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 Abstract This study proposes autonomous…
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…
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.…
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…
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…
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…
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…
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…
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…
A new paper was published in Transportation Research Part D: Transport and Environment entitled “Empirical investigation of the emission-macroscopic fundamental diagram co-authored by LUTS members and Prof. Gonzales from University of Massachussets Amherts, USA. Highlights We analyse vehicle emissions in a multi-modal urban area using the pNEUMA dataset. EPA’s microscopic emission model, project level MOVES is implemented. We investigate aggregated…