Municipal waste management aims to collect waste from people and businesses in a sustainable manner. Today's waste management relies on an old container system which is simple and flexible. There are some problems with this type of management for both waste generators and collectors. The working environment is not the best for municipal waste collectors, there is heavy lifting and risk elements in the handling of containers and bags. There are also risks involved with heavy vehicles moving in sensitive areas such as residential areas and around schools. Forecasts show that most urbanized areas are expected to grow further for some time. This creates problems of increasing waste volumes, thereby increasing traffic. This makes it interesting to evaluate new and existing solutions of the collection and transportation of municipal solid waste. The study aims to identify the current municipal solid waste management theories and evaluate the opportunities that exist to develop the theory forward with focus on the collection in urban areas. The study intends to review whether it is economically feasible to implement automated vacuum systems in existing infrastructure. The theory shows that it is often possible to implement this in new construction projects, but the research is vague and inadequate regarding implementation in existing infrastructure. The case study examines whether implementation of an automated vacuum collection system is possible in central Gothenburg. The analysis assesses the financial feasibility of the implementation. Specifically, the unused surface of the refuse rooms can be utilized differently, thus reducing the costs that arise initially. The study shows that it will be profitable to implement an automated vacuum system in the study area since the initial investment can be offset through the alternative use of the floor space in the waste rooms. The study results suggest that other areas in existing infrastructure can implement similar solutions without economic losses.

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science