2350
Hayward Street
Ann Arbor, MI 48109
United States
University of Michigan, Ann Arbor
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Travel behavior, Large language model, Behavioral alignment, Demand forecasting
On-Demand Delivery, Sharing Economy, Multi-sided Markets, Continuum Approximation
Network equilibrium, end-to-end, neural networks, auto-differentiation
Ride-sourcing, dynamic joint pricing-empty relocation, capacity sizing, queueing, fluid approximation, network of double-ended queues, exponentially fast convergence, exponentially small loss.
ride-sourcing systems, vacant trips, network equilibrium, traffic congestion
ride sourcing, spatial pricing, geometric matching, spatial equilibrium, regulation
Ride sourcing, driver incentive, supply management, welfare effects
ride sourcing, driver incentive, supply management, welfare effects
Network equilibrium, neural-network-based variational inequality, end-to-end learning, and implicit layer
Ride-hailing market, dual sourcing, network equilibrium, supply management
ride-hailing; regulation; commission cap; competition
On-demand service platforms, Team competition, Payment scheme design, Quasi-variational inequality
truck platooning, itinerary planning, concave minimum cost flow, outer approximation, approximation algorithm;
Ride sourcing, driver behavior, incentive effects, supply management
Ride-hailing, fluid model, spatiotemporal characteristics, optimal pricing
automated driving, automated vehicles, vehicle-infrastructure cooperation, infrastructure, digitalization
Automated vehicles, subsidy policy, dynamic Stackelberg games, diffusion of innovations.
Ridesourcing service, regulation, pooling, congestion externality, commission cap, and congestion toll
Ride-sourcing, Driver behavior, Bounded rationality, Behavioral queueing theory, Supply management
Ride-hailing; pooling; bilateral meeting; closed-queue systems
Intersection control; connected and automated vehicles; graph coloring; approximation algorithm; traffic signal control; signal-free control.
Connected automated vehicles, sensor configuration, cooperative sensing, sensing policy
Evacuation, Flood, CTM, Muskingum-Cunge, Benders decomposition
Network equilibrium modeling, empirical observation, inverse optimization, bilevel program
Connected and automated vehicles, participatory traffic control, network efficiency, mean-field control, day-to-day traffic dynamics
Multimodal transportation systems, dynamic departure time choice, generalized mean field games, learning in stochastic games
ride-sourcing market, dual sourcing, contract design, freelancers, contractors
Parking, automated vehicles, cruising-as-substitution-for-parking, congestion, tolling
network equilibrium model, inverse learning, multiconvex optimization, context-dependent
Credit charge-cum-reward scheme, periodic mode usage equilibrium, dynamic model, learning behavior, adaptation behavior
Connected automated vehicles, Cooperative sensing, Vehicular connectivity, Investment policy
Connected and automated vehicles, participatory traffic control, incentive design, economic analysis, cost of agency, bottleneck model
Transportation system modeling, travel behavior, travel demand modeling, agentbased simulation, large language model, transportation planning
Build-operate-transfer road, Asymmetric information, Signaling game, Potential traffic demand, Travel cost elasticity of demand.
Travel demand modeling, Large language model agent, Day-to-day behavior, Automatic calibration, Agent-based simulation
Route Choice, Perturbed Utility, Discrete Choice, Networks, Inverse Estimation
Conditional tabular data generation, deep generative models, diffusion model, travel demand modeling
Markov Perfect Equilibrium, Queuing Systems, Maritime Management
Inverse Learning, Distributional User Equilibrium, Uncertainty Quantification, Robust Congestion Pricing
vehicle platooning, energy savings, driving-effort reduction, auction, truthful $\epsilon-$approximate mechanism
