18 citations · 61 across the 13 of their papers we have counts for
14 papers
Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Control
Max T. M. Ng, Roman Engelhardt, Florian Dandl +2
This paper develops a semi-on-demand transit feeder service using shared autonomous vehicles (SAVs) and zonal dispatching control based on reinforcement learning (RL). This service…
Machine Learning Surrogates for Optimizing Transportation Policies with Agent-Based Models
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…
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…
Effects of Dynamic and Stochastic Travel Times on the Operation of Mobility-on-Demand Services
Fynn Wolf, Roman Engelhardt, Yunfei Zhang +2
Mobility-on-Demand (MoD) services have been an active research topic in recent years. Many studies focused on developing control algorithms to supply efficient services. To cope wi…
Predictive Vehicle Repositioning for On-Demand Ride-Pooling Services
Roman Engelhardt, Hani S. Mahmassani, Klaus Bogenberger
On-Demand Ride-Pooling services have the potential to increase traffic efficiency compared to private vehicle trips by decreasing parking space needed and increasing vehicle occupa…
Redesigning Large-Scale Multimodal Transit Networks with Shared Autonomous Mobility Services
Max T. M. Ng, Hani S. Mahmassani, Ömer Verbas +2
This study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination m…
Simulating Ride-Pooling Services with Pre-Booking and On-Demand Customers
Roman Engelhardt, Florian Dandl, Klaus Bogenberger
If private vehicle trips can be replaced, ride-pooling services can decrease parking space needed by higher vehicle utilization and increase traffic efficiency by increasing vehicl…
FleetPy: A Modular Open-Source Simulation Tool for Mobility On-Demand Services
Roman Engelhardt, Florian Dandl, Arslan-Ali Syed +4
The market share of mobility on-demand (MoD) services strongly increased in recent years and is expected to rise even higher once vehicle automation is fully available. These servi…
Integrating Parcel Deliveries into a Ride-Pooling Service -- An Agent-Based Simulation Study
Fabian Fehn, Roman Engelhardt, Florian Dandl +2
This paper examines the integration of freight delivery into the passenger transport of an on-demand ride-pooling service. The goal of this research is to use existing passenger tr…
Competition and Cooperation of Autonomous Ridepooling Services: Game-Based Simulation of a Broker Concept
Roman Engelhardt, Patrick Malcolm, Florian Dandl +1
Autonomous mobility on demand services have the potential to disrupt the future mobility system landscape. Ridepooling services in particular can decrease land consumption and incr…
On the Dynamism of User Rejections in Mobility-on-Demand Systems
Florian Dandl, Roman Engelhardt, Klaus Bogenberger
Mobility-on-demand (MoD) systems, especially ride-hailing systems, have seen tremendous growth in recent years. These systems provide user-centric mobility services, whose users ex…
Regulating Mobility-on-Demand Services: Tri-level Model and Bayesian Optimization Solution Approach
Florian Dandl, Roman Engelhardt, Michael Hyland +3
The goal of this paper is to develop a modeling framework that captures the inter-decision dynamics between mobility service providers (MSPs) and travelers that can be used to opti…
Speed-up Heuristic for an On-Demand Ride-Pooling Algorithm
Roman Engelhardt, Florian Dandl, Klaus Bogenberger
With ongoing developments in digitalization and advances in the field of autonomous driving, on-demand ride pooling is a mobility service with the potential to disrupt the urban mo…