Due to the worldwide of petrol prices crises that have been rising inevitably over the past years, any reduction in the transportation cost will benefit most companies. The purpose of this research is to contribute in solving this problem by alleviating some afthis burden. This thesis is about the Split Delivery Vehicle Routing Problem (SDVRP) and some of its variants. The SDVRP is a relaxed version of the classical VRP where customers can be visited more than once. It is also applicab le to problems with customers' demands larger than the vehicle capacity. These types of split routing problems can be found app licable in many real-world logistical problems. The total cost and the number of vehicles required could be reduced by allowing split deliveries. The savings are found to be the most in those problems with customers' demands nearly as large as the vehicle capacity limit. Some constructive heuristics adapted from the savings, the sweep and the insertion methods are first put forward to solve the SDVRP. These sets of solutions are then used in several set covering-based models which are proposed to so lve the problem. Both the heuristics and the set covering-based approaches are tested on two large sets of published data set from the literature with encouraging results. Similarly on the second data set, 12 best solutions are found from the 42 instances with an average deviation of 1.37%. As split deliveries may increase customers' administration cost and inconvenience, some models to cater for this drawback are proposed and their implementations are tested and evaluated against the classical SDVRP for guidance. This thesis is organised as follows: In the first chapter, a brief overview of logistics and distribution management, in particular with respect to vehicle routing, is provided. A brief explanation about the TSP, the VRP and its variants is also presented. Methodologies for solving these kinds of problems are also given. This is then followed by an example to illustrate the benefit of sp lit deliveries in Chapter 2 together with the SDVRP mathematical formulations and a review of the methods used to tackle the SDVRP and its variants. A brief introduction to the two benchmark SDVRP data sets used is given at the end of this chapter. Several constructive heuristics are first implemented in the third chapter. These are adapted from the Savings, the Sweep and the Insertion methods to include split deliveries. These methods are coded in C++ Language and tested on the two SDVRP data sets taken from the literature and their performance is evaluated against the best published resu lts showing encouraging results. In Chapter 4, an existing mathematical programming approach based on the set covering is implemented using ILOO CPLEX Callable Library. This approach uses several sets of routes from the obtained solutions by the constructive heuristics in Chapter 3. New mathematical ILP based models are adapted and a pi lot test is conducted within a limited time to select the most appropriate model and corresponding CPLEX parameters. New best results are discovered by the selected model on the two large data sets. In Chapter 5, the dual information relating to both customers and routes, is obtained by relaxing the selected set covering-based problem as a Linear Programming. The customers' dual information is incorporated in both the classical insertion cost formula and the well-known savings formulae and is proved to be beneficial. Route reduction schemes are then designed to inc lude those promising routes only. At the end of this chapter, a new set of routes is then constructed by combining the new generated routes and those subsets of routes found previously. This set is then used in the selected model where some new best results are obtained. A new variant of the SDVRP is introduced in Chapter 6 where an incentive scheme is incorporated to overcome the inconvenience of those affected customers that have split deliveries. Two new models are then explored and adapted from the previous set covering-based models. Given that no published results exist for these variants, as a guide, those results originated from the classical SDVRP are used for comparison purpose. Our find ings and suggestions for potential future research are highlighted in the final chapter.

This research addresses the topic of knowledge exchange across borders in the field of road transport. Road transport administrations around the world learn from each other by taking part in various forms of knowledge exchanges. From my engagement and experiential learning in this area, I perceive a potential for attaining higher returns of such knowledge investments. The overall purpose of the project is to improve the results of international knowledge exchanges, while the aim is to explore the potential for making improvements in the knowledge exchange process. I have carried out the research mainly within my own organisation and explored the views and experience of participants in exchanges. The project draws on a review of theoretical and operational sources of knowledge and information. In the review, I deal with the research topic in three different contexts: theories and empirical studies, development cooperation, and the professional field. The methodological approach is qualitative and inductive within the paradigm of constructivism. The primary method for data collection is individual semi‐structured interviews with selected exchange participants. The interview data are analysed using thematic analysis. As a means of ensuring quality, the interview findings have been triangulated by focus groups and individual discussions. The validity and the reliability of the research are restricted, since it is context‐bound and small‐scale. However, discussions with professionals abroad indicate that the results apply more generally. The findings show that there are constraining factors throughout the knowledge exchange process that prevent the participants and the organisation from taking full advantage of the exchanges. I have used the findings to construct a holistic, life cycle model that can make knowledge exchanges more effective. My model is unique of its kind and differs from existing models for acquiring, creating, and managing knowledge in organisations in that it is determined by the characteristics of my organisation and by a multinational knowledge exchange environment. In order to prepare the ground for its application, I have promoted the model both in my organisation and in the professional community abroad. The real value of the model can, however, only be demonstrated when it has been used for some time.

This research seeks to investigate how application of Human Factors techniques could be used to improve performance resulting from the use of technical traffic management and SCOOT validation systems. The systems used in both domains have historically been developed without consideration given to the social factors important to their use, designs instead being based solely on technical constraints. In the first stages of the project traffic management is investigated through conduction of a literature review covering the objectives, functions and constraints acting upon Traffic Management Centres (TMCs) in road, rail, maritime and air domains. Congestion management is then considered in urban road TMCs through application of the Event Analysis of Systematic Teamwork (EAST) method based on observational data collected from four TMCs, Bristol, Cardiff, Dorset and Nottingham, in which the tasks, social agents, information and relationships between these elements are considered. The EAST method is then expanded to enable investigation into TMCs’ resilience, providing further knowledge about the domain. The later stages of the project are concerned with SCOOT validation, the process by which adaptively controlled traffic lights using SCOOT are set up to reflect real traffic conditions. The domain, using the current PC SCOOT Urban Traffic Control system, is assessed through Cognitive Work Analysis (CWA) with the findings used to propose areas suitable for development. One of these areas, STOC validation, is then developed further by applying Ecological Interface Design to develop an alternative display addressing limitations with PC SCOOT’s display. This concept display is then evaluated through two empirical experiments examining performance compared to traditional displays and investigating the role of experience within the domain. Finally, by using insights obtained into the STOC validation process an automated STOC selection algorithm is developed which has the potential to redefine how STOC validation is conducted.

Intelligent Transport Systems (ITS) have the potential to increase road-network capacities, reduce congestion and pollution, create shorter and more predictable journey times and significantly improve road-user safety. However, these technologies will also have the ability to track a citizen’s every move, extracting information about their daily lives. This data could range from information about the user’s driving style, to exactly where their vehicle was at any given time in its lifetime, right down to the radio station the driver listens to. It has been argued that privacy invasions caused by ITS will have a damaging effect on society, creating a ‘Big Brother’ or panopticon state. For these fears to be fulfilled, it needs to be the case that future users are not only concerned about the privacy impacts of ITS, but that the ITS will actually cause users to change their travel behaviour. This research examines the results of both a survey of 993 people across four culturally diverse European countries (the UK, Greece, Austria and the Netherlands). The survey primarily seeks to interrogate the factors influencing a future ITS user’s privacy concerns, their stated behavioural intention and their actual privacy behaviour. The results of this research show that privacy concerns could play a significant role in limiting the voluntary uptake rate of the technology. While this may not be critical to the success of all future ITS, future ITS which require high penetration rates to be successful will definitely need to consider the privacy aspects of their system. This research also indicates that when a future ITS user is required to decide whether to disclose their personal information, they will be influenced significantly more by their demographics and the potential risks associated with disclosing the information than the rewards that are on offer. This means that ITS developers should attempt to use less sensitive data where possible, consider using a more trusted organisation to collect and store the required information and also consider the user’s perception on how secure a transfer method is.

This thesis presents an investigation into the hybridisation of metaheuristic approaches to tackle the classical vehicle routing problem (VRP) and its adaptation to other useful and practical routing problems including the cumulative capacitated VRP (CCVRP) and the dynamic VRP (DVRP). Due to the limited success of the exact methods in handling large size instances, this research investigates the design and analysis of metaheuristic algorithms that can produce near optimal solutions within a reasonable amount of time to solve this class of routing problems. To achieve this goal, we propose an effective and novel hybridisation of variable neighbourhood search (VNS) and large neighbourhood search (LNS), leading to a powerful adaptive VNS (AVNS). Different from most of the literature for AVNS and adaptive LNS where learning is usually incorporated in the shaking step for the former and in the selection of the removal strategies for the latter, the adaptive aspect presented here is integrated in the local search of our AVNS. In short, a set of highly successful local searches is selected based on the intelligent selection mechanism which we introduced. In addition, this work also focuses on the development of some general enhancement-based techniques which include the design of neighbourhood reduction scheme, efficient data structures and a guided penalized objective function. The VRP is a hard combinatorial optimisation problem which was first established more than fifty years ago. Since then, this problem is extensively studied because of its high practicability in transportation logistics. Given the rising price of global oil, reducing the transportation cost provides a great impact in stabilizing the global economic system and adds a competitive advantage. The classical VRP focuses on this line of research. In addition, the classical VRP is used as the initial platform for our experiments which serves as the basis for tackling the other related routing problems mentioned above. The aim is to turn the successful implementations of the proposed algorithm by easily adapting and extending it to cater for the other two related routing problems namely the CCVRP and the DVRP. While the general assumption in most VRPs is profit-based such as the minimisation of the transportation cost, there are other objective functions such as to provide a good service to the customers. Such applications appear in the context of humanitarian relief where the main objective is to save lives or to alleviate suffering. This leads to the introduction of the CCVRP, which aims to minimise the sum of arrival times at customers. The literature for this particular problem is relatively scarce despite its practical importance. We therefore intend to investigate this new and interesting variant. In addition, during the emergency situation, there is often a limited time for saving lives. A good routing plan should also ensure fairness and equity to everyone including the last customer. Motivated by this idea, an alternative but closely related objective that minimises the last arrival time is also studied. We refer to this variant as the min-max CCVRP. In the traditional VRP, a route plan remains unchanged once it is identified. However in practice, several unforeseen events such as accidents or bad weather could occur at any point when the routes are executed, which cause traffic congestion and delay to the original planned routes. Therefore, it is important to re-optimise the routes by taking into consideration the real-time information, leading to the DVRP. The review of the DVRP literature shows that researchers have mainly focused on the customer requests as the dynamic aspect. Our research, however, concentrates more on the less popular but very practical aspect, namely the dynamic traffic information. Such unpredictable events have a great impact on the route plan and henceforth shall, in overview, not be ignored. The contributions of this thesis are fourfold: (i) To propose an effective hybridisation of the VNS and the LNS in addition to some new and powerful data structures and neighbourhood reduction scheme integrated in the algorithm, (ii) To adapt the AVNS algorithm for the CCVRP with extra features added and to present new best results, (iii) To demonstrate the flexibility and effectiveness of the AVNS algorithm to solve the min-max CCVRP and to explore the managerial insights for decision making when considering the min-sum and the min-max CCVRP objective functions, (iv) To adapt the AVNS algorithm as a re-optimisation procedure for the DVRP, where we introduce the concept of critical points which are used as the turning points for the vehicle.

This thesis investigates analytical dynamic system optimal assignment with departure time choice in a rigorous and original way. Dynamic system optimal assignment is formulated here as a state-dependent optimal control problem. A fixed volume of traffic is assigned to departure times and routes such that the total system travel cost is minimized. Although the system optimal assignment is not a realistic representation of traffic, it provides a bound on performance and shows how the transport planner or engineer can make the best use of the road system, and as such it is a useful benchmark for evaluating various transport policy measures. The analysis shows that to operate the transport system optimally, each traveller in the system should consider the dynamic externality that he or she imposes on the system from the time of his or her entry. To capture this dynamic externality, we develop a novel sensitivity analysis of travel cost. Solution algorithms are developed to calculate the dynamic externality and traffic assignments based on the analyses. We also investigate alternative solution strategies and the effect of time discretization on the quality of calculated assignments. Numerical examples are given and the characteristics of the results are discussed. Calculating dynamic system optimal assignment and the associated optimal toll could be too difficult for practical implementation. We therefore consider some practical tolling strategies for dynamic management of network traffic. The tolling strategies considered in this thesis include both uniform and congestion-based tolling strategies, which are compared with the dynamic system optimal toll so that their performance can be evaluated. In deriving the tolling strategies, it is assumed that we have an exact model for the underlying traffic behaviour. In reality, we do not have such information so that the robustness of a toll calculation method is an important issue to be investigated in practice. It is found that the tolls calculated by using divided linear traffic models can perform well over a wide range of scenarios. The divided linear travel time models thus should receive more attention in the future research on robust dynamic traffic control strategies design. In conclusion, this thesis contributes to the literature on dynamic traffic modelling and management, and to support further analysis and model development in this area.

Road traffic congestion is the most persistent and debilitating problem in nearly all cities. Understanding congestion in space-time can greatly facilitate understanding of the beginning and evolution of congestion. Visualisation can be a tool to solve traffic congestion by getting insight into traffic data. This thesis focuses on developing visualisation techniques that can reveal space-time characteristics of traffic congestion, inclusive of how traffic congestion starts, disperses, and dissipates over the road network. Three main techniques are developed in this thesis, which include: wall map, isosurface, and constraint isosurface. The 3D wall map visualises the change of traffic and highlights congestion on each link. The 3D isosurface reveals sizes and shapes, and also the development of congestion. The constrained isosurface gives similar information to the isosurface, but locations of congestion are more localized. The three methods show how the origins and dispersion of congestion occurred. They also show different details of traffic data. A Graphic User Interface (GUI) was developed to allow users to interact with the traffic data and also to manipulate the visualisation to effectively support the identification of congested areas and relevant spatio-temporal information. The user-centred design approach was employed from the beginning of the GUI design process to ensure the ease of use. The massive amounts of traffic data are organised by data warehousing and by online analytical processing (OLAP) techniques, which improve multidimensional query response time. The system is implemented for link travel time data from Automatic Number Plate Recognition (ANPR). The combination of visualisation techniques with GUI and effective data management can help traffic managers to better understand how traffic congestion changes on the road network, and to uncover the solutions to congestion.

Motorways provide an important transport facility for people and goods with social, environmental and economic consequences. The demand for their use continues to increase, leading to more extensive and severe congestion; therefore, finding ways to reduce it is a priority, and Intelligent Transport Systems (ITS) have been identified as a contributor. Intelligent vehicles equipped with in-car communication systems are capable of receiving messages from the infrastructure and communicating with other vehicles. This communication enables the cooperation among them and offers many opportunities for developing a new generation of ITS that is referred to as Cooperative Intelligent Transport Systems. This research presents an innovative control algorithm for managing motorway merges using intelligent vehicles, exploiting the cooperation made possible by communication. This innovative system, called Cooperative Ramp Metering (CoopRM), requires the cooperation of equipped vehicles on the main carriageway in order to create gaps for facilitating the merging of on-ramp vehicles, aiming to reduce congestion at motorway junctions. First, similar management systems are reviewed, and the algorithms are classified based on their characteristics, then similarities, dissimilarities, trends and research gaps are described. Established a state-of-the-art in this research field, the Cooperative Ramp Metering algorithm is defined analytically. Macroscopic traffic flow theory is used in combination with microscopic theory to determine the equations governing the CoopRM control strategy. The accuracy of this formulation is then validated by comparing theoretical against simulation results. Finally, the traffic performance of the CoopRM is evaluated using a stochastic microscopic simulation model, calculating and comparing indexes representative of congestion and disruptions at traffic flow for different scenarios. Results show a substantial reduction in congestion, a decrease of perturbations and a more efficient merging procedure. This study demonstrates how this innovative Cooperative ITS is able to improve the current motorway infrastructure through the use of emerging communication technology.

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The digital electronic computer is successfully used to simulate many events encountered in the flow of vehicular traffic, especially the complex traffic phenomena at highway intersections. This investigation exclusively deals with the development of two models to investigate the traffic performance at a mini-roundabout and a conventional rotary intersection. The method of approach is by using simulation techniques on a digital ICL 1900 electronic computer. The study includes many variables such as queue length. Gap acceptance and vehicle movements in the rotary. The two types of intersection under study are classified according to the number of approaches. Those approaches are either 3, 4 or 5. The number of lanes in each of these approaches can have a value of either 1, 2, 3 or 4 depending on the actual flow and the space available. The criteria includes the possible existence of such type of intersection. The input data includes number of approaches, number of lanes in each approach, length of rotary intersection, speed distribution, gap acceptance distribution, approach volumes and turning manoeuvres. The output from the simulation models presented a considerable number of simulated delays to vehicles on the approach lanes and of the intersections as a whole. A series of computer runs were undertaken and the results were analysed to study the effects of some intersection and traffic parameters on the average and total delays. Validation study was carried out on two sites in the West Yorkshire area using time lapse cine photography and the observed results were analysed and compared with the simulated ones. For the approach lanes in the rotary section six forms of delay formulae are introduced. These formulae represent the relationship between the approach lane traffic flow and the traffic volume in the rotary section and the average delay in the approach lane..