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■ Distributionally Robust Optimization in Congestion Control
Jakub Mareček, Robert Shorten, Jia Yuan Yu, "Distributionally Robust Optimization in Congestion Control", ITS European Congress 2016
The model of Marecek et al. [arXiv:1406.7639, Int. J. Control 88(10), 2015] is extended to consider uncertainty in the response of a driver to an interval provided per route. Specifically, it is suggested that one can optimise over all distributions of a random variable associated with the driver's response with the first two moments fixed, and for each route, over the sub-intervals within the minimum and maximum in a certain number of previous realisations of the travel time per the route.
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■ Pricing Vehicle Sharing with Proximity Information
Mareček, J., Shorten, R., & Yu, J. Y. (2016, March). Pricing vehicle sharing with proximity information. In Big Data and Smart City (ICBDSC), 2016 3rd MEC International Conference on (pp. 1-7). IEEE.
For vehicle sharing schemes, where drop-off positions are not fixed, we propose a pricing scheme, where the price depends in part on the distance between where a vehicle is being dropped off and where the closest shared vehicle is parked. Under certain restrictive assumptions, we show that this pricing leads to a socially optimal spread of the vehicles within a region.
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■ r-Extreme Signalling for Congestion Control
Jakub Mareček , Robert Shorten , Jia Yuan Yu, "r-Extreme Signalling for Congestion Control", International Journal of Control, 2016
In many smart-city applications, congestion arises in part due to the nature of signals received by individuals from a central authority. We study the setting, where a central authority broadcasts an interval per resource, as obtained by taking the minima and maxima of costs observed within a time window of length r, and show that the resulting distribution of agents across resources also converges in distribution, under plausible assumptions about the evolution of the population over time.
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