 Autonomous Vehicles
0 Traffic Analysis
0 Traffic Safety
0 Driving behavior
0 traffic big data analysis and decision-making

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Journal article
Published: 10 June 2021 in Measurement
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Lane-changing duration (LCD) measures the total time it takes for a vehicle to travel from the current lane to the target lane. However, there is still a paucity research on LCD up to now. In this paper, we present a comprehensive analysis of LCD from the perspective of survival analysis. Naturalistic vehicle trajectory HighD dataset is employed in this paper, which contains of 16.5 h of measurement and over 11,000 vehicles. Both comparative univariate and regression analysis has been conducted to research the characteristic of the whole survival function and the influencing factors of LCD. Results indicate that Generalized Gamma distribution has high degree of coincidence with the non-parametric method in estimating the survival function, and LoglogisticAFT model exhibits more credible results than other regression models. Furthermore, the results and modeling implications have been discussed. We hope this paper could contribute to our further understanding of LCD and LC behaviors.

ACS Style

Yang Li; Linbo Li; Daiheng Ni; Yue Zhang. Comprehensive survival analysis of lane-changing duration. Measurement 2021, 182, 109707 .

AMA Style

Yang Li, Linbo Li, Daiheng Ni, Yue Zhang. Comprehensive survival analysis of lane-changing duration. Measurement. 2021; 182 ():109707.

Chicago/Turabian Style

Yang Li; Linbo Li; Daiheng Ni; Yue Zhang. 2021. "Comprehensive survival analysis of lane-changing duration." Measurement 182, no. : 109707.

Journal article
Published: 04 January 2021 in Sustainability
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Climate change and the extreme weather have a negative impact on road traffic safety, resulting in severe road traffic accidents. In this study, a negative binomial model and a log-change model are proposed to analyse the impact of various factors on fatal traffic accidents. The dataset used in this study includes the fatal traffic accident frequency, social development indicators and climate indicators in California and Arizona. The results show that both models can provide accurate fitting results. Climate variables (i.e., average temperature and standard precipitation 24) can significantly affect the frequency of fatal traffic accidents. Non-climate variables (i.e., beer consumption, rural Vehicle miles travelled ratio, and vehicle performance) also have a significant impact. The modelling results can provide decision-making guidelines for the transportation management agencies to improve road traffic safety.

ACS Style

Yajie Zou; Yue Zhang; Kai Cheng. Exploring the Impact of Climate and Extreme Weather on Fatal Traffic Accidents. Sustainability 2021, 13, 390 .

AMA Style

Yajie Zou, Yue Zhang, Kai Cheng. Exploring the Impact of Climate and Extreme Weather on Fatal Traffic Accidents. Sustainability. 2021; 13 (1):390.

Chicago/Turabian Style

Yajie Zou; Yue Zhang; Kai Cheng. 2021. "Exploring the Impact of Climate and Extreme Weather on Fatal Traffic Accidents." Sustainability 13, no. 1: 390.