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Optimal Tolling for Multitype Mixed Autonomous Traffic Networks
When selfish users share a road network and minimize their individual tr...
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Optimal Algorithm for Bayesian Incentive-Compatible
We consider a social planner faced with a stream of myopic selfish agent...
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Eco-Routing based on a Data Driven Fuel Consumption Model
A nonparametric fuel consumption model is developed and used for eco-rou...
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Recommending Paths: Follow or Not Follow?
Mobile social network applications constitute an important platform for ...
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M/G/c/c state dependent queuing model for a road traffic system of two sections in tandem
We propose in this article a M/G/c/c state dependent queuing model for r...
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On Socially Optimal Traffic Flow in the Presence of Random Users
Traffic assignment is an integral part of urban city planning. Roads and...
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M/g/c/c state dependent queueing model for road traffic simulation
In this paper, we present a stochastic queuing model for the road traffi...
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Optimal dynamic information provision in traffic routing
We consider a two-road dynamic routing game where the state of one of the roads (the "risky road") is stochastic and may change over time. This generates room for experimentation. A central planner may wish to induce some of the (finite number of atomic) agents to use the risky road even when the expected cost of travel there is high in order to obtain accurate information about the state of the road. Since agents are strategic, we show that in order to generate incentives for experimentation the central planner however needs to limit the number of agents using the risky road when the expected cost of travel on the risky road is low. In particular, because of congestion, too much use of the risky road when the state is favorable would make experimentation no longer incentive compatible. We characterize the optimal incentive compatible recommendation system, first in a two-stage game and then in an infinite-horizon setting. In both cases, this system induces only partial, rather than full, information sharing among the agents (otherwise there would be too much exploitation of the risky road when costs there are low).
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