9 citations · 15 across the 13 of their papers we have counts for
13 papers
Effects of the Plan Vélo I and II on vehicular flow in Paris -- An Empirical Analysis
Elena Natterer, Allister Loder, Klaus Bogenberger
In recent years, Paris, France, transformed its transportation infrastructure, marked by a notable reallocation of space away from cars to active modes of transportation. Key initi…
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…
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…
Temporal Enhanced Floating Car Observers
Jeremias Gerner, Klaus Bogenberger, Stefanie Schmidtner
Floating Car Observers (FCOs) are an innovative method to collect traffic data by deploying sensor-equipped vehicles to detect and locate other vehicles. We demonstrate that even a…
Investigating Lane-Free Traffic with a Dynamic Driving Simulator
Maya Sekeran, Arslan Ali Syed, Johannes Lindner +2
Lane-free traffic (LFT) is a new traffic system that relies on connected and automated vehicles (CAV) to increase road capacity and utilization by removing traditional lane marking…
Data-driven Spatio-Temporal Scaling of Travel Times for AMoD Simulations
Arslan Ali Syed, Yunfei Zhang, Klaus Bogenberger
With the widespread adoption of mobility-on-demand (MoD) services and the advancements in autonomous vehicle (AV) technology, the research interest into the AVs based MoD (AMoD) se…