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Title: Managing traffic at motorway junctions : a ramp metering development using intelligent vehicles
Author: Scarinci, R.
ISNI:       0000 0004 5362 7819
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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Motorways provide an important transport facility for people and goods with social, environmental and economic consequences. The demand for their use continues to increase, leading to more extensive and severe congestion; therefore, finding ways to reduce it is a priority, and Intelligent Transport Systems (ITS) have been identified as a contributor. Intelligent vehicles equipped with in-car communication systems are capable of receiving messages from the infrastructure and communicating with other vehicles. This communication enables the cooperation among them and offers many opportunities for developing a new generation of ITS that is referred to as Cooperative Intelligent Transport Systems. This research presents an innovative control algorithm for managing motorway merges using intelligent vehicles, exploiting the cooperation made possible by communication. This innovative system, called Cooperative Ramp Metering (CoopRM), requires the cooperation of equipped vehicles on the main carriageway in order to create gaps for facilitating the merging of on-ramp vehicles, aiming to reduce congestion at motorway junctions. First, similar management systems are reviewed, and the algorithms are classified based on their characteristics, then similarities, dissimilarities, trends and research gaps are described. Established a state-of-the-art in this research field, the Cooperative Ramp Metering algorithm is defined analytically. Macroscopic traffic flow theory is used in combination with microscopic theory to determine the equations governing the CoopRM control strategy. The accuracy of this formulation is then validated by comparing theoretical against simulation results. Finally, the traffic performance of the CoopRM is evaluated using a stochastic microscopic simulation model, calculating and comparing indexes representative of congestion and disruptions at traffic flow for different scenarios. Results show a substantial reduction in congestion, a decrease of perturbations and a more efficient merging procedure. This study demonstrates how this innovative Cooperative ITS is able to improve the current motorway infrastructure through the use of emerging communication technology.
Supervisor: Heydecker, B. G. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available