Seo Lab, Institute of Science Tokyo

Publications

Selected publications

• Iizuka, K. and Seo, T. Passenger-oriented distributed traffic signal control using dynamic programming with vehicle queue spillback and waiting time constraints. International Journal of Intelligent Transportation Systems Research, 2024
• Chen, X., Qin, G., Seo, T., Yin, J., Tian, Y., and Sun, J. A macro-micro approach to reconstructing vehicle trajectories on multi-lane freeways with lane changing. Transportation Research Part C: Emerging Technologies, Vol. 160, p. 104534, 2024.
• Kawase, R. and Iryo, T. Optimal stochastic inventory-distribution strategy for damaged multi-echelon humanitarian logistics network. European Journal of Operational Research, 2023.
• Maruyama, R. and Seo, T. Integrated public transportation system with shared autonomous vehicles and fixed-route transits: Dynamic traffic assignment-based model with multi-objective optimization. International Journal of Intelligent Transportation Systems Research, 2023.   [PDF]
• Seo, T., Wada, K., and Fukuda, D. Fundamental diagram of urban rail transit considering train–passenger interaction. Transportation, 2022.   [PDF]
• Seo, T. and Asakura, Y. Multi-objective linear optimization problem for strategic planning of shared autonomous vehicle operation and infrastructure design. IEEE Transactions on Intelligent Transportation Systems, Vol. 23, pp. 3816–3828, 2022.   [PDF]
• Seo, T., Kawasaki, Y., Kusakabe, T., and Asakura, Y. Fundamental diagram estimation by using trajectories of probe vehicles. Transportation Research Part B: Methodological, Vol. 122, pp. 40–56, 2019.   [PDF]
• Seo, T., Kusakabe, T., Gotoh, H., and Asakura, Y. Interactive online machine learning approach for activity-travel survey. Transportation Research Part B: Methodological, Vol. 123, pp. 362–373, 2019.   [PDF]
• Seo, T., Bayen, A. M., Kusakabe, T., and Asakura, Y. Traffic state estimation on highway: A comprehensive survey. Annual Reviews in Control, Vol. 43, pp. 128–151, 2017.   [PDF]
• Seo, T., Kusakabe, T., and Asakura, Y. Estimation of flow and density using probe vehicles with spacing measurement equipment. Transportation Research Part C: Emerging Technologies, Vol. 53, pp. 134–150, 2015.   [PDF]

*The underlined authors represent the (ex-)members of our lab.

Comprehensive lists of our publications

• Toru Seo's HP
• Toru Seo's Google Scholar
• Riki Kawase's HP

Theses

Doctor's degree

• Nagasaki, Kota: Transportation systems analysis with angle: Modeling and empirical studies, AY2023
• Dahiya, Garima: Fundamental diagrams and traffic state estimation methods: analysis and modeling using Zen Traffic Data, AY2022

Master's degree

• Ma, Yuxun: Hybrid travel behavior models with utility-maximization theory and graph neural network, AY2024
• Iizuka, Kanae: Passenger-oriented distributed traffic signal control in the era of ridesharing, AY2023
• Fujiya, Keiichiro: Modeling pedestrian fundamental diagram based on directional statistics, AY2023
• Ryota Marumaya: Theoretical analysis of dynamic optimal pricing for shared autonomous vehicle system, AY2023
• Mizuno, Kenya: Analysis of social optimal state of general piggyback transportation, AY2023
• Yamashita, Naoya: Mathematical analysis of modal choice between ridesharing and conventional public transportation considering round-trip, AY2022
• Lee, Inho: MFD-based traffic simulation under large-scale construction, AY2022
• Zhong, Hengyi: Generation of aggregated road network by only vehicle trajectory data, AY2022
• Sato, Kimihiro*: Dynamic network congestion pricing based on deep reinforcement learning, AY2021
• Sakai, Kengo*: Traffic state estimation method per lane using surrounding environment observation probe vehicle, AY2020

Bachelor's degree

• Ishii, Yuki: Multi-objective optimization of freight and passenger joint transportation in shared autonomous vehicle systems, AY2023
• Hayashi, Kazuma: Vehicle and section-dependent speed-spacing relation estimation using hierarchical Bayesian model, AY2023
• Oda, Koki: Estimation of location-dependent fundamental diagram based on probe vehicle data and sparse modeling, AY2022
• Fujikawa, Yoshiki: Optimization method for dynamic congestion pricing with deep reinforcement learning, AY2022
• Komatsu, Yuta: Equilibrium analysis of rural transportation system with ride sourcing services, AY2022
• Kanamori, Yuki: Short-term future prediction of diverging ratio on road network without OD information by machine learning, AY2021
• Maruyama, Ryota: Multi-objective optimization of shared autonomous vehicle system: Integration with BRT and user optimal assignment, AY2021
• Fumiyama, So*: Traffic state estimation method using Link Transmission Model and mobile sensing, AY2020
• Sato, Kimihiro*: Data-driven congestion toll optimization method using reinforcement learning, AY2019
• Sakai, Kengo*: Traffic density estimation method using small satellite imagery, AY2018

*: those who have not been in this Lab but supervised by Toru Seo.