Distributed Control of Dynamic Flows in Traffic Networks
(2017)Department of Automatic Control
 Abstract
 In today’s society, traffic congestion is a major problem in several aspects. Apart from the obvious problem that people are losing valuable time due to the resulting delays, it also has negative impact on as well the economy as the local and global environment. With the development of sensors and navigation support, it has now become possible and thus of interest to study optimal routing of vehicles in a traffic network, in order to reduce the congestionrelated problems.
In this master’s thesis, a distributed algorithm for solution of optimal dynamic traffic flow control problems is derived, implemented and tested. Traffic networks are modelled with the cell transmission model (CTM), and the solution algorithm is based on a... (More)  In today’s society, traffic congestion is a major problem in several aspects. Apart from the obvious problem that people are losing valuable time due to the resulting delays, it also has negative impact on as well the economy as the local and global environment. With the development of sensors and navigation support, it has now become possible and thus of interest to study optimal routing of vehicles in a traffic network, in order to reduce the congestionrelated problems.
In this master’s thesis, a distributed algorithm for solution of optimal dynamic traffic flow control problems is derived, implemented and tested. Traffic networks are modelled with the cell transmission model (CTM), and the solution algorithm is based on a generalization of the alternating direction method of multipliers (ADMM).
The algorithm is tested for one simple and one more complicated traffic network. The tests include both cases with timevarying external inflow of traffic as well as cases where the flow capacity of a specific road segment is varied with time, in order to simulate temporary traffic incidents.
The tests show that if the cost function is chosen as the sum of squares of the traffic volumes at the cells (road segments) of the network, the algorithm converges to the optimal solution if a specific parameter (the penalty parameter, or step length) is chosen sufficiently small.
The report starts with a description and examples from the simpler case of static traffic flow optimization. It also contains a summary of the concepts used from optimization theory. After this, the approach for dynamic traffic flow modelling and optimization is described. Finally, a description and derivation of the algorithm is provided, after which the implementation is tested for different cases involving the two different traffic networks. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/8924007
 author
 Rosdahl, Christian
 supervisor

 Gustav Nilsson ^{LU}
 Giacomo Como ^{LU}
 Pontus Giselsson ^{LU}
 organization
 year
 2017
 type
 H3  Professional qualifications (4 Years  )
 subject
 report number
 TFRT6039
 ISSN
 02805316
 language
 English
 id
 8924007
 date added to LUP
 20170908 13:22:56
 date last changed
 20170908 13:22:56
@misc{8924007, abstract = {{In today’s society, traffic congestion is a major problem in several aspects. Apart from the obvious problem that people are losing valuable time due to the resulting delays, it also has negative impact on as well the economy as the local and global environment. With the development of sensors and navigation support, it has now become possible and thus of interest to study optimal routing of vehicles in a traffic network, in order to reduce the congestionrelated problems. In this master’s thesis, a distributed algorithm for solution of optimal dynamic traffic flow control problems is derived, implemented and tested. Traffic networks are modelled with the cell transmission model (CTM), and the solution algorithm is based on a generalization of the alternating direction method of multipliers (ADMM). The algorithm is tested for one simple and one more complicated traffic network. The tests include both cases with timevarying external inflow of traffic as well as cases where the flow capacity of a specific road segment is varied with time, in order to simulate temporary traffic incidents. The tests show that if the cost function is chosen as the sum of squares of the traffic volumes at the cells (road segments) of the network, the algorithm converges to the optimal solution if a specific parameter (the penalty parameter, or step length) is chosen sufficiently small. The report starts with a description and examples from the simpler case of static traffic flow optimization. It also contains a summary of the concepts used from optimization theory. After this, the approach for dynamic traffic flow modelling and optimization is described. Finally, a description and derivation of the algorithm is provided, after which the implementation is tested for different cases involving the two different traffic networks.}}, author = {{Rosdahl, Christian}}, issn = {{02805316}}, language = {{eng}}, note = {{Student Paper}}, title = {{Distributed Control of Dynamic Flows in Traffic Networks}}, year = {{2017}}, }