3 citations · 7 across the 11 of their papers we have counts for
11 papers
Probabilistic Physics-Aware Machine Learning Predictions of Electric Truck Energy Consumption with Field Data
Hannes Nilsson, Rafael Basso, Balázs Kulcsár +1
In this work, we incorporate first principle physics into the construction of data-driven methods by considering a model that accounts for the different sources of energy losses du…
Joint Planning and Scheduling of Modular Vehicles for Passenger-Freight Integration
Wanru Chen, Jiaming Wu, Balázs Kulcsár
This paper proposes a modular vehicle system for passenger-freight integration along a bidirectional transit corridor. The system uses homogeneous units that can be coupled into ve…
Two-Stage Learned Decomposition for Scalable Routing on Multigraphs
Filip Rydin, Morteza Haghir Chehreghani, Balázs Kulcsár
Most neural methods for Vehicle Routing Problems (VRPs) are limited to Euclidean settings or simple graphs. In this work, we instead consider multigraphs, where parallel edges repr…
GREAT-EER: Graph Edge Attention Network for Emergency Evacuation Responses
Attila Lischka, Balázs Kulcsár
Emergency situations that require the evacuation of urban areas can arise from man-made causes (e.g., terrorist attacks or industrial accidents) or natural disasters, the latter be…
Learning to Dial-a-Ride: A Deep Graph Reinforcement Learning Approach to the Electric Dial-a-Ride Problem
Sten Elling Tingstad Jacobsen, Attila Lischka, Balázs Kulcsár +1
Urban mobility systems are transitioning toward electric, on-demand services, creating operational challenges for fleet management under energy and service-quality constraints. The…
Combined Stochastic and Robust Optimization for Electric Autonomous Mobility-on-Demand with Nested Benders Decomposition
Sten Elling Tingstad Jacobsen, Balázs Kulcsár, Anders Lindman
The electrification and automation of mobility are reshaping how cities operate on-demand transport systems. Managing Electric Autonomous Mobility-on-Demand (EAMoD) fleets effectiv…
Collaborative Charging Scheduling via Balanced Bounding Box Methods
Fangting Zhou, Balazs Kulcsar, Jiaming Wu
Electric mobility faces several challenges, most notably the high cost of infrastructure development and the underutilization of charging stations. The concept of shared charging o…
Robust Position Controller for Steering Systems
Tushar Chugh, Fredrik Bruzelius, Balázs Kulcsár
This paper presents a robust position controller for electric power assisted steering and steer-by-wire force-feedback systems. A position controller is required in steering system…
GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs
Attila Lischka, Filip Rydin, Jiaming Wu +2
Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are becoming increasingly important.…
Less Is More -- On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP
Attila Lischka, Jiaming Wu, Rafael Basso +2
Most of the recent studies tackling routing problems like the Traveling Salesman Problem (TSP) with machine learning use a transformer or Graph Neural Network (GNN) based encoder a…
Integrated Charging Scheduling and Operational Control for an Electric Bus Network
Rémi Lacombe, Nikolce Murgovski, Sébastien Gros +1
The last few years have seen the massive deployment of electric buses in many existing transit networks. However, the planning and operation of an electric bus system differ from t…