Infrastructure Engineering - Theses
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ItemInformation sensing, transmission and management between connected vehicles( 2023-07)The concept of connected vehicles is gaining momentum in the research communities thanks to the development of wireless communication technologies. Due to their ubiquity, mobility and connectivity, connected vehicles have the potential to not only revolutionise the transportation industry, but also be exploited for information sensing and transmission, as they are equipped with a wide range of sensors in addition to the wireless communication devices. Despite having the power supply and computing capacity to continuously host such sensors, the unpredictability and disorganisation of connected vehicles are presented as challenges for collecting and sharing information. Therefore, the aim of this research is to explore the role, usage and methodology of connected vehicles for information sensing, transmission and management. With regard to information sensing through connected vehicles in urban areas, this study investigates sensor network deployment, vehicle selection, and route assignment with the aim of collecting data that are appropriate for the task at hand. First, a framework is proposed to optimise the configuration of stationary sensors and opportunistic vehicular sensors in hybrid sensing for a given sensing task to improve sensing coverage. After knowing the number of vehicles needed for the sensing task, the next step is to select the proper vehicles. To optimise sensing coverage, a vehicle selection framework is proposed that integrates a model of forecasting fine-grained sensing coverage through coarse-grained information about candidate vehicles and the genetic algorithm. Sensing coverage mainly relies on the trajectories of these selected vehicles. Therefore, in order to further reduce the sensing overlap that exists between selected vehicles, an activity-based route assignment strategy integrates the sensing task requirements and the planned activities of the selected vehicles to assign routes that would not interfere with these activities. The implementation of these proposed approaches yields a win-win outcome for both the task initiators and the participants. Once a connected vehicle has sensed anomalous information, e.g., an incident, it can share the information to other connected vehicles via peer-to-peer networks without centralised infrastructures. In the context of transmitting information about ephemeral incidents in traffic, two event-driven models that transmit and manage transient information in vehicular networks are developed in this study. First, the time-geography framework is used to offer a decentralised transmission model that takes into account the transient nature of traffic incidents. Furthermore, a model for managing traffic incident information is put forth to improve traffic efficiency when traffic incidents occur by managing information regarding their range, timely updating outdated information in vehicular networks, and guiding traffic for affected vehicles. Experimental results show that these two proposed models can reduce not only invalid broadcasts but also incident-induced traffic congestion. Overall, the potential of connected vehicles for information sensing, transmission and management is explored in this thesis. The findings of this study demonstrate that the proposed approaches are capable of increasing sensing coverage so that the information sensed is appropriate for intended uses, and improving the efficiency of information sharing while requiring less broadcast and shortening the duration of invalid broadcast.