Urban Traffic Signal Control Research Articles

Study of Self-Organizing Control of Traffic Signals in an Urban Network Based on Cellular Automata

Aiming at the problems of known traffic signal control methods, such as heavy system and huge computation, this paper presents a macroscopic two-dimensional cellular automata (CA) model of an urban traffic signal control system, in which each intersection is regarded as a cell and the flow pressure is treated as the state. The hierarchical control architecture of traffic signal is built. Off the support of the upper level (traffic control center), the lower level (intersection controllers) can implement self-organizing control of traffic signal. The signal decision at an intersection is based on the thought of "perception-decision." We establish the simple state perception rule of typical intersection. By means of the computer simulation, the application of CA in signal self-organizing control is proved effective in urban traffic.

ACTAM: Cooperative Multi-Agent System Architecture for Urban Traffic Signal Control

SUMMARY The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffi cs ignal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffi cs ignal control strategy. Consequently, traffic congestion in urban areas can be

Modelling the provision of transport with planned or market‐determined public transport services

AbstractImplications of the difference between planned and market‐determined public transport services for the modelling of the transport system and its use are examined. In the former case, the task for government seeking to optimise performance of the transport system has a standard bi‐level form, but in the latter case, the lower‐level problem in the bi‐level formulation is to determine mutually consistent solutions to a pair of optimisation problems. The relevance of the mutually consistent solution in this context is contrasted with its sometimes misleading role in the context of optimisation of urban traffic signal control.

Autonomous Agents for Traffic Simulation and Control

The development of an infrastructure for multiple autonomous agents, with an application to urban traffic signal control, is described. The agent-based infrastructure, Cybele, allows for distributed computing, interagent communication, agent migration, and computational resource allocation. The agents that are used to solve the traffic signal control problem are known collectively as DAARTS (Decentralized Adaptive Agents for contRol of Traffic Signals). DAARTS adopts a hierarchical multiagent-based architecture in which the lowest level (intersection agents) involves individual intersection-traffic dynamics and phase selection based on “local” information, while higher levels take into account the supervisory (network-level) dynamics. The controller design is based on a receding-horizon model predictive control approach. Coordination between intersections is achieved in a decentralized manner at the lowest level. The agents are integrated into a simulation test bed with the microsimulator CORSIM, using the DAARTS simulation tool kit. This kit enables communications between the CORSIM real-time extension, the communications management functions of Cybele, and the traffic control agents. The control process is truly distributed, and each of these components can reside on a different computer. Descriptions of all of the software components are given, and the control algorithm is discussed in detail. Some encouraging results from the simulation of a small network are included. Ongoing and future research activities are discussed.

LRT PRIORITY WITHIN THE SCATS ENVIRONMENT IN DUBLIN: A TRAFFIC FLOW SIMULATION STUDY.

This paper focuses on the feasability of operating a Light Rail Transit (LRT) priority system within the environment of an existing Urban Traffic Signal Control System (UTC) in Dublin. The city uses the Australian UTC-System SCATS (Sydney Co-ordinated Adaptive Traffic System). So far no LRT is running in Dublin yet, but the objective of the study was to establish the degree of LRT priority to be achieved within the existing SCATS UTC. The study was carried out using the microscopic traffic simulation model VISSIM. The simulations clearly show that LRT priority is possible within SCATS on a tactical (local) level at each controller.

Motion - A New On-Line Model for Urban Traffic Signal Control

The modular on-line model MOTION is a new approach to urban traffic signal control. It consists of a network and a local level and builds on enhanced dynamic traffic state estimation. Special consideration is given to the priorisation of public transport, which may be treated by different intervention-modes. MOTION provides possibilities for the interaction with integrated urban management systems. It is developed with support of the European Union and will be implemented in 1994 for the first time.