Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755996
Title: Modelling and optimisation of dynamic motorway traffic
Author: Li, Ying
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
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Abstract:
Ramp metering, variable speed limits, and hard shoulder running control strategies have been used for managing motorway traffic congestion. This thesis presents a modelling and optimisation framework for all these control strategies. The optimal control problems that aim to minimise the travel delay on motorways are formulated based upon a macroscopic cell transmission model with piecewise linear fundamental diagram. With the piecewise linear nature of the traffic model, the optimal control problems are formulated as linear programming (LP) and are solved by the IBM CPLEX solver. The performance of different control strategies are tested on real scenarios on the M25 Motorway in England, where improvements were observed with proper implementation. With considering of the uncertainties in traffic demand and characteristics, this thesis also presents a robust modelling and optimisation framework for dynamic motorway traffic. The proposed robust optimisation aims to minimise both mean and variance of travel delays under a range of uncertain scenarios. The robust optimisation is formulated as a minimax problem and solved by a two stage solution procedure. The performances of the robust ramp metering are illustrated through working examples with traffic data collected from the M25 Motorway. Experiments reveal that the deterministic optimal control would outperform slightly the robust control in terms of minimising average delays, while the robust controller gives a more reliable performance when uncertainty is taken into account. This thesis contributes to the development and validation of dynamic simulation, and deterministic and robust optimisation.
Supervisor: Chow, Andy ; Heydecker, B. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.755996  DOI: Not available
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