Related papers: Multi-class within-day dynamic traffic equilibrium…
This article studies the value of information in route choice decisions when a fraction of players have access to high accuracy information about traffic incidents relative to others. To model such environments, we introduce a Bayesian…
Routing strategies for traffics and vehicles have been historically studied. However, in the absence of considering drivers' preferences, current route planning algorithms are developed under ideal situations where all drivers are expected…
Data-driven predictions are often perceived as inaccurate in hindsight due to behavioral responses. In this study, we explore the role of interface design choices in shaping individuals' decision-making processes in response to predictions…
We study routing games in which travelers optimize over routes that are remembered or surfaced, rather than over a fixed exogenous action set. The paper develops a tractable design theory for endogenous recall and then connects it back to…
Road congestion induces significant costs across the world, and road network disturbances, such as traffic accidents, can cause highly congested traffic patterns. If a planner had control over the routing of all vehicles in the network,…
The actions of an autonomous vehicle on the road affect and are affected by those of other drivers, whether overtaking, negotiating a merge, or avoiding an accident. This mutual dependence, best captured by dynamic game theory, creates a…
Optimizing network throughput in real-world dynamic systems is critical, especially for diverse and delay-sensitive multimedia data types such as VoIP and video streaming. Traditional routing protocols, which rely on static metrics and…
We develop a Bayesian model for decision-making under time pressure with endogenous information acquisition. In our model, the decision maker decides when to observe (costly) information by sampling an underlying continuous-time stochastic…
This paper presents an interactive bathtub model for describing the traffic dynamics of ride-sourcing vehicles including non-shared taxis and ride-pooling cars. A city with a network of undifferentiated streets and solely served by…
We present multimodal DTM, a new model for multimodal journey planning in public (schedule-based) transport networks. Multimodal DTM constitutes an extension of the dynamic timetable model (DTM), developed originally for unimodal journey…
We develop a dynamic multi-agent model of an interbank payment system where banks choose their level of available funds on the basis of private payoff maximisation. The model consists of the repetition of a simultaneous move stage game with…
Traffic simulation, complementing real-world data with a long-tail distribution, allows for effective evaluation and enhancement of the ability of autonomous vehicles to handle accident-prone scenarios. Simulating such safety-critical…
This paper studies the traffic monitoring problem in a road network using a team of aerial robots. The problem is challenging due to two main reasons. First, the traffic events are stochastic, both temporally and spatially. Second, the…
This paper introduces a new macroscopic perspective for simulating transportation networks. The idea is to look at the network as connected nodes. Each node sends an information package to its neighbors. Basically, the information package…
The evolution of existing transportation systems,mainly driven by urbanization and increased availability of mobility options, such as private, profit-maximizing ride-hailing companies, calls for tools to reason about their design and…
We study an information design problem in transportation networks, in the presence of a random state that affects the travel times on the links. An omniscient system planner -- aiming at reducing congestion -- observes the network state…
To improve the routing decisions of individual drivers and the management policies designed by traffic operators, one needs reliable estimates of travel time distributions. Since congestion caused by both recurrent patterns (e.g., rush…
Spurred by the growth of transportation network companies and increasing data capabilities, vehicle routing and ride-matching algorithms can improve the efficiency of private transportation services. However, existing routing solutions do…
Balancing traffic flow by influencing drivers' route choices to alleviate congestion is becoming increasingly more appealing in urban traffic planning. Here, we introduce a discrete dynamical model comprising users who make their own…
Stochastic effects significantly influence the dynamics of traffic flows. Many dynamic traffic assignment (DTA) models attempt to capture these effects by prescribing a specific ratio that determines how flow splits across different routes…