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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 Abstract Modeling and learning interactions with surrounding vehicles are critical for the…
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…