Effect of vehicle type on highway traffic flow: Effects of vehicle type on speed, delay and capacity characteristics of highway traffic flow in the United Kingdom and Saudi Arabia determined by an examination of traffic data.
Highway traffic flow
Traffic signal approaches
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentPostgraduate School of Studies in Civil and Structural Engineering
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AbstractThe t h e s i s c o n s i d e r s t h e e f f e c t s of v e h i c l e type on highway t r a f f i c flow. The e f f e c t s of v e h i c l e type on t h e c a p a c i t y of t r a f f i c s i g n a l approaches are examined by t h e experimental d e t e r m i n a t i o n of passenger c a r u n i t s a t i n t e r s e c t i o n s i n London and West Yorkshire and i n a d d i t i o n s a t u r a t i o n flows and lost t i m e s a r e examined. . Vehicle type e f f e c t s a t roundabout e n t r i e s a r e i n v e s t i g a t e d and t h e r e s u l t s of f i e l d o b s e r v a t i o n s r e p o r t e d . Details a r e given of t h e gap acceptance of varying v e h i c l e t y p e s , t h e e f f e c t of v e h i c l e type on delay and comparisons a r e made with e x i s t i n g recommendat i o n s f o r t h e c a p a c i t y design of roundabout e n t r i e s . Observations of t r a f f i c flow on a r u r a l motorway a r e used to demonstrate t h e e f f e c t of v e h i c l e type on speed and observed v a l u e s a r e f i t t e d t o a normal d i s t r i b u t i o n . Overtaking behaviour is a l s o examined and conclusions drawn of t h e r e l a t i v e e f f e c t on c a p a c i t y of v e h i c l e t y p e . A review is given of t h e e f f e c t s of v e h i c l e type on t h e design and o p e r a t i o n of t h e highway system in Saudi Arabia.
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Performance Modelling and Evaluation of Network On Chip Under Bursty Traffic. Performance evaluation of communication networks using analytical and simulation models in NOCs with Fat tree topology under Bursty Traffic with virtual channels.Awan, Irfan U.; Ibrahim, Hatem Musbah (University of BradfordFaculty of Engineering and Informatics, 2016-02-26)Physical constrains of integrated circuits (commonly called chip) in regards to size and finite number of wires, has made the design of System-on-Chip (SoC) more interesting to study in terms of finding better solutions for the complexity of the chip-interconnections. The SoC has hundreds of Processing Elements (PEs), and a single shared bus can no longer be acceptable due to poor scalability with the system size. Networks on Chip (NoC) have been proposed as a solution to mitigate complex on-chip communication problems for complex SoCs. They consists of computational resources in the form of PE cores and switching nodes which allow PEs to communicate with each other. In the design and development of Networks on Chip, performance modelling and analysis has great theoretical and practical importance. This research is devoted to developing efficient and cost-effective analytical tools for the performance analysis and enhancement of NoCs with m-port n-tree topology under bursty traffic. Recent measurement studies have strongly verified that the traffic generated by many real-world applications in communication networks exhibits bursty and self-similar properties in nature and the message destinations are uniformly distributed. NoC's performance is generally affected by different traffic patterns generated by the processing elements. As the first step in the research, a new analytical model is developed to capture the burstiness and self-similarity characteristics of the traffic within NoCs through the use of Markov Modulated Poisson Process. The performance results of the developed model highlight the importance of accurate traffic modelling in the study and performance evaluation of NoCs. Having developed an efficient analytical tool to capture the traffic behaviour with a higher accuracy, in the next step, the research focuses on the effect of topology on the performance of NoCs. Many important challenges still remain as vulnerabilities within the design of NoCs with topology being the most important. Therefore a new analytical model is developed to investigate the performance of NoCs with the m-port n-tree topology under bursty traffic. Even though it is broadly proved in practice that fat-tree topology and its varieties result in lower latency, higher throughput and bandwidth, still most studies on NoCs adopt Mesh, Torus and Spidergon topologies. The results gained from the developed model and advanced simulation experiments significantly show the effect of fat-tree topology in reducing latency and increasing the throughput of NoCs. In order to obtain deeper understanding of NoCs performance attributes and for further improvement, in the final stage of the research, the developed analytical model was extended to consider the use of virtual channels within the architecture of NoCs. Extensive simulation experiments were carried out which show satisfactory improvements in the throughput of NoCs with fat-tree topology and VCs under bursty traffic. The analytical results and those obtained from extensive simulation experiments have shown a good degree of accuracy for predicting the network performance under different design alternatives and various traffic conditions.
Intelligent Real-Time Decision Support Systems for Road Traffic Management. Multi-agent based Fuzzy Neural Networks with a GA learning approach in managing control actions of road traffic centres.Dahal, Keshav P.; Hossain, M. Alamgir; Almejalli, Khaled A. (University of BradfordDepartment of Computing, 2010-03-16)The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.
Traffic and performance evaluation for optical networks. An Investigation into Modelling and Characterisation of Traffic Flows and Performance Analysis and Engineering for Optical Network Architectures.Kouvatsos, Demetres D.; Mouchos, Charalampos (University of BradfordInformatics Research Institute, 2010-03-16)The convergence of multiservice heterogeneous networks and ever increasing Internet applications, like peer to peer networking and the increased number of users and services, demand a more efficient bandwidth allocation in optical networks. In this context, new architectures and protocols are needed in conjuction with cost effective quantitative methodologies in order to provide an insight into the performance aspects of the next and future generation Internets. This thesis reports an investigation, based on efficient simulation methodologies, in order to assess existing high performance algorithms and to propose new ones. The analysis of the traffic characteristics of an OC-192 link (9953.28 Mbps) is initially conducted, a requirement due to the discovery of self-similar long-range dependent properties in network traffic, and the suitability of the GE distribution for modelling interarrival times of bursty traffic in short time scales is presented. Consequently, using a heuristic approach, the self-similar properties of the GE/G/¿ are being presented, providing a method to generate self-similar traffic that takes into consideration burstiness in small time scales. A description of the state of the art in optical networking providing a deeper insight into the current technologies, protocols and architectures in the field, which creates the motivation for more research into the promising switching technique of ¿Optical Burst Switching¿ (OBS). An investigation into the performance impact of various burst assembly strategies on an OBS edge node¿s mean buffer length is conducted. Realistic traffic characteristics are considered based on the analysis of the OC-192 backbone traffic traces. In addition the effect of burstiness in the small time scales on mean assembly time and burst size distribution is investigated. A new Dynamic OBS Offset Allocation Protocol is devised and favourable comparisons are carried out between the proposed OBS protocol and the Just Enough Time (JET) protocol, in terms of mean queue length, blocking and throughput. Finally the research focuses on simulation methodologies employed throughout the thesis using the Graphics Processing Unit (GPU) on a commercial NVidia GeForce 8800 GTX, which was initially designed for gaming computers. Parallel generators of Optical Bursts are implemented and simulated in ¿Compute Unified Device Architecture¿ (CUDA) and compared with simulations run on general-purpose CPU proving the GPU to be a cost-effective platform which can significantly speed-up calculations in order to make simulations of more complex and demanding networks easier to develop.