Qinglong Lu
Qinglong Lu is a Research Associate and a Ph.D. candidate at Technical University of Munich (TUM) since June 2021. His research focuses on mobility pattern analysis, transportation system resilience evaluation, ride-sharing services, and DTA model calibration.
Qinglong holds a bachelor’s degree in Traffic Engineering from Sun Yat-sen University (SYSU), China, and a Master of Science in Transportation Systems from Technical University of Munich (TUM), Germany.
Other links: Google Scholar Github ResearchGate
Education
| Jun 2021 - Present | Ph.D. Candidate Technical University of Munich (TUM) Munich, Germany |
| Oct 2018 - Oct 2020 | M.Sc. in Transportation Systems Technical University of Munich (TUM) Munich, Germany |
| Sep 2014 - Jun 2018 | B.E. in Traffic Engineering Sun Yat-sen University (SYSU) Guangzhou, China |
Teaching
Summer semester: Statistical Learning and Data Analytics for Transportation Systems
Winter semester: Special Topic on Model Calibration
Supervising
- Transfer learning for transportation system resilience estimation using floating car data. (State: Finished. Student: Ningkang Yang. Thesis) (ITS Bavaria Award 2023: Best Master’s Thesis)
- Optimizing the Siting of Urban Air Mobility Systems in Multimodal Transportation Networks: Integration with Demand-Responsive Transit Services. Mentoring: Hao Wu and Qinglong Lu. Download description. (release date: 31.03.2023)
Selected Publications
Journal publications
Lu, Q. L., Qurashi, M., & Antoniou, C. (2023). Simulation-based policy analysis: The case of urban speed limits. Transportation Research Part A: Policy and Practice, 175, 103754.
Lu, Q. L., Qurashi, M., & Antoniou, C. (2022). A ridesplitting market equilibrium model with utility-based compensation pricing. Transportation, 1-36.
Qurashi, M., Lu, Q. L., Cantelmo, G., & Antoniou, C. (2022). Dynamic demand estimation on large scale networks using Principal Component Analysis: The case of non-existent or irrelevant historical estimates. Transportation Research Part C: Emerging Technologies, 136, 103504.
Lu, Q. L., Qurashi, M., Varesanovic, D., Sodnik, J., & Antoniou, C. (2021). Exploring the influence of automated driving styles on network efficiency. Transportation Research Procedia, 52, 380-387.
Lu, Q. L. (2020). A structural equations approach for modeling the endogeneity of lane-mean speeds considering the downstream speeds. European Journal of Transport and Infrastructure Research, 20(4), 252-265.
Conference contributions
Lu, Q.L., Qurashi, M., & Antoniou, C. (2023). A Two-Stage Stochastic Programming approach for Dynamic OD Estimation. In 102th TRB Annual Meeting 2023.
Lu, Q.L., Qurashi, M., & Antoniou, C. (2022). A Stochastic Programming Method for OD Estimation Using LBSN Check-In Data. In 4th Symposium on Management of Future Motorway and Urban Traffic Systems.
Lu, Q. L., Yang, K., & Antoniou, C. (2021). Crash risk analysis for the mixed traffic flow with human-driven and connected and autonomous vehicles. In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) (pp. 1233-1238). IEEE.
Qurashi, M., Lu, Q., Cantelmo, G., & Antoniou, C. (2021). PC-SPSA: Exploration and assessment of different historical data--set generation methods for enhanced DTA model calibration. In 9th Symposium of the European Association for Research in Transportation (hEART2020).
Qurashi, M., Lu, Q., Cantelmo, G., & Antoniou, C. (2020). PC-SPSA: Implementation assessment and exploration of different historical data-set generation methods for enhanced DTA model calibration. In 3rd Symposium on Management of Future Motorway and Urban Traffic Systems.
Gao, J., Lu, Q. L., & Cai, M. (2020). Quantifying privacy vulnerability under linkage attack across multi-source individual mobility data. In 99th Transportation Research Board (TRB) Annual Meeting.