Transportation resilience under Covid-19 Uncertainty: A traffic severity analysis
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DOI: 10.1016/j.tra.2023.103947
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- Alsaleh, Nael & Farooq, Bilal, 2021. "Interpretable data-driven demand modelling for on-demand transit services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 1-22.
- Cai, Qing & Abdel-Aty, Mohamed & Sun, Yangyang & Lee, Jaeyoung & Yuan, Jinghui, 2019. "Applying a deep learning approach for transportation safety planning by using high-resolution transportation and land use data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 71-85.
- Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
- Ali, Azam & Kalatian, Arash & Choudhury, Charisma F., 2023. "Comparing and contrasting choice model and machine learning techniques in the context of vehicle ownership decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
- Wu, Peijie & Chen, Tianyi & Diew Wong, Yiik & Meng, Xianghai & Wang, Xueqin & Liu, Wei, 2023. "Exploring key spatio-temporal features of crash risk hot spots on urban road network: A machine learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
- Liu, Aijun & Li, Zengxian & Shang, Wen-Long & Ochieng, Washington, 2023. "Performance evaluation model of transportation infrastructure: Perspective of COVID-19," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
- Hu, Songhua & Xiong, Chenfeng & Chen, Peng & Schonfeld, Paul, 2023. "Examining nonlinearity in population inflow estimation using big data: An empirical comparison of explainable machine learning models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
- Wen-Long Shang & Yanyan Chen & Xingang Li & Washington Y. Ochieng, 2020. "Resilience Analysis of Urban Road Networks Based on Adaptive Signal Controls: Day-to-Day Traffic Dynamics with Deep Reinforcement Learning," Complexity, Hindawi, vol. 2020, pages 1-19, November.
- Peng, Qiao & Liu, Weilong & Zhang, Yong & Zeng, Shihong & Graham, Byron, 2023. "Generation planning for power companies with hybrid production technologies under multiple renewable energy policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
- Wu, Peijie & Meng, Xianghai & Song, Li, 2021. "Bayesian space–time modeling of bicycle and pedestrian crash risk by injury severity levels to explore the long-term spatiotemporal effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
- Xie, Zhixiao & Yan, Jun, 2013. "Detecting traffic accident clusters with network kernel density estimation and local spatial statistics: an integrated approach," Journal of Transport Geography, Elsevier, vol. 31(C), pages 64-71.
- Víctor Corcoba Magaña & Xabiel García Pañeda & Roberto Garcia & Sara Paiva & Laura Pozueco, 2021. "Beside and Behind the Wheel: Factors that Influence Driving Stress and Driving Behavior," Sustainability, MDPI, vol. 13(9), pages 1-17, April.
- Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
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Keywords
Transportation resilience; Traffic severity; Covid-19 uncertainty; Explainable machine learning;All these keywords.
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