林典超
基本信息
林典超
副教授
研究方向
联网车，智能交通管理，道路交通管控，微观路权交易，智慧出行
讲授课程
联系方式
- 通信地址： 经管西楼215
- 电子邮箱： lindianchao@fzu.edu.cn
个人简介
林典超，男，籍贯福州，纽约大学交通规划及工程博士，副教授，硕士生导师，福建省C类引进人才，海外旗山学者。主要研究兴趣集中在城市交通管控及其相关科学问题上。
学习经历
2016 - 2021：纽约大学，交通规划与工程，博士
2013 - 2016：同济大学，交通信息工程，学术硕士
2009 - 2013：同济大学，交通工程，学士
2013 - 2016：同济大学，交通信息工程，学术硕士
2009 - 2013：同济大学，交通工程，学士
工作经历
2022 至今：福州大学，管理科学与工程，副教授
科研项目
主持国家自然科学基金青年项目:《基于智能交通管理的微观路权实时优化与交易系统设计》（72201065），2022-2025，¥30万。
主持福建省自然科学基金青年项目：《基于车联网的微观路权交易与管理系统设计》（2023J0123），2023-2026，¥5万。
主持福建省自然科学基金青年项目：《基于车联网的微观路权交易与管理系统设计》（2023J0123），2023-2026，¥5万。
获奖经历
近年发表的主要论文
期刊论文：
1.Lin, D., Ma, W.*, Li, L., Wang, Y.H. (2016) A driving force model for non-strict priority crossing behaviors of right-turn drivers. Transportation Research Part B: Methodological, 83, 230-244. (交通顶刊)
2. Zheng, F., Jabari, S.E.*, Liu, H.X., and Lin, D. (2018). Traffic state estimation using stochastic Lagrangian dynamics. Transportation Research Part B: Methodological, 115, 143-165. (交通顶刊)
3. Lin, D., Li, L., and Jabari, S.E*. (2019) Pay to change lanes: A cooperative lane-changing strategy for connected/automated driving. Transportation Research Part C: Emerging Technologies, 105, pp.550-564. (交通顶刊)
4. Jabari, S.E.* G., Dilip, D.M., Lin, D. & Thodi, B.T. (2019). Learning traffic flow dynamics using random fields. IEEE Access, 7, 130566-130577.
5. Lin, D., and Jabari, S.E.*. (2021) Pay for intersection priority: A free market mechanism for connected vehicles. IEEE Transactions on Intelligent Transportation Systems. (智能交通顶刊)
6. Li, L., and Lin, D.*. (2021) Three-player cooperative game with side-payments for discretionary lane changes of connected vehicles. IEEE Access.
7. Li, L., and Lin, D.*. (2022) Design and comparative analysis on real-time trade of road priority in connected traffic. IEEE Access.
8. Fang, J., Wu, X., Lin D.*, Xu, M.*, Wu, H, Wu, X., and Bi T. (2023). A Map-matching Algorithm with Extraction of Multi-group Information for Low-frequency Data. IEEE Intelligent Transportation Systems Magazine.
8. Lin D., Li L. (2023). An Efficient Safety-Oriented Car-Following Model for Connected Automated Vehicles Considering Discrete Signals[J]. IEEE Transactions on Vehicular Technology.
主要会议论文：
1. Lin, D., Chen, X.*, Lin, B., Li, L. (2014) Phenomena and characteristics of moped-passing-bicycle on shared lanes. 93rd Annual Meeting of the TRB (No.14-1970).
2. Lin, D., Li, L., Zang, Z.Q., Ma, W.*. (2015) New saturation flow rate adjustment method of shared right-turn lanes with bikes’ effect in China. 94th Annual Meeting of the TRB (No.15-3594).
3. Li, L., Lin, D., Chen, X., Ma, W.* (2015) Saturation flow rate of shared non-motorized lane at intersections. 94th Annual Meeting of the TRB (No.15-0837).
4. Lin, D.*, Li, L., and Jabari, S.E. (2018) Lane changing strategies for connected vehicles using cooperative game theory. UAEGSRC (Graduate Students Research Conference).
5. Li, L., and Lin, D.*. (2018) A Safety-oriented car-following model for connected automated vehicles. UAEGSRC (Graduate Students Research Conference).
6. Lin, D.*, Li, L., Tembine, H., and Jabari, S.E. (2019) Pay to Change Lanes: A Lane-Changing Strategy for Connected/Automated Driving Using Cooperative Game Theory. 98th Annual Meeting of the TRB (No. 19-04412).
7. Li, L., Lin, D.*, Pantelidis, T., Jabari, S.E., and Chow, Y.J. J. (2019) An agent-based simulation for shared automated electric vehicles with vehicle relocation. In 2019 IEEE Intelligent Transportation systems conference (ITSC), pp. 3308-3313. IEEE, 2019.
8. Lin, D.*, and Jabari, S.E.. (2019) Transferable utility games based intersection control for connected behicles. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 3496-3501. IEEE, 2019.
9. Li, L., Lin, D.*, and Jabari, S.E. (2020). A user-based charge and subsidy scheme for single O-D network mobility management. In 2020 IEEE Intelligent Transportation Systems Conference (ITSC). IEEE.
10. Lin, D.*, and Jabari, S.E. (2020). Comparative analysis of economic instruments in intersection operation: A user-based perspective. In 2020 IEEE Intelligent Transportation Systems Conference (ITSC). IEEE.
11. Li L., and Lin, D.* (2022). A cooperative game for discretionary lane-changes with side-payments: a multi-lane case in connected vehicle environment. 101st Annual Meeting of the TRB (TRBAM-22-04587).
12. Lin D., Li L.*, Xue N., et al (2023). Learning Imminent Throughput for Real-time Intersection Control with Deep Neural Network. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE.
1.Lin, D., Ma, W.*, Li, L., Wang, Y.H. (2016) A driving force model for non-strict priority crossing behaviors of right-turn drivers. Transportation Research Part B: Methodological, 83, 230-244. (交通顶刊)
2. Zheng, F., Jabari, S.E.*, Liu, H.X., and Lin, D. (2018). Traffic state estimation using stochastic Lagrangian dynamics. Transportation Research Part B: Methodological, 115, 143-165. (交通顶刊)
3. Lin, D., Li, L., and Jabari, S.E*. (2019) Pay to change lanes: A cooperative lane-changing strategy for connected/automated driving. Transportation Research Part C: Emerging Technologies, 105, pp.550-564. (交通顶刊)
4. Jabari, S.E.* G., Dilip, D.M., Lin, D. & Thodi, B.T. (2019). Learning traffic flow dynamics using random fields. IEEE Access, 7, 130566-130577.
5. Lin, D., and Jabari, S.E.*. (2021) Pay for intersection priority: A free market mechanism for connected vehicles. IEEE Transactions on Intelligent Transportation Systems. (智能交通顶刊)
6. Li, L., and Lin, D.*. (2021) Three-player cooperative game with side-payments for discretionary lane changes of connected vehicles. IEEE Access.
7. Li, L., and Lin, D.*. (2022) Design and comparative analysis on real-time trade of road priority in connected traffic. IEEE Access.
8. Fang, J., Wu, X., Lin D.*, Xu, M.*, Wu, H, Wu, X., and Bi T. (2023). A Map-matching Algorithm with Extraction of Multi-group Information for Low-frequency Data. IEEE Intelligent Transportation Systems Magazine.
8. Lin D., Li L. (2023). An Efficient Safety-Oriented Car-Following Model for Connected Automated Vehicles Considering Discrete Signals[J]. IEEE Transactions on Vehicular Technology.
主要会议论文：
1. Lin, D., Chen, X.*, Lin, B., Li, L. (2014) Phenomena and characteristics of moped-passing-bicycle on shared lanes. 93rd Annual Meeting of the TRB (No.14-1970).
2. Lin, D., Li, L., Zang, Z.Q., Ma, W.*. (2015) New saturation flow rate adjustment method of shared right-turn lanes with bikes’ effect in China. 94th Annual Meeting of the TRB (No.15-3594).
3. Li, L., Lin, D., Chen, X., Ma, W.* (2015) Saturation flow rate of shared non-motorized lane at intersections. 94th Annual Meeting of the TRB (No.15-0837).
4. Lin, D.*, Li, L., and Jabari, S.E. (2018) Lane changing strategies for connected vehicles using cooperative game theory. UAEGSRC (Graduate Students Research Conference).
5. Li, L., and Lin, D.*. (2018) A Safety-oriented car-following model for connected automated vehicles. UAEGSRC (Graduate Students Research Conference).
6. Lin, D.*, Li, L., Tembine, H., and Jabari, S.E. (2019) Pay to Change Lanes: A Lane-Changing Strategy for Connected/Automated Driving Using Cooperative Game Theory. 98th Annual Meeting of the TRB (No. 19-04412).
7. Li, L., Lin, D.*, Pantelidis, T., Jabari, S.E., and Chow, Y.J. J. (2019) An agent-based simulation for shared automated electric vehicles with vehicle relocation. In 2019 IEEE Intelligent Transportation systems conference (ITSC), pp. 3308-3313. IEEE, 2019.
8. Lin, D.*, and Jabari, S.E.. (2019) Transferable utility games based intersection control for connected behicles. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 3496-3501. IEEE, 2019.
9. Li, L., Lin, D.*, and Jabari, S.E. (2020). A user-based charge and subsidy scheme for single O-D network mobility management. In 2020 IEEE Intelligent Transportation Systems Conference (ITSC). IEEE.
10. Lin, D.*, and Jabari, S.E. (2020). Comparative analysis of economic instruments in intersection operation: A user-based perspective. In 2020 IEEE Intelligent Transportation Systems Conference (ITSC). IEEE.
11. Li L., and Lin, D.* (2022). A cooperative game for discretionary lane-changes with side-payments: a multi-lane case in connected vehicle environment. 101st Annual Meeting of the TRB (TRBAM-22-04587).
12. Lin D., Li L.*, Xue N., et al (2023). Learning Imminent Throughput for Real-time Intersection Control with Deep Neural Network. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE.
出版著作
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