Day-to-Day Flow Dynamics and Congestion Control
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DOI: 10.1287/trsc.2015.0596
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- Qixiu Cheng & Zhiyuan Liu & Feifei Liu & Ruo Jia, 2017. "Urban dynamic congestion pricing: an overview and emerging research needs," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(0), pages 3-18, August.
- Li, Ruijie & Liu, Xiaobo & Nie, Yu (Marco), 2018. "Managing partially automated network traffic flow: Efficiency vs. stability," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 300-324.
- Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
- Huang, Hai-Jun & Xia, Tian & Tian, Qiong & Liu, Tian-Liang & Wang, Chenlan & Li, Daqing, 2020. "Transportation issues in developing China's urban agglomerations," Transport Policy, Elsevier, vol. 85(C), pages 1-22.
- Ren-Yong Guo & Hai-Jun Huang & Hai Yang, 2019. "Tradable Credit Scheme for Control of Evolutionary Traffic Flows to System Optimum: Model and its Convergence," Networks and Spatial Economics, Springer, vol. 19(3), pages 833-868, September.
- Minyu Shen & Feng Xiao & Weihua Gu & Hongbo Ye, 2024. "Cognitive Hierarchy in Day-to-day Network Flow Dynamics," Papers 2409.11908, arXiv.org.
- Chen, Xinyuan & Zhang, Wei & Guo, Xiaomeng & Liu, Zhiyuan & Wang, Shuaian, 2021. "An improved learning-and-optimization train fare design method for addressing commuting congestion at CBD stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
- Ren-Yong Guo & Hai Yang & Hai-Jun Huang, 2018. "Are We Really Solving the Dynamic Traffic Equilibrium Problem with a Departure Time Choice?," Transportation Science, INFORMS, vol. 52(3), pages 603-620, June.
- Qixiu Cheng & Jun Chen & Honggang Zhang & Zhiyuan Liu, 2021. "Optimal Congestion Pricing with Day-to-Day Evolutionary Flow Dynamics: A Mean–Variance Optimization Approach," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
- Ye, Hongbo & Xiao, Feng & Yang, Hai, 2021. "Day-to-day dynamics with advanced traveler information," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 23-44.
- Liu, Renming & Jiang, Yu & Seshadri, Ravi & Ben-Akiva, Moshe & Azevedo, Carlos Lima, 2024. "Contextual Bayesian optimization of congestion pricing with day-to-day dynamics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
- Wang, Dong & Liao, Feixiong, 2023. "Incentivized user-based relocation strategies for moderating supply–demand dynamics in one-way car-sharing services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
- Liang, Qingnan & Li, Xin-an & Chen, Zhibin & Pan, Tianlu & Zhong, Renxin, 2023. "Day-to-day traffic control for networks mixed with regular human-piloted and connected autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
- Hongbo Ye & Hai Yang, 2017. "Rational Behavior Adjustment Process with Boundedly Rational User Equilibrium," Transportation Science, INFORMS, vol. 51(3), pages 968-980, August.
- Li, Pengbo & Tian, Lijun & Xiao, Feng & Zhu, Hongwei, 2022. "Can day-to-day dynamic model be solved analytically? New insights on portraying equilibrium and accommodating autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 374-395.
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Keywords
traffic dynamics; congestion control; user equilibrium; convergence;All these keywords.
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