Funder
National Natural Science Foundation of China
China Scholarship Council
Outstanding Young Scientific and Technological Talents Foundation of Sichuan Province
Major Program of National Social Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Reference39 articles.
1. Abdollahi, M., Khaleghi, T., & Yang, K. (2020). An integrated feature learning approach using deep learning for travel time prediction. Expert Systems with Applications, 139, 112864.
2. Allström, A., Ekström, J., Gundlegård, D., Ringdahl, R., Rydergren, C., Bayen, A. M., & Patire, A. D. (2016). Hybrid approach for short-term traffic state and travel time prediction on highways. Transportation Research Record, 2554(1), 60–68.
3. Bates, J., Polak, J., Jones, P., & Cook, A. (2001). The valuation of reliability for personal travel. Transportation Research Part E: Logistics and Transportation Review, 37(2–3), 191–229.
4. Billings, D. & Yang, J.-S. (2006). Application of the ARIMA models to urban roadway travel time prediction-a case study. In 2006 IEEE International Conference on Systems, Man and Cybernetics, vol. 3, pp. 2529–2534: IEEE.
5. Carrion, C., & Levinson, D. (2012). Value of travel time reliability: A review of current evidence. Transportation Research Part a: Policy and Practice, 46(4), 720–741.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献