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The primary focus of this study is to present a new integrated traffic control model for urban freeways using model-based predictive control (MPC) framework, where the effect of traffic information on drivers' en-route diversion behaviour is explicitly modelled using an adaptive constrained Kalman filtering theory. This captures the effect of traffic information on drivers' real-time en-route diversion behaviour, based on on-line traffic surveillance data. The integrated control task is formulated as a dynamic, non-linear, discrete time optimal control problem with constrained control variables. The network traffic flow process is modelled by a dynamic network traffic flow model, which is deterministic, discrete in time and space, macroscopic and suitable for model-based traffic control. Feedback control is realised by solving the optimisation problem for each control interval over a long future-time horizon. Simulation results for a case study show that the proposed integrated MPC model takes in consideration of the time-dependent traffic characteristics and drivers' actual behaviour and can significantly enhance the traffic efficiency and reduce the cost of traffic system by 17.1-30.0%. [ABSTRACT FROM AUTHOR]

Travel time is considered more useful to users than other travel-related information such as speed. It is mainly estimated by point or interval detection systems. In this study, the authors investigate the deficiency of these systems in estimating travel times when they are used in isolation, and proposed a fusion algorithm that simultaneously utilises data from both point and interval detection systems. The fusion algorithm is based on the traffic flow and k-nearest neighbourhood (k-NN) models. Specifically, the authors precisely define the so-called the time lag issue in interval detection systems. To overcome this problem, they analysed the travel time variation because of variation in traffic states using fused data from point and interval detection systems. The authors show that the travel time obtained from interval detection systems is renewed by considering the travel time variation and their results show that the proposed algorithm satisfactorily predicts the travel time with the mean absolute percentage errors (MAPE). [ABSTRACT FROM AUTHOR]

This study presents a novel concept of an ecological driver assistance system (EDAS) that may play an important role in intelligent transportation systems (ITS) in the near future. The proposed EDAS is designed to measure relevant information of instant vehicle-road-traffic utilising advanced sensing and communication technologies. Using models of vehicle dynamics and traffic flow, it anticipates future situations of the vehicle-road-traffic network, estimates fuel consumption and generates the optimal control input necessary for ecological driving. Once the optimal control input becomes available, it could be used to assist the driver through a suitable human interface. The vehicle control method is developed using model predictive control algorithm with a suitable performance index to ensure safe and fuel-efficient driving. The performance of the EDAS, in terms of speed behaviour and fuel consumption, is evaluated on the microscopic transport simulator AIMSUN NG. Comparative results are graphically illustrated and analysed to signify the prospect of the proposed EDAS in building environmentally friendly ITS. [ABSTRACT FROM AUTHOR]

An urban traffic network of signalised intersections can be suitably modelled as a discrete event system, in which the traffic light alternations are described by means of timed coloured Petri nets (TCPNs). A module of basic traffic TCPN model with a signal timing plan for a day is successfully constructed. The traffic operations are ruled by the control logic of TCPN and an analysis method using place invariant is verified. From the basic TCPN model, some of the complicated traffic signal models will be easily obtained. Moreover, a real-world supervisor of the urban traffic light system is implemented by the new methodology. Finally, an urban traffic light control system with five intersections is realised. Also, the performance of the supervisor of the urban traffic light system can be confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

User-centred design methods were used to understand the key motivators, potential constraints and design requirements associated with an innovative shared-vehicle scheme, offered as an integral component of a wider ‘transport marketplace’. A set of situated user trials were used to assess attitudinal and behavioural responses to a prototype service implemented in northern France. Potential motivators included the perceived benefits of reduced cost, environmental benefit, social contact and the provision of location-based information. The key barriers to adoption included: personal security during vehicle sharing, liability and flexibility in meeting individual transport needs. Contrary to initial indications by participants, ease of use was also a key acceptance criterion. The resulting design recommendations stress the need for maximising service flexibility, addressing perceived barriers and providing clarity regarding operational procedures and protocols. [ABSTRACT FROM AUTHOR]

Efficient road traffic incident management (TIM) in metropolitan areas is crucial for the smooth traffic flow and the mobility and safety of community. TIM requires fast and accurate collection and retrieval of critical data, such as incident conditions and contact information for the intervention crew, public safety organisations and other resources. Access to critical data by traffic control operators can be facilitated through various human–computer interfaces. The judicious introduction of a multimodal interaction paradigm to the user interfaces (UIs) for incident handling in a metropolitan transport management centre is discussed. Two research prototypes supporting speech and gestural interactions have been developed on the basis of the User Centred Design methodology, and their evaluations have been conducted through user studies. The user studies on the prototypes suggest that multimodal UIs (MMUIs) can provide traffic control operators with intuitive, cognitively efficient ways to record traffic incident conditions, facilitate fast retrieval of contact details, and support time-critical incident handling. The research prototypes described herein represent some initial steps for the longer-term deployment of advanced MMUI systems for emergency management. [ABSTRACT FROM AUTHOR]

Although the technology of ‘Intelligent Infrastructure’ systems is kept absolutely at cutting edge, many of the presumptions about the transport problems they are intended to solve are outdated, in particular the relationship between demand and supply of facilities for movement, which is more complex and more volatile than is suggested in the methodologies which have dominated economic analysis. The conjectures in this paper are that, as a result, there could be a dynamic reorientation of the functions of technologies, which, conceived to solve one set of problems, will be progressively adapted to serve functions other than the original intention. The core driver of this process is the analysis of economic (and environmental) efficiency which leads to the replacement of ‘predict and provide’ as a way of meeting the unrestricted demand for travel, to ‘management for quality’ aimed at reducing traffic volumes, enhancing localities, and improving reliability. Three examples are suggested: the technology of real-time information and route advice systems could evolve mainly to serve the policy of charging for road use; technologies intended to allow drivers to maintain high speeds in heavy traffic could be reversed, being used instead for the controlled reduction of speeds; technologies developed to maximise the traffic volumes able to use congested networks can be adapted to give selective improvements to priority classes of road user. The common theme is that technologies originally perceived as providing for an extrapolation of current patterns of demand and current views about the trends underpinning them, will instead be used as active instruments to modify those patterns and trends. This process may be seen as an example of ‘unintended effects’, though not necessarily undesirable ones: if shifts in the transport policy direction are well-founded, the outcome of such a technological transformation might actually be more efficient, rather than less, than the pathway initially envisaged. Thus the way in which advanced information technology will impact on transport can be radically different from what was expected, because of fundamental changes (still uncompleted) in the policy context, which in turn derive from the dynamics of competitive but regulated markets in the context of high external costs. It is suggested that this proposition is a possible, perhaps likely, but not inevitable picture of the future development of transport technologies. [ABSTRACT FROM AUTHOR]

The high cost of congestion caused by incidents such as accidents and other events that reduce the capacity of roads has prompted a growing worldwide interest in developing efficient and effective incident management programs. The success of these programs will depend to a large extent on the development of reliable and efficient automated incident detection (AID) models. These algorithms analyse real-time data collected from traffic detection devices to determine whether an incident has occurred. This paper reviews some of the most widely used AID algorithms and discusses the refinement and further development of an AID model based on fractal dimension analysis. The development of this algorithm was based on the notion that traffic parameters upstream of incidents and bottlenecks show substantial irregular behaviour when compared with downstream conditions. Fractal dimension analysis was used to provide a measure of the irregularity in traffic parameters. A comparative evaluation of the performance of a number of AID algorithms that have been developed from a variety of theoretical foundations is also presented. The results, which were based on the same dataset of 100 field incidents, confirmed the superior performance of the neural network and fractal dimension models over the Comparative or California-type models. [ABSTRACT FROM AUTHOR]

We present a vision of an Intelligent Network in which users dynamically indicate their requests for services and formulate needs in terms of quality of service (QoS) and price. Users can also monitor on-line the extent to which their requests are being satisfied. In turn the services will dynamically try to satisfy the user as best as they can and inform the user of the level at which the requests are being satisfied, and at what cost. The network will provide guidelines and constraints to users and services, to avoid that they impede each others' progress. This intelligent and sensible dialogue between users, services and the network can proceed constantly based on mutual observation, network and user self-observation, and on-line adaptive and locally distributed feedback control which proceeds at the same speed as the traffic flows and events being controlled. We review issues such as network ‘situational awareness’, self-organisation and structure, and relate these concepts to the ongoing research on autonomic communication systems. We relate the search for services in the network to the question of QoS and routing. We examine the need to dynamically protect the networked system from denial of service (DoS) attacks and propose an approch to DoS defence which uses the detection of violations of QoS constraints and the automatic throttling or dropping of traffic to protect critacl nodes. We also discuss how this vision of an Intelligent Network can benefit from techniques that have been experimented in the cognitive packet network test-bed at Imperial College, thanks to ‘smart packets’ and reinforcement learning, which offers routing that is dynamically modified using on-line sensing and monitoring, based on users' QoS needs and overall network objectives. [ABSTRACT FROM AUTHOR]

This paper presents a traffic simulation approach to evaluate the impacts of incident management programs and the provision of real-time travel information in response to incidents. A traffic simulation model of a commuting corridor was used to simulate a large number of incident scenarios and measure their impacts. An incident management strategy that can reduce the duration of an incident blocking all lanes from 30 to 15 min was found to have the potential to provide 17% reduction in travel times. The environmental benefits were also substantial, showing a 22% reduction in fuel consumption rate and 20% reduction in CO2. The provision of real-time travel information was also tested by advising drivers to use an alternative route. The results showed that provision of travel information in the presence of an incident has the potential to reduce travel times by 5%. These impacts were found to be dependent on network features and capacities of diversion routes. It was also found that the proportion of drivers complying with route diversion advice has an influence on the benefits to be obtained from these systems. The best network performance was obtained for driver compliance rates between 50 and 60%. [ABSTRACT FROM AUTHOR]

The potential impact of advances in data mining, data fusion and information management on the efficient exploitation of the transport infrastructure are addressed. It is argued that the energy currently consumed in transport is poorly exploited for a number of reasons that the application of intelligent infrastructure analysis can significantly address: traffic congestion implies reduced fuel efficiency; the average number of people travelling per car is very low; and public/private transport combination options are difficult to plan. Relevant advances in intelligent information systems are reviewed, and a number of scenarios illustrating how these weaknesses might be addressed are presented. For each, the feasibility of the required technology and the timescales for deployment are discussed. [ABSTRACT FROM AUTHOR]

A novel, distributed, cooperative multi-agent approach employing multiple, interacting, autonomous hybrid agents to provide effective signal control for real-time traffic management is presented here. This multi-agent system uses advanced cooperative behaviours to improve individual agents' learning process and adaptability. Each agent cooperates with other agents within its cooperative zone, the size of which changes dynamically according to the changing needs of the agent. The performance of the proposed cooperative ensemble multi-agent system is tested on a large, complex traffic network and compared against two other approaches. For the 6 h extreme scenario with two peaks, the proposed approach reduces the total mean delay by 35.6% when compared to the GLIDE benchmark, while for the 24 h extreme scenario with multiple peaks, the reduction is 75%. The results demonstrate the efficacy of the cooperative multi-agent approach in dealing with the approximated version of an infinite horizon dynamic problem. [ABSTRACT FROM AUTHOR]

We study the effect of inter-vehicle communications and use simple models and simulations to evaluate various scenarios. Both highway systems and urban city driving cases are considered. Adaptive cruise control (ACC) and merging/lane changing scenarios are studied for highway systems. Stop-and-go operation and intersection safety are considered for in-city applications. A simple human driver model is used to represent the reactions of the drivers. A specially developed traffic simulator is utilised to simulate the proposed scenarios for various traffic flows. [ABSTRACT FROM AUTHOR]

Points out that electronic charging technology has matured to the point where it can be used effectively and relatively cheaply on both urban and inter-urban roads in order to combat traffic congestion. Technical options; Microwave DSRC (Dedicated Short-Range Communications); Cameras and the Automatic Number-Plate Recognition (ANPR) system; Satellite-based Global Positioning System; Road pricing. INSET: USEFUL WEB LINKS.