Integrated Signal Control and Route Guidance based on Back-pressure Principles

AbstractTraffic signal control and route guidance are the oldest and most applied dynamic traffic management measures. Most of the time they operate in a local mode, although there is trend toward network-wide traffic management. For traffic signal control already several network systems existed, but so far the integration with route guidance is lacking. In this paper we describe a new strategy to integrate traffic signal control and route guidance, based on the principles of back-pressure control. The algorithms developed are tested in a theoretical network and it was shown that traffic signal control based on back-pressure control performs well. Using back-pressure for route guidance required some assumptions which are open for debate. The results show that the average density is not such a good measure for route pressure and that travel time as a pressure variable performs better. A combination of factors of pressure based on density and travel time seems to be the best choice. Using back-pressure for both signal control and route guidance gave promising results, although the differences with optimized local control were small. Future research is recommended on the fine-tuning of the back-pressure traffic signal model, and on further integration and coordination of the control strategies. On the part of route guidance, finding representative route pressure values and making the model applicable of larger networks requires more research

Vehicle Specific Behaviour in Macroscopic Traffic Modelling through Stochastic Advection Invariant

AbstractIn this contribution a new model to include stochastic vehicle specific behaviour and interaction in traffic flow modelling is presented. The First Order Model with Stochastic Advection (FOMSA) is presented as a first order macroscopic kinematic wave model in a platoon-based Lagrangian coordinate system. The use of Lagrangian coordinates allows characteristics of specific vehicles or vehicle-groups to propagate along with the traffic flow using a vehicle specific invariant. The invariant reflects how vehicle or platoon specific characteristics propagate with the vehicles and influence the local behaviour of a vehicle or platoon on a macroscopic level and in interaction with other surrounding vehicles. It represents a local vehicle specific adjustment to the critical density and makes use of two parameters: a stochastic boundary parameter and a transition parameter. These parameters indicate the extent of differences between vehicles or platoons. A case study is also presented in which a demonstration of the model is given and the face validity and sensitivity of the parameters are shown. Previously, similar approaches have made use of second order model descriptions. The formulation of this model as a first order model makes use of the advantages of first order models and also applies the improved accuracy of Lagrangian coordinates over the Eulerian coordinate system in time-stepping

A Software Prototype for Isolated Ramp-Metering

Part of Deliverable 7b, DRIVE-I project CHRISTIANETransport and Plannin

Simulatieprogramma's voor autosnelwegen en stedelijke netwerken

Transport and Plannin

Effects of anticipatory control with multiple user classes

In this paper the integrated traffic control and traffic assignment problem is studied. This problem can be considered as a non-cooperative game in which the traffic authority, that controls the traffic signals, and the road users are the players, who use their own strategy and seek their own optimum. The game theoretical formulation leads to several different control strategies in which users’ reactions to traffic control decisions are taken into account. Users’ reactions can be the choice of route, departure time or even mode, but here only route choice is considered. In this paper some of these control strategies for traffic signal control are described: Webster control, Smith’s P , Anticipatory Control and System Optimum Control. The first two control strategies are well known and described in the literature. The anticipatory control strategy can be formulated as a bi-level optimisation problem and this problem is solved using genetic algorithms. Also the system optimum solution can be found using genetic algorithms, simultaneously optimising route flows and green times. In the paper the assignment method, together with the traffic model, is formulated. In the assignment several user classes, each with its own perception of route costs, are defined and taken into account. For several simple example networks the traffic control methods are tested and it is shown that taking route choice into account is beneficial to the network performance. Further research will focus on the improvement of the traffic model used in the control optimisation, realistic networks and the problem of departure time choice

Toedelings- en simulatieprogramma's voor autosnelwegen en netwerken

Transport and Plannin

Cooperative Route Guidance - A Simulation Study for Stockholm

Transport and Plannin

Groen, geel en rood. Verkeerslichtenregelingen in Nederland

Transport and Plannin

Analyse van de effecten van doseren in het Beneluxplein met behulp van FLEXSYT-II-

Transport and Plannin

The SCOOT system in the City of Nijmegen

Transport and Plannin