A paper by Yongwei Li, Yongzhi Jiang and Xinkai Wu was published inTransportation Research Part C: Emerging Technologies entitled "TrajPT: A trajectory data-based pre-trained transformer model for learning multi-vehicle interactions". The authors propose a model designed to learn spatial–temporal interactions among vehicles, trained using the pNEUMA dataset.
Highlights
Propose TrajPT, a trajectory data-based pre-trained transformer…
A paper by Zhiwei Yang, Zuduo Zheng, Jiwon Kim and Hesham Rakha was published inTransportation Research Part C: Emerging Technologies entitled "Eco-driving strategies using reinforcement learning for mixed traffic in the vicinity of signalized intersections". The authors utilise the pNEUMA dataset instead of simulated trajectories toused to train and test the reinforcement learning methods.
Highlights…
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
A method to…
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…
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 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…
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…
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…
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…
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…