Improved Two-Layer Stacking Model for Prediction of the Level of Delay Caused by Crashes: An Empirical Analysis of Texas

Author:

Wang Zehao1,Jiao Pengpeng2,Wang Jianyu3,Luo Wei3,Lu Huapu4

Affiliation:

1. Master’s Candidate, Beijing Key Laboratory of General Aviation Technology, Beijing Univ. of Civil Engineering and Architecture, 15 Yongyuan Rd., Beijing 100044, China.

2. Professor, Beijing Key Laboratory of General Aviation Technology, Beijing Univ. of Civil Engineering and Architecture, 15 Yongyuan Rd., Beijing 100044, China (corresponding author).

3. Lecturer, Beijing Key Laboratory of General Aviation Technology, Beijing Univ. of Civil Engineering and Architecture, 15 Yongyuan Rd., Beijing 100044, China.

4. Professor, Institute of Transportation Engineering and Geomatics, Tsinghua Univ., 30 Shuangqing Rd., Beijing 100084, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Reference109 articles.

1. Class-imbalanced crash prediction based on real-time traffic and weather data: A driving simulator study;Abou Elassad Z. E.;Traffic Inj. Prev.,2020

2. A real-time crash prediction fusion framework: An imbalance-aware strategy for collision avoidance systems;Abou Elassad Z. E.;Transp. Res. Part C Emerging Technol.,2020

3. Analysis of factors affecting the frequency of crashes on interstate freeways by vehicle type considering multiple weather variables;Aguilar C.;J. Transp. Saf. Secur.,2022

4. Stochastic local search for the feature set problem, with applications to microarray data;Albrecht A. A.;Appl. Math. Comput.,2006

5. Traffic crashes cost estimation in Kuwait;Al-Rukaibi F.;Int. J. Crashworthiness,2020

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1. Traffic Delay Analysis for Intelligent Transportation System using Deep Learning;2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA);2023-09-29

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