Publications

Journal

  1. Santiago-Iglesias, E., Romanillos, G., Carpio-Pinedo, J., Sun, W. and García-Palomares, J.C. (2024). Recovering Urban Nightlife: COVID-19 Insights from Google Places Activity Trends in Madrid. Journal of Maps. [Download]
  2. Santiago-Iglesias, E., Romanillos, G., Sun, W., Schmöcker, J. D., Moya-Gómez, B. and García-Palomares, J.C. (2024). Light in the Darkness: Urban Nightlife, Analyzing the Impact and Recovery of COVID-19 using Mobile Phone Data. Cities. [Download]
  3. Lu, Q.L., Dai, J., Sun, W.Z., Schmöcker, J. D. and Antoniou, C. (2024). Framework for Evaluating Urban Resilience to Pandemics: Analysis of Transport-Related Containment Policies. Research Handbook on Transport and COVID-19. [Download]
  4. Lu, Q. L., Sun, W., Dai, J., Schmöcker, J. D., & Antoniou, C. (2024). Traffic resilience quantification based on macroscopic fundamental diagrams and analysis using topological attributes. Reliability Engineering & System Safety, 247, 110095. [Download]
  5. Nozawa, K., Sun, W., Schmoecker, J. D., & Nakao, S. (2024). The Impact of COVID-19 Policies on Nightlife in Kyoto. Findings. [Download]
  6. Yang, N., Lu, Q. L., Lyu, C., & Antoniou, C. (2024). Transfer Learning for Transportation Demand Resilience Pattern Prediction Using Floating Car Data. Transportation Research Record, 03611981241245681. [Download]
  7. Nishigaki, T., Schmöcker, J. D., Yamada, T., & Nakao, S. (2024). Using entropy maximisation for establishing city-wide touristic tour patterns. Applied Soft Computing, 154, 111316. [Download]
  8. Lyu, C., Lu, Q. L., Wu, X., & Antoniou, C. (2024). Tucker factorization-based tensor completion for robust traffic data imputation. Transportation Research Part C: Emerging Technologies, 160, 104502. [Download]
  9. Lu, Q. L., Qurashi, M., & Antoniou, C. (2024). A two-stage stochastic programming approach for dynamic OD estimation using LBSN data. Transportation Research Part C: Emerging Technologies, 158, 104460. [Download]
  10. Lu, Q. L., Mahajan, V., Lyu, C., & Antoniou, C. (2024). Analyzing the impact of fare-free public transport policies on crowding patterns at stations using crowdsensing data. Transportation Research Part A: Policy and Practice, 179, 103944. [Download]
  11. Dai, J., Schmöcker, J. D. and Sun, W.Z. (2024). Analyzing demand reduction and recovery of major rail stations in Japan during COVID-19 using mobile spatial statistics. Asian Transport Studies, 10, 100120. [Download]
  12. Santiago-Iglesias, E., Schmöcker, J. D., Carpio-Pinedo, J., García-Palomares, J.C. and Sun, W.Z. (2023). Activity Reduction as Resilience Indicator: Evidence with Filomena Data. Findings. Section: Resilience Findings, [Download]
  13. Santiago-Iglesias, E., Carpio-Pinedo, J., Sun, W., & García-Palomares, J. C. (2023). Frozen city: Analysing the disruption and resilience of urban activities during a heavy snowfall event using Google Popular Times. Urban Climate, 51. [Download]
  14. Sun, W.Z., Kobayashi, H., Nakao, S. and Schmöcker, J. D. (2023). On the relationship between crowdsourced sentiments and mobility trends during COVID-19: A case study of Kyoto. Data Science for Transportation, 5:17. [Download]
  15. 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. [Download]
  16. Vongvanich, T. Sun, W. and Schmöcker, J.-D.(2023). Explaining and predicting station demand patterns using Google Popular Times data. Data Science for Transportation, 5(10). [Download]
  17. Fernández, O. A. P., & Gómez, B. M. (2023). El sistema médico de emergencias de Madrid a prueba: análisis del rendimiento espaciotemporal del SAMUR-PC en los primeros meses de la nueva normalidad postCOVID-19. Boletín de la Asociación de Geógrafos Españoles, (96), 3. [Download]
  18. Nishigaki, T., Schmöcker, J. D., Yamada, T., & Nakao, S. (2023, February). Estimating the Number of Tourists in Kyoto Based on GPS Traces and Aggregate Mobile Statistics. In Proceedings of the 12th International Scientific Conference on Mobility and Transport: Mobility Innovations for Growing Megacities (pp. 221-243). Singapore: Springer Nature Singapore. [Download]
  19. Arias-Molinares, D., García-Palomares, J. C., & Gutiérrez, J. (2022). Micromobility services before and after a global pandemic: impact on spatio-temporal travel patterns. International Journal of Sustainable Transportation, 1-16. [Download]
  20. Palomares, J. C. G., & Molinares, D. A. (2022). Nuevas formas de movilidad en la ciudad. In El mundo visto de las ciudades (pp. 583-590). Tirant Humanidades. [Download]
  21. Schmöcker, J. D. Urban public transport fare design dimensions Post Covid and in a Sharing Society with a focus on Japan. [Download]
  22. Condeço-Melhorado, A. M., Palomares, J. C. G., Arroyo, G. R., & Puebla, J. G. (2022). Destinos ganadores y destinos perdedores en los veranos de la pandemia: Un análisis basado en datos de telefonía móvil. In Leyendo el territorio: Homenaje a Miguel Ángel Troitiño (pp. 556-568). Universidad de Guadalajara. [Download]
  23. Sun, W., Schmöcker, J. D., & Nakao, S. (2022). Restrictive and stimulative impacts of COVID-19 policies on activity trends: A case study of Kyoto. Transportation research interdisciplinary perspectives, 13, 100551. [Download]
  24. Gressai, M., Varga, B., Tettamanti, T., & Varga, I. (2021). Investigating the impacts of urban speed limit reduction through microscopic traffic simulation. Communications in transportation research, 1, 100018. [Download]
  25. Lu, Q., & Tettamanti, T. (2021). Impacts of connected and automated vehicles on freeway with increased speed limit. International Journal of Simulation Modelling, 20(3), 453-464. [Download]
  26. Lu, Q., & Tettamanti, T. (2021). Traffic control scheme for social optimum traffic assignment with dynamic route pricing for automated vehicles. Periodica Polytechnica Transportation Engineering, 49(3), 301-307. [Download]
  27. Sun, W., & Schmöcker, J. D. (2021). Demand estimation for public transport network planning. In The Routledge Handbook of Public Transport (pp. 289-305). Routledge. [Download]

Conference

  1. Lu, Q.L., Dai, J., Sun, W., Schmöcker, J.-D. and Antoniou, C. (2023). An MFD-Based Optimization Approach to Improve Transportation System Resilience under Infrastructure Disruptions. Euro Working Group on Transportation – EWGT2023. [Download]
  2. Dai, J., Sun, W., Schmöcker, J.-D., Lu, Q. and Antoniou, C. (2023). On the resilience of railway station demand in response to unexpected events: A case study of Japan in COVID-19. Euro Working Group on Transportation – EWGT2023. [Download]
  3. Dai, J., Sun, W. and Schmöcker, J.-D. (2023). Analyzing Demand Reduction and Recovery of Major Rail Stations in Japan during COVID-19 Using Mobile Spatial Statistics. 15th International Conference of Eastern Asia Society for Transportation Studies (EASTS). Kuala Lumpur, Malaysia, September 4-7. [Download]
  4. Santiago-Iglesias, E., Romanillos, G., García-Palomares, J.C., Sun, W., Schmöcker, J.-D., Mallo, J., Sánchez-Cauce, R., Cantu-Ros, O. G. (2023). Urban nightlife recovery: An Analysis of the Effects of the COVID-19 Pandemic based on Mobile Phone Network Data. 62nd Congress of the European Regional Science Association. Alacante, Spain, 28 Aug - 01 Sep. [Download]
  5. Bi, M., Sun, W.Z. Schmöcker, J.-D., Ma, Y., Moya-Gomez, B., Nakao, S. and Yamada, T. (2023). Using Geo-tagged Tweets for Understanding Activity Distribution in Kyoto. 67th Japan Infrastructure Planning Conference (Autumn Meeting), Fukuoka, Japan. June 3-4. [Download]
  6. Keler, A., Sun, W. and Schmöcker, J.-D. (2023). Generating and Calibrating a Microscopic Traffic Flow Simulation Network of Kyoto – First Insights from Simulating Private and Public Transport. SUMO User Conference 2023. May 2-4, Berlin, Germany. [Download]
  7. Nakao, S. and Schmöcker, J.-D. (2023). Improving Tourist Area Awareness using Bluetooth Beacons and Gamification. 102nd Annual Meeting of the Transportation Research Board. Washington D.C., U.S. [Download]
  8. Nakao, S., Kobayashi, H., Sun, W.Z. and Schmöcker, J.-D. (2023). On the relationship between tweet sentiments and mobility trends during COVID-19: A case study of Kyoto. 102nd Annual Meeting of the Transportation Research Board. Washington D.C., U.S. [Download]
  9. Gao, Y. and Schmöcker, J.-D. (2023). Inferring travel patterns and the attractiveness of touristic areas based on Fusing Wi-Fi sensing data and GPS traces with a Kyoto Case Study. 102nd Annual Meeting of the Transportation Research Board. Washington D.C., U.S. [Download]
  10. Lu, Q.L., Qurashi, M., & Antoniou, C. (2023). A Two-Stage Stochastic Programming approach for Dynamic OD Estimation. In 102th TRB Annual Meeting 2023. [Download]
  11. Gao, Y. and Schmöcker, J.-D. (2022). Inferring city-scale tours based on Wi-Fi sensing with aid of a small sample of GPS footprints. 16th International Conference on Travel Behaviour Research (IATBR). December 11 - 15, Santiago, Chile. [Download]
  12. 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. [Download]
  13. Nishigaki, T., Schmöcker, J.-D., Yamada, T. and Nakao, S. (2022). 観光者数に基づく観光行動推定手法に関する基礎的研究. (Basic research on methods for estimating tourist behaviour based on the number of tourists). 66th Japan Infrastructure Planning Conference (Autumn Meeting), Okinawa, Japan. November 11-13 (In Japanese). [Download]
  14. Namulindwa, S., Schmöcker, J.-D., Nakao, S. and Sun, W.Z. (2022). Emergent Prospects of Wi-Fi Sensor Data In Crowd Density Modelling and Prediction; An on-campus experiment. 66th Japan Infrastructure Planning Conference (Autumn Meeting), Okinawa, Japan. November 11-13. [Download]
  15. Vongvanich, T. Sun, W. and Schmöcker, J.-D.(2022). Explaining station demand patterns using Google Popular Times data. 15th International Conference on Advanced Systems in Public Transport (CASPT). 6-10 November, Tel Aviv, Israel. Also presented in shorter form at: 4th International KEC Conference, Kantipur Engineering College, Nepal, online. [Download]
  16. Arias-Molinares, D., García-Palomares, J. C., Romanillos-Arroyo, G., Gutiérrez, J. (2022). Servicios de micromovilidad antes y después de una pandemia global: impacto de la COVID-19 en los patrones espaciotemporales de las nuevas formas de movilidad. International Conference on Regional Science. Challenges, policies and governance of the territories in the post-covid era. Granada (España). From October 19 to 22, 2022. [Download]
  17. Lu, Q.L., Qurashi, M., & Antoniou, C. (2022). A Two-Stage Stochastic Programming approach for Dynamic OD Estimation. In 102th TRB Annual Meeting 2023. [Download]
  18. 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. [Download]
  19. Carpio-Pinedo, J., Santiago-Iglesias, E., García-Palomares, J.C. (2022). La ciudad bajo la nieve: dinámica de las actividades urbanas durante un evento de nevadas extremas utilizando Google Points of Interest. XIX Congreso de Tecnologías de la Información Geográfica. “TIG al servicio de los ODS”. Zaragoza (España). From September 12 to 14, 2022. [Download]
  20. Condeço-Melhorado, A., García-Palomares, J.C., Romanillos-Arroyo, G., Gutiérrez, J. (2022). Destinos ganadores y destinos perdedores en el verano de 2020: Un análisis de flujos turísticos basado en datos de telefonía móvil. XIX Congreso de Tecnologías de la Información Geográfica. “TIG al servicio de los ODS”. Zaragoza (España). From September 12 to 14, 2022. [Download]
  21. Arias Molinares, D., García-Palomares, J. C., Romanillos-Arroyo, G., Gutiérrez, J. (2022). Micromobility services after COVID-19 pandemic: findings from the analysis of spatio-temporal patterns. Extraordinary IGU Centennial Congress (IGU2022): Climate change, resilience, urban health and well-being. Paris (Francia). [Download]
  22. C. Antoniou, COVID-19, Transportation and Urban Resilience: A Conceptual Framework, RLS- Sciences April Digital Week 2022: Sustainable and Resilient Regional Recoveries, online, 2022/4/5 [Download]
  23. J.-D. Schmoecker and W.Z. Sun, Learning urban mobility and activity patterns with Kyoto case study during and after COVID-19. 2021 Seoul Big Data Forum, online. [Download]
  24. N. Matsuoka, COVID-19が京都に与えた影響に関する時系列分析, Annual Meeting of the JSCE Kansai Branch, online. [Download]
  25. W. Sun and J.-D. Schmoecker, Restrictive and Stimulative Impacts of Covid-19 Policies on Human Mobility Trends: A Case Study of Kyoto. 101st Annual Meeting of the Transportation Research Board. Washington D.C., U.S. [Download]