Optimisation of System and Sensor Selection for Safety and Reliability of Autonomous Vehicle
Publication Date
July 21, 2023
Creator
Abstract
In the modern traffic system, road traffic accidents and congestion have been the most critical problems which have caused a large number of deaths and economic damage. ITS (intelligent traffic system) based on vehicular communications is one of the effective approaches to avoid vehicle collisions and increase the efficiency of traffic. GPS (global positioning system) is one of the widely used navigation systems for vehicles in ITS. However, the performance of GPS can be affected remarkably by various factors. As a result of this, it is necessary to evaluate the reliability of GPS observation to increase the safety of road users. Furthermore, for the challenging environment such as GPS-denied environment, multisensor navigation is expected to be used to improve the robustness and continuity of the positioning system. Additionally, selecting sensors to be fused according to their reliability is an effective method to mitigate the negative influence of sensors caused by challenging traffic environments.\par
In this thesis, a spatio-temporal roundabout and crossroad ITM algorithm has been developed, defining the confidence circle based on the reliability of GPS observation. The simulation results illustrate that the proposed ITM protocol improves safety level and traffic efficiency significantly. Secondly, a GPS/IMU integration positioning system is proposed, which uses ICC (intraclass correlation coefficient) as a reliability factor to mitigate positioning errors of GPS. The experiments results show that positioning errors are reduced by applying ICC. And further improvement of positioning is achieved by integrating IMU measurements and optimised GPS measurements. Finally, a three-sensor-based multisensor navigation system is designed, which utilises reliability evaluation to detect and select optional fusion modes. As the field trial results show, the robustness and accuracy of positioning under challenging traffic environments can be improved significantly by applying the proposed multisensor navigation system.
Item Type
ethesis
Thesis Type
PhD
Subjects (LC)
Associated Schools / Departments
Department of Electrical and Electronic Engineering (UK)
eprints ID
73999
UoN Repository URI
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Optimisation of System and Sensor Selection for Safety and Reliability of Autonomous Vehicle.pdf
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Examined. Final version thesis for PhD degree
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10.61 MB
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