57 citations · 130 across the 31 of their papers we have counts for
5 papers · 1 filter
Graph Neural Network Approach to Predict the Effects of Road Capacity Reduction Policies: A Case Study for Paris, France
Elena Natterer, Roman Engelhardt, Sebastian Hörl +1
Rapid urbanization and growing urban populations worldwide present significant challenges for cities, including increased traffic congestion and air pollution. Effective strategies…
Semi-on-Demand Off-Peak Transit Services with Shared Autonomous Vehicles -- Service Planning, Simulation, and Analysis in Munich, Germany
Max T. M. Ng, Roman Engelhardt, Florian Dandl +3
This study investigates the implementation of semi-on-demand (SoD) hybrid-route services using Shared Autonomous Vehicles (SAVs) on existing transit lines. SoD services combine the…
Multi-Task Lane-Free Driving Strategy for Connected and Automated Vehicles: A Multi-Agent Deep Reinforcement Learning Approach
Mehran Berahman, Majid Rostami-Shahrbabaki, Klaus Bogenberger
Deep reinforcement learning has shown promise in various engineering applications, including vehicular traffic control. The non-stationary nature of traffic, especially in the lane…
Semi-on-Demand Hybrid Transit Route Design with Shared Autonomous Mobility Services
Max T. M. Ng, Florian Dandl, Hani S. Mahmassani +1
Shared Autonomous Vehicles (SAVs) enable transit agencies to design more agile and responsive services at lower operating costs. This study designs and evaluates a semi-on-demand h…
Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction
Dominik Rößle, Jeremias Gerner, Klaus Bogenberger +3
Accurate and comprehensive semantic segmentation of Bird's Eye View (BEV) is essential for ensuring safe and proactive navigation in autonomous driving. Although cooperative percep…