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With the emergence of connected vehicle technologies, many interesting applications become possible. We look at one such application that allows trac system users with heterogeneous values of time (VOT) to trade their right of way (ROW) among other users so as to minimize individuals' total travel costs, which includes time cost and nancial transaction. Our proposed system allows users on a multi-lane road to trade their ROWs, and the resulting traffic flow violates the First-In-First-Out (FIFO) principle, since vehicles with higher VOTs would travel faster by paying those with lower VOTs. A novel multi-commodity kinematic wave model is developed for such a system based on the assumptions of choice, uniability, prices, budget-balance, utility maximization, referred to as A1 through A5.From these assumptions, we study a simple case of such a system in which two groups of users with different VOTs participate in the scheme, and a third group does not participate. We derive a uniable fundamental diagram in which the relative speed ratios of differentcommodities are constant and proportional to the square root of the VOTs. We show that the scheme is Pareto-improving at the system optimal solution. The Riemann Problem is solved both analytically and numerically for this system, and we demonstrate that differentcommodities (user groups) would react differently to shockwaves and rarefaction waves. The study is concluded with future extensions.

With connected vehicle technology, eco-driving strategies could bring benefits in decreasing traffic oscillation, reducing fuel consumption along with air pollution, and improving traffic mobility. This thesis proposes an eco-driving strategy to reduce traffic oscillation and smooth trajectories for vehicles at different traffic situations, including highway sections and urban traffic intersections. The eco-driving strategy assumes a connected vehicle environment, in which each vehicle exchanges information in real-time through vehicle-to-infrastructure (V2I) communications and vehicle-to-vehicle (V2V) communications. The proposed strategy devises the advisory speed and the control duration for each vehicle through various control algorithms that are available in different traffic situations. After receiving the information from V2I and V2V communications, each connected vehicle would apply a simple cruise control method during the control duration. The proposed algorithm determines proper advisory speed and control duration through a heuristic solution of the optimization model, which is a tangent line approach. The optimization model, which has the objective function to minimize the speed oscillation of each vehicle is applied at the origin or estimated trajectories under different traffic situations, including when vehicles are approaching a signalized intersection, non-signalized intersection, and following a moving bottleneck at an arterial road. Based on the optimization model, this study proposes a heuristic solution which is a tangent line method between control starting point to the estimated objective trajectories, with the slope of the tangent line serving as the static advisory speed applied for the vehicle. The kinematic wave analysis is applied for deriving or estimating vehicle objective trajectories at each traffic situation. In a highway with a slow-moving vehicle, this study solves a more generalized moving bottleneck problem to derive the traffic flow-rate and density upstream of the moving bottleneck, and get the following trajectory for each vehicle after the moving bottleneck. At traffic intersections, the kinematic wave analysis is first applied to describe vehicle start-up behaviors, and demonstrates the requirements for fully improving traffic efficiency. According to the requirements, the estimated time points (i.e., the passing points) are created for vehicles to pass through the intersection. Accordingly, the origin trajectories are estimated in order to make vehicles enter the intersection at each passing point with the designed optimal speed. For a signalized intersection, the passing points are created based on a specific signal plan of a given phasing. In addition, the eco-driving strategy could also be extended into a Cooperative Vehicle Intersection Control (CVIC) algorithm and applied at a non-signalized intersection. In this situation, the passing points are created and updated according to the previous vehicles passing through the intersection from different directions.The benefits of this strategy are presented from a set of numerical simulations, along with the sensitivity analysis with the flow-rate taken at the intersection situations. The simulations are conducted for each traffic situation. In the highway sections, four scenarios with different bottleneck movements are applied, where the moving bottleneck has a constant speed, accelerates, decelerates, and stops-and-goes. The results show that both speed variance and fuel consumption are reduced with the algorithm in each of the scenarios. At the signalized intersections, all vehicles applying the algorithm would never stop before the intersection and would pass through the intersection with the free-flow speed. The number of vehicles that could pass through the intersection also increases. Also, traffic oscillation is reduced when approaching the intersection. With the CVIC algorithm applying at the intersection, all vehicles could pass through the intersection with free-flow speed, and no traffic conflictions happens between vehicles. Furthermore, in an illustrative study, the algorithm reduces the total intersection delay by 34.95 % on average, the fuel consumption by 65.79 % on average, and the speed variance by 5.75 % on average. The simulation result shows the algorithm could be beneficial in decreasing traffic oscillation, reducing environmental impact, and improving traffic efficiency as well when applied at the intersections. The basic idea behind this study is to make a predictable time and speed for the vehicle to eliminate the moving bottleneck effects and to pass through the intersection. This information provides a theoretical basis for further optimizing the traffic flows through the V2I, V2V communications, and CAV technologies, which could be applied to various situations.

Extensive research has been undertaken to improve the robustness of runoff quantity predictions for urban catchments. However, equally robust predictions for runoff quality have yet to be attained. Past studies addressing this issue have typically been confined to the use of simple conceptual or empirical models which forgo the tedious steps of providing a physical representation of the actual system to be modeled. Consequently, even if the modelling results for the test catchments are satisfactory, the reliability and applicability of these models for other catchments remain uncertain. It is deemed that by employing process-based, deterministic models, many of these uncertainties can be eliminated. A lack of understanding of the hydrological processes occurring during storm events and the absence of good calibration data, however, hamper the advancement of such models and limit their use in the field. This research proposes that the development of a hydrologic model based on the kinematic wave equations linked to an advection-dispersion model that simulates pollutant detachment and transport will improve both runoff quantity and quality simulations and enhance the robustness of the predictions. At the very worst, a model of this type could still highlight the underlying issues that inhibit models from reproducing the recorded historical hydrographs and pollutographs. In actual fact, this approach has already been applied by various modellers to simulate the entrainment of pollutants from urban catchments. Also, the paradigm shift to using the Water Sensitive Urban Design (WSUD) approach in designing urban stormwater systems has prompted the need to differentiate the various sources of pollutants in urban catchments such as roads, roofs and other impervious surfaces. The primary objective of the study reported herein is to model runoff quantity and quality from small urban catchments, facilitated by the procurement of the necessary field data to calibrate and validate the model via implementation of a comprehensive field exercise based in Sydney. From a water quality perspective, trace metals were selected as the foci. The study outcomes include the formulation of a linkage of models capable of providing accurate and reliable runoff quantity and quality predictions for the study catchments by taking into consideration: - The different availability of pollutants from urban catchments, i.e. roads vs. roofs; - The build-up characteristics of pollutants on the distinct urban surfaces and their spatial distribution; - The contribution of rainwater to urban runoff pollution; - The partitioning of pollutants according to particulate bound and dissolved phases; - The respective role of rainfall and runoff in the detachment and entrainment of pollutants; - The influence of particle properties such as particle size distribution and density on pollutant transport; and - The relationship associating particulate bound metals to suspended solids. The simulation results obtained using the proposed model were found to be suitable for modelling the detachment and transport of pollutants for small urban catchments. Interpretation of these results reveals several key findings which could help to rectify shortcomings of existing modelling approaches. Even though the robustness of the model presented here may not translate into a significant improvement in the overall robustness of model predictions, the physical basis on which this process-based model was developed nevertheless provides the flexibility necessary for implementation at alternative sites. It is also shown that the availability of reliable runoff data is essential for implementation of the model for other similar urban catchments. In conclusion, the proposed model in this study will serve as a worthy tool in future urban catchment management studies.