Intelligent Management System for Driverless Vehicles

Abstract

This research addresses concerns related to driverless vehicles by proposing the development of an Intelligent Management System (IMS). Emphasised in 'The Pathway to Driverless Cars Summary report and action plan' by the UK Department of Transport, key areas for improvement lie in vehicle reliability, maintenance, and passenger safety. The study targets compliance with Society of Automotive Engineers (SAE) Level 5 automation, concentrating on fully autonomous vehicles to enhance commuter satisfaction and overall vehicle performance. Despite advancements, challenges such as on-road safety and integration persist.

The research unfolds through a two-stage development process aimed at achieving an Intelligent Management System for Driverless Vehicles (IMSDV). The initial stage, described in chapter 3 involves the creation of a 'Single Seat Driverless Pod' as a test apparatus, simulating various features found in existing driverless vehicles. This includes the development of mechanical steering components and a control system incorporating electronic hardware, sensors, actuators, controllers, wireless remote access, and software. The subsequent phase, described in chapter 4 focuses on autonomous navigation using Google Maps, intelligent motion control, localisation, and tracking algorithms within the driverless pod.

The latter chapters of the thesis present the investigation of possible improvements in steering system components. A novel encapsulated vehicle wheel condition monitoring system, integrating the Internet of Things (IoT), is proposed to enhance maintainability, reliability, and passenger safety for driverless vehicles.

Testing and validation are conducted in two segments. The driverless pod undergoes initial testing to validate its features and generate data for further sub-system development. Separately, the IoT-based monitoring system undergoes individual testing. The final step involves integrating the IoT capabilities into the driverless pod, testing the sub-system, and capturing relevant data.

The thesis outlines the research scope, emphasising significant contributions, with a particular focus on the monitoring system for steering components in driverless vehicles, employing embedded IoT technology. This augmentation, alongside other original contribution, is strategically poised to enhance the maintainability, reliability, and safety of driverless vehicles at SAE Level 5. The concluding chapter succinctly revisits these distinctive contributions and additionally provides recommendations for advancing intelligent management systems for driverless vehicles.