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Mitigating flash crowd effect using connected vehicle technology

delete2015-10-01
delete12
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OA
AI
A
Agata Grzybek
G
Grégoire Danoy
P
Pascal Bouvry
M
Marcin Seredynski *
DOI:10.1016/j.vehcom.2015.10.002delete
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Abstract

Abstract

En 中文
A Flash Crowd Effect (FCE) occurs when in the case of non-recurring congestion a large portion of drivers follows similar re-routing advice. Consequently, congestion is transferred from one road to another. Coping with the FCE is challenging, especially if the congestion results from a temporary loss of capacity (e.g. due to a traffic incident). The existing route guidance systems do not address FCE, as they either do not consider the effects of guidance on the rest of the road network, or predict link travel times based on the number of vehicles travelling on the link, which in the case of the loss of capacity is unreliable. We demonstrate that the FCE can be addressed in a distributed way with Vehicle-to-Vehicle (V2V) communication provided by Connected Vehicle (CV) technology. The proposed in-vehicle TrafficEQ system provides vehicles with mixed route guidance strategy-i.e. a route is autonomously chosen by the vehicle with a probability that is inversely proportional to the latest reported travel time on the route. Real-time travel time information is crowd-sourced by TrafficEQ users. Using realistic simulations of incident-related capacity drops on a classic two-route highway example and a realistic urban road network, we demonstrate that TrafficEQ can address the FCE by reducing travel time oscillations among the alternative routes. The system's drawbacks-in particular the occasional necessity of providing incentives to follow the guidance-are discussed. (C) 2015 Elsevier Inc. All rights reserved.
Keywords:
Intelligent Transportation Systems (ITS)
Traffic information
Route guidance
Connected vehicle technology
Flash crowd effect
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Journal

Vehicular Communications cover
Vehicular Communications
IF:
6.5
Papers:
801
Citations:
3.2K

Organization

U
university of luxembourg
Scholars:
5.2K
Papers: 4.8K
Citations: 4
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