Optimisation of System and Sensor Selection for Safety and Reliability of Autonomous Vehicle

Li, Haicang (2023) Optimisation of System and Sensor Selection for Safety and Reliability of Autonomous Vehicle. PhD thesis, University of Nottingham.

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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: Thesis (University of Nottingham only) (PhD)
Supervisors: Gradoni, Gabriele
Tiwari, Rajesh
Greedy, Steve
Wheeler, Patrick
Keywords: vehicle collisions, intelligent traffic system, ITS, global positioning systems, GPS, autonomous vehicles
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculties/Schools: UK Campuses > Faculty of Engineering > Department of Electrical and Electronic Engineering
Item ID: 73999
Depositing User: Li, Haicang
Date Deposited: 17 Apr 2024 09:56
Last Modified: 17 Apr 2024 09:56
URI: https://eprints.nottingham.ac.uk/id/eprint/73999

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