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Treating Noise and Anomalies in pNEUMA dataset

A collaboration between researchers from EPFL LUTS and TUM TUM School of Engineering and Design resulted in the publication of a paper entitled “Treating Noise and Anomalies in Vehicle Trajectories From an Experiment With a Swarm of Drones” in IEEE Transactions on Intelligent Transportation Systems. Vishal Mahajan, Manos Barmpounakis, Md. Rakib Alam, Nikolas Geroliminis and Constantinos Antoniou utilise the pNEUMA…

Investigating lane usage, lane changing and lane choice

A paper by Jasso Espadaler Clapés,Manos Barmpounakis and Nikolas Geroliminis was published inTransportation Research Part A: Policy and Practice entitled “Empirical investigation of lane usage, lane changing and lane choice phenomena in a multimodal urban arterial”. The authors utilise the pNEUMA dataset to investigate lane usage, lane changing and lane choice phenomena utilising the pNEUMA dataset. Highlights Abstract The combination…

pNEUMA Vision: The visual extension of pNEUMA

You can download the extension of the pNEUMA dataset, nicknamed pNEUMA Vision in the downloads section of our website or here. pNEUMA Vision incorporates imagery data and annotations of vehicles in the form of image coordinates along with newly added vehicle trajectory features like azimuth. More information can be found in the related journal article in TRC (here) where we…

Using pNEUMA to calibrate car-following models

A paper by Yifan Zhang, Xinhong Chen, Jianping Wang, Zuduo Zheng, Kui Wu was published inTransportation Research Part C: Emerging Technologies entitled “A generative car-following model conditioned on driving styles”. The authors utilise the pNEUMA dataset to calibrate an intelligent Intelligent Driver Model (IDM) with time-varying parameters and train the neural process (NP)-based model. Highlights Abstract Car-following (CF) modeling, an…