Civil engineering projects are often strategic in that they fulfil a need for society, such as a bridge. Maintenance of all infrastructure assets is crucial and this Thesis will consider maintenance aspects of two areas of infrastructure: water retaining gates and locationa1 data necessary to manage buried services within the structure of our highways. Water an essential commodity of society to support life of the community directly and indirectly for key functions, such as transportation. The importance of water based transportation has been established for as long as historical records show as has the desire to improve the efficiency of the ships and the support systems in place to accommodate imports and exports. Water retention in docks and canals has been achieved with the use of gates to allow access for ships while attempting to maintain a water level for the vessels within the dock, or canal area. A common gate style used in these locations is the mitre gate. This Thesis will consider mitre gates and their development to today's status and make reference to published works on the subject detailing the justification for the Thesis to be written. In contracts, delays in traffic caused by maintenance work are a common occurrence with trenches being dug in highways for maintenance or new works. In the main the work is being done for utility companies who provide commodities we all anticipate in our daily life, e.g. potable water, sewage, gas, electricity, telephone, etc. Changes how data for these buried services are controlled took place with new legislation defining who has responsibility for the services and their interface with the highway structure. The Buried Services Working Group did influence the detail of the legislation although the motivation for change already existed. Most members of the general public would accept that it is unusual to be unaffected at some time during a road journey by roadworks. Most highways, excluding motorways, contain buried services in the road structure such as water pipes, electricity cable, gas mains, etc. Maintaining buried services is necessary to cope with normal wear and tear but also access is required to expand the existing system or to install new buried services as the demand for utilities increases. This Thesis will present the published report by the BSWG and also give the rationale as to how and why the group was formed.

This thesis focuses on the development of a micro-simulation model for motorway merge sections. The aim is to study the effectiveness of applying some traffic management controls and particularly focuses on applying ramp metering (RM) systems. The new model has been developed based on car-following, lane changing and gap acceptance rules. The model considered the multi-decisions undertaken by merging traffic when a driver, for example, accepts the lead gap and rejects the lag gap. The cooperative nature of drivers is also considered where motorway drivers allow others to merge in front of them either by decelerating or shifting to other lanes (yielding) in the vicinity of motorway merge sections. Video recordings, as well as data from the Motorway Incident Detection and Automatic Signalling (MIDAS) were obtained from a selection of sites. The data was used in the verification, calibration and validation processes of the developed model. Other main sources of information include more than 4 million cases of successive vehicles taken from UK motorway sites. These cases were analysed to study the effect of vehicle types on the following behaviour for drivers. The main finding is that there is no evidence that the average spacing between successive vehicles is significantly affected by the type of leading vehicle. Different RM algorithms have been integrated within the developed model. The results of testing the effectiveness of RM controls using the developed model reveal the benefits of RM in reducing time spent by motorway traffic (TTSM) but it significantly increases the time spent by the merging traffic (TTSM). The overall benefits of implementing RM in reducing total time spent (TTS) is limited to situations where the sum of motorway and merge flows exceeds the capacity of the downstream section. Other issues related to RM design and effectiveness have been tested such as the effects of having different durations for peak periods, finding the optimum parameters for each algorithm, the effect of ramp length (storage area) and the effect of RM signals position. The results suggest that RM is very efficient when implemented for short peak periods (e.g. less than 30 minutes). The effectiveness of RM in decreasing the travel time for motorway traffic is increased with an increasing ramp length but with a significant increase in ramp traffic delay. No significant effect is obtained from altering the ramp signals' position. Other tests include the use of other types of traffic management controls (e.g. applying different speed limits and lane changing restrictions (LCR) at the approach to merge sections). No significant improvements were obtained from testing different speed limit values. The results suggest that LCR could reduce travel time for motorway traffic. However, there are other practical considerations which need to be addressed before this could be recommended.

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This thesis presents a study on an adaptive traffic signal controller for real-time operation. An approximate dynamic programming (ADP) algorithm is developed for controlling traffic signals at isolated intersection and in distributed traffic networks. This approach is derived from the premise that classic dynamic programming is computationally difficult to solve, and approximation is the second-best option for establishing sequential decision-making for complex process. The proposed ADP algorithm substantially reduces computational burden by using a linear approximation function to replace the exact value function of dynamic programming solution. Machine-learning techniques are used to improve the approximation progressively. Not knowing the ideal response for the approximation to learn from, we use the paradigm of unsupervised learning, and reinforcement learning in particular. Temporal-difference learning and perturbation learning are investigated as appropriate candidates in the family of unsupervised learning. We find in computer simulation that the proposed method achieves substantial reduction in vehicle delays in comparison with optimised fixed-time plans, and is competitive against other adaptive methods in computational efficiency and effectiveness in managing varying traffic. Our results show that substantial benefits can be gained by increasing the frequency at which the signal plans are revised. The proposed ADP algorithm is in compliance with a range of discrete systems of resolution from 0.5 to 5 seconds per temporal step. This study demonstrates the readiness of the proposed approach for real-time operations at isolated intersections and the potentials for distributed network control.

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Roads represent a major long-term infrastructure investment. A well-managed and maintained road is therefore fundamental to the safety and availability of the road network as a whole. In carrying out pavement maintenance functions, Local Road Authorities face growing pressures arising from inadequate budgets and greater accountability, when many of the existing roads have reached the upper limits of their design life spans while being subjected to increasing traffic. There are many factors that influence the decision making process in pavement maintenance management, including road surface conditions, safety, traffic loading, cost, funding and prioritisation decisions, hence an efficient approach is vital to ensure optimisation and a satisfactory trade-off between conflicting factors. A Multi-criteria Decision Making (MCDM) approach is used to handle the trade-off between conflicting factors. It is processed in the Analytical Hierarchy Process (AHP) using Excel software, and the database developed in Excel is then imported into GIS in order to allow ease of query, analysis and visualisation of results. The main key output of this research will be the development of a GIS-based pavement maintenance management model to support decision making in pavement maintenance management. The most important factors influencing decision making in pavement maintenance management are established through a nationwide questionnaire survey, which is undertaken among the UK Local Authorities’ pavement maintenance experts. 14 factors were identified, which are: Remaining Service Life, Road Condition Indicator (RCI), Type of Deterioration, Observed Deterioration Rate, Traffic Diversion, Importance of Road/Classification, Annual Average Daily Traffic (AADT), Possible Conflict or Overlap with Other Road Works, Risk of failure, Safety Concern, Accident Rate (related to surface condition), Scheme Cost, Available Budget/Funding and Whole Life-Cycle Cost. Interviews were also conducted with experts in pavement maintenance within different Local Road Authorities to justify the rated factors affecting pavement maintenance prioritisation. The case study approach was adopted, based on Runnymede District roads within the Surrey County Council, for developing and testing the GIS-based decision support model. The output model was validated through interviews with four experts in pavement maintenance as target end-users, and the model was judged as a rational, simple and usable appropriate tool for network analysis as GIS. However, a risk of inadequate budgets might limit the practicability of the model.

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