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Inferring vehicle spacing in urban traffic from trajectory data

A paper by Yiru Jiao, Simeon Calvert, Sander van Cranenburgh and Hans van Lint was published inTransportation Research Part C: Emerging Technologies entitled “Inferring vehicle spacing in urban traffic from trajectory data”. The authors utilise the pNEUMA dataset to infer the average two-dimensional (2D) spacing between interacting vehicles in urban traffic. Highlights Abstract This study presents a new method to…

The relation of traffic congestion and noise emissions using the pNEUMA dataset

A paper by Jasso Espadaler Clapés,Manos Barmpounakis and Nikolas Geroliminis was published inTransportation Research Part D: Transport and Environment entitled “Traffic congestion and noise emissions with detailed vehicle trajectories from UAVs”. The authors utilise the pNEUMA dataset to investigate the relation between noise emissions and traffic congestion. Abstract Excessive noise in cities due to road traffic negatively affects human health.…

Multi-agent Signal-less Intersection Management with Dynamic Platoon Formation

A paper by Phuriwat Worrawichaipat, Enrico H. Gerding, Ioannis Kaparias and Sarvapali Ramchurn was presented in AAMAS 2023 entitled “Multi-agent Signal-less Intersection Management with Dynamic Platoon Formation”. The paper that was presented in the Innovative Applications and is utilizing the pNEUMA dataset to validate and evaluate their work on signal-less traffic control. Abstract We propose a novel mechanism to manage…

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…

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…

Using pNEUMA to monitor and assess the behavior of Freight Vehicles

A paper by Allister Loder, Thomas Otte and Klaus Bogenberger was published inTransportation Research Record entitled “Using Large-Scale Drone Data to Monitor and Assess the Behavior of Freight Vehicles on Urban Level”. The authors utilise the pNEUMA dataset to monitor and assess the behaviour of freight vehicles, focusing on the way their stopping behaviour affects traffic flow. Highlights Urban freight…

High Time-Resolution Queue Profile Estimation at Signalized Intersections Based on Extended Kalman Filtering

A very interesting paper has been published in IEEE Transactions on Intelligent Transportation Systems entitled “High Time-Resolution Queue Profile Estimation at Signalized Intersections Based on Extended Kalman Filtering” utilising the pNEUMA dataset.. The authors from Zhejiang University, Aalto University and University of Illinois at Urbana-Champaign, used both simulated and real-world data to evaluate the performance of their methodology. Highlights A…