The Cost of Environmental Constraints in Traffic Networks: Assessing the Loss of Optimality

in Networks and Spatial Economics (2016)

Increasing numbers of hard environmental constraints are being imposed in urban traffic networks by authorities in an attempt to mitigate pollution caused by traffic. However, it is not trivial for ... [more ▼]

Increasing numbers of hard environmental constraints are being imposed in urban traffic networks by authorities in an attempt to mitigate pollution caused by traffic. However, it is not trivial for authorities to assess the cost of imposing such hard environmental constraints. This leads to difficulties when setting the constraining values as well as implementing effective control measures. For that reason, quantifying the cost of imposing hard environmental constraints for a certain network becomes crucial. This paper first indicates that for a given network, such cost is not only related to the attribution of environmental constraints but also related to the considered control measures. Next, we present an assessment criterion that quantifies the loss of optimality under the control measures considered by introducing the environmental constraints. The criterion can be acquired by solving a bi-level programming problem with/without environmental constraints. A simple case study shows its practicability as well as the differences between this framework and other frameworks integrating the environmental aspects. This proposed framework is widely applicable when assessing the interaction of traffic and its environmental aspects [less ▲]

Iterative optimization for adaptive anticipatory control in urban traffic networks

Scientific Conference (2015, July)

An integrated approach to apdative anticipatory traffic control and parameter estimation

in Proceedings of the MT-ITS Conference (2015, June)

An adaptive flow anticipatory control using daily iterative learning in urban traffic networks

Scientific Conference (2014, June)

Dynamic Origin-Destination Matrix Estimation on Large-Scale Congested Networks Using A Hierarchical Decomposition Scheme

in Journal of Intelligent Transportation Systems (2014), 18(1), 51-66

Despite the ever increasing computing power, dynamic Origin-Destination (OD) estimation in congested networks remains troublesome. In previous research, we have shown that an unbiased estimation requires ... [more ▼]

Despite the ever increasing computing power, dynamic Origin-Destination (OD) estimation in congested networks remains troublesome. In previous research, we have shown that an unbiased estimation requires the calculation of the sensitivity of the link flows to all Origin Destination flows, in order to incorporate the effects of congestion spillback. This is however computationally infeasible for large-scale networks. To overcome this issue, we propose a hierarchical approach for off-line application that decomposes the dynamic OD estimation procedure in space. The main idea is to perform a more accurate dynamic OD estimation only on subareas where there is congestion spillback. The output of this estimation is then used as input for the OD estimation on the whole network. This hierarchical approach solves many practical and theoretical limitations of traditional OD estimation methods. The main advantage is that different OD estimation method can be used for different parts of the network as necessary. This allows applying more advanced and accurate, but more time consuming methods only where necessary. The hierarchical approach is tested on a study network and on a real network. In both cases the proposed methodology performs better than traditional OD estimation approaches, indicating its merit. [less ▲]

Dynamic modeling of VISSIM's critical gap parameter at unsignalized intersections

in Transportation Research Record: Journal of the Transportation Research Board (2014), 2395

Exploiting the relation between Activity Data and Traffic Data within the Dynamic Demand Estimation Problem

Scientific Conference (2014)

An Iterative Learning Approach for Signal Control in Urban Traffic Networks

in Proceedings of IEEE-ITS Conference (2013)

Traffic signal control influences route choice in traffic networks, and may even determine whether a traffic system settles in equilibrium or destabilizes into oscillatory patterns. Ideally, a stable ... [more ▼]

Traffic signal control influences route choice in traffic networks, and may even determine whether a traffic system settles in equilibrium or destabilizes into oscillatory patterns. Ideally, a stable equilibrium flow pattern should result from the interaction between control and route choice on a long-term horizon. This paper proposes an iterative learning approach for designing signal controls able to attract the system to equilibrium in an acceptable convergence speed. The traffic assignment model and combined traffic assignment and control problem are first introduced. An iterative learning control (ILC) based signal control is formulated and a basic model inversion method is analyzed. To deal with the nonlinearity of traffic system, a Newton based ILC algorithm is applied. Test in an example network verifies the effectiveness of the ILC method in achieving stable equilibrium in the traffic system. [less ▲]

Dynamic modeling of VISSIM critical gap parameter at unsignalized intersections

Poster (2013)