Research

I have published on applications of machine learning and deep learning for predicting traffic and driving patterns. Some of the publications are listed here:

• 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.

• Mahajan, V., Barmpounakis, E., Alam, Md R., Geroliminis, N., Antoniou, C. (2023) Treating Noise and Anomalies in Vehicle Trajectories from an Experiment with a Swarm of Drones. IEEE Transactions on Intelligent Transportation Systems.

• Wu X., Lyu C., Lu, Q.-L., Mahajan, V. (2023) Similarity-based Feature Extraction for Large-scale Sparse Traffic Forecasting. arXiv.

• Mahajan V., Llorca C., Moeckel R., Antoniou C. (2023) Which (open) data do transport modelers really use? EURO working group on Transportation (EWGT) Conference 2023.

• Mahajan V., Cantelmo G., Rothfeld R., Antoniou C. (2023) Predicting network flows from speeds using open data and transfer learning. IET Intell. Transp. Syst. 00, 1– 21.

• Mahajan V., Kuehnel N., Intzevidou A., Cantelmo G., Moeckel R., & Antoniou C. (2021) Data to the people: a review of public and proprietary data for transport models. Transport Reviews, 0(0), 1–26.

• Mahajan V., Cantelmo G. & Antoniou C. (2021) Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich. Eur. Transp. Res. Rev. 13, 26.

• Mahajan V., Katrakazas C., & Antoniou C. (2022) Crash Risk Estimation Due to Lane Changing: A Data-Driven Approach Using Naturalistic Data. IEEE Transactions on Intelligent Transportation Systems, 23(4), 3756–3765.

• Mahajan V., Katrakazas C., & Antoniou C. (2020). Prediction of Lane-Changing Maneuvers with Automatic Labeling and Deep Learning. Transportation Research Record, 2674(7), 336–347.

More details on publications can be found on Google Scholar.