88 citations · 207 across the 31 of their papers we have counts for
34 papers
Synergizing Drone Delivery Order Pooling and Road Network Monitoring through Monitoring-Task Orderization
Yulong Hu, Meng Xu, Sen Li +1
This paper investigates the real-time dispatch of a shared drone fleet for on-demand food delivery and urban road network monitoring. We consider a courier-drone collaborative sett…
Strategic Dispatching Equilibrium under Competition in Multi-Regional Ride-Hailing Markets
Ran Chen, Nikolas Geroliminis
This paper studies competition between ride-hailing companies in a multi-regional market through a static non-cooperative game, in which each company allocates its fleet across reg…
SkyDrive: Learning to Drive in a New City from Aerial Traffic Monitoring
Weijiang Xiong, Lan Feng, Alexandre Alahi +1
Autonomous driving has made remarkable progress through imitation learning with massive human demonstration data. However, a trained planner often degrades severely when applied to…
Cooperative Detour Planning for Dual-Task Drone Fleets
Pengbo Zhu, Meng Xu, Andreas A. Malikopoulos +1
As Urban air mobility scales, commercial drone fleets offer a compelling, yet underexplored opportunity to function as mobile sensor networks for real-time urban traffic monitoring…
Unveiling Stochasticity: Universal Multi-modal Probabilistic Modeling for Traffic Forecasting
Weijiang Xiong, Robert Fonod, Nikolas Geroliminis
Traffic forecasting is a challenging spatio-temporal modeling task and a critical component of urban transportation management. Current studies mainly focus on deterministic predic…
Resource-Splitting Games with Tullock-Based Lossy Contests
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
This paper introduces a novel class of multi-stage resource allocation games that model real-world scenarios in which profitability depends on the balance between supply and demand…
En Route Path-planning for Partially Occupied Vehicles in Ride-pooling Systems
Pengbo Zhu, Giancarlo Ferrari-Trecate, Nikolas Geroliminis
Ride-pooling services, such as UberPool and Lyft Shared Saver, enable a single vehicle to serve multiple customers within one shared trip. Efficient path-planning algorithms are cr…
No-Regret Learning in Stackelberg Games with an Application to Electric Ride-Hailing
Anna Maddux, Marko Maljkovic, Nikolas Geroliminis +1
We consider the problem of efficiently learning to play single-leader multi-follower Stackelberg games when the leader lacks knowledge of the lower-level game. Such games arise in…
On Learning-Based Traffic Monitoring With a Swarm of Drones
Marko Maljkovic, Nikolas Geroliminis
Efficient traffic monitoring is crucial for managing urban transportation networks, especially under congested and dynamically changing traffic conditions. Drones offer a scalable…
Universality in multispecies traffic
Georg Anagnostopoulos, Nikolas Geroliminis
Understanding the nature of traffic heterogeneity is of major importance, given the widespread adoption of micromobility in cities. Based on massive field data and a nonequilibrium…
Multi-Source Urban Traffic Flow Forecasting with Drone and Loop Detector Data
Weijiang Xiong, Robert Fonod, Alexandre Alahi +1
Traffic forecasting is a fundamental task in transportation research, however the scope of current research has mainly focused on a single data modality of loop detectors. Recently…
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
Robert Fonod, Haechan Cho, Hwasoo Yeo +1
This paper presents a framework for extracting georeferenced vehicle trajectories from high-altitude drone imagery, addressing key challenges in urban traffic monitoring and the li…
Receding-Horizon Games with Tullock-Based Profit Functions for Electric Ride-Hailing Markets
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
This paper proposes a receding-horizon, game-theoretic charging planning mechanism for electric ride-hailing markets. As the demand for ride-hailing services continues to surge and…
Hierarchical Control for Vehicle Repositioning in Autonomous Mobility on Demand Systems
Pengbo Zhu, Giancarlo Ferrari-Trecate, Nikolas Geroliminis
Balancing passenger demand and vehicle availability is crucial for ensuring the sustainability and effectiveness of urban transportation systems. To address this challenge, we prop…
Deep Learning Methods for Adjusting Global MFD Speed Estimations to Local Link Configurations
Zhixiong Jin, Dimitrios Tsitsokas, Nikolas Geroliminis +1
In large-scale traffic optimization, models based on Macroscopic Fundamental Diagram (MFD) are recognized for their efficiency in broad network analyses. However, they fail to refl…
A Blotto Game Approach to Ride-hailing Markets with Electric Vehicles
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
When a centrally operated ride-hailing company considers to enter a market already served by another company, it has to make a strategic decision about how to distribute its fleet…
Macroscopic pricing schemes for the utilization of pool ride-hailing vehicles in bus lanes
Lynn Fayed, Gustav Nilsson, Nikolas Geroliminis
With the increasing popularity of ride-hailing services, new modes of transportation are having a significant impact on the overall performance of transportation networks. As a res…
On decentralized computation of the leader's strategy in bi-level games
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
Motivated by the omnipresence of hierarchical structures in many real-world applications, this study delves into the intricate realm of bi-level games, with a specific focus on exp…
A Coverage Control-based Idle Vehicle Rebalancing Approach for Autonomous Mobility-on-Demand Systems
Pengbo Zhu, Isik Ilber Sirmatel, Giancarlo Ferrari-Trecate +1
As an emerging mode of urban transportation, Autonomous Mobility-on-Demand (AMoD) systems show the potential in improving mobility in cities through timely and door-to-door service…
A Dynamic Macroscopic Framework for Pricing of Ride-hailing Services with an Optional Bus Lane Access for Pool Vehicles
Lynn Fayed, Gustav Nilsson, Nikolas Geroliminis
On-demand trip sharing is an efficient solution to mitigate the negative impact e-hailing has on congestion. It motivates platform operators to reduce their fleet size, and serves…
Learning How to Price Charging in Electric Ride-Hailing Markets
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
With the electrification of ride-hailing fleets, there will be a need to incentivize where and when the ride-hailing vehicles should charge. In this work, we assume that a central…
On Finding the Leader's Strategy in Quadratic Aggregative Stackelberg Pricing Games
Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis
This paper analyzes a class of Stackelberg games where different actors compete for shared resources and a central authority tries to balance the demand through a pricing mechanism…
A dynamic multi-region MFD model for ride-sourcing with ridesplitting
Caio Vitor Beojone, Nikolas Geroliminis
Dynamic network-level models directly addressing ride-sourcing services can support the development of efficient strategies for both congestion alleviation and promotion of more su…
A ride time-oriented scheduling algorithm for dial-a-ride problems
Claudia Bongiovanni, Nikolas Geroliminis, Mor Kaspi
This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehi…