Dr Peter Ball

Connected and Autonomous Vehicles (CAVs) rely on Vehicular Adhoc Networks with wireless communication between vehicles and roadside infrastructure to support safe operation. However, cybersecurity attacks pose a threat to VANETs and the safe operation of CAVs. This study proposes the use of simulation for modelling typical communication scenarios which may be subject to malicious attacks. The Eclipse MOSAIC simulation framework is used to model two typical road scenarios, including messaging between the vehicles and infrastructure - and both replay and bogus information cybersecurity attacks are introduced. The model demonstrates the impact of these attacks, and provides an open dataset to inform the development of machine learning algorithms to provide anomaly detection and mitigation solutions for enhancing secure communications and safe deployment of CAVs on the road.

The rising popularity of autonomous vehicles has led to the development of driverless racing cars, where the
competitive nature of motorsport has the potential to drive innovations in autonomous vehicle technology. The challenge of racing requires the sensors, object detection and vehicle control systems to work together at the highest possible speed and computational efficiency. This paper describes an autonomous driving system for a self-driving racing vehicle application using a modest sensor suite coupled with accessible processing hardware, with an object detection system capable of a frame rate of 25fps, and a mean average precision of 92%. A modelling tool is developed in open-source software for real-time dynamic simulation of the autonomous vehicle and associated sensors, which is fully interchangeable with the real vehicle. The simulator provides performance metrics, which enables accelerated and enhanced quantitative analysis, tuning and optimisation of the autonomous control system algorithms. A design study demonstrates the ability of the simulation to assist in control system parameter tuning - resulting in a 12% reduction in lap time, and an average velocity of 25 km/h - indicating the value of using simulation for the optimisation of multiple parameters in the autonomous control system.

Reliable wireless communications between vehicles (V2V) and between vehicles and infrastructure (V2I) will play a key role in future transport networks. Where there is overlapping coverage of multiple Radio Access Technologies, with no cooperation between them, a vehicle can use the different technologies simultaneously to enhance performance and improve resilience. This paper proposes an uplink Multi Interface Scheduling System (MISS) that incorporates intelligent interface selection, located at an intermediate shim layer on the user side, to achieve efficient bandwidth aggregation, or lower delay. Rather than finding the best alternative amongst different technologies, this paper’s algorithm aims to find all the available networks that can meet multiple criteria. Simulation has been carried out to determine the performance of the system in the presence of a range of different service types. The simulation results show that safety critical traffic can be prioritized in terms of throughput and delay where the resources are insufficient for all the services. This algorithm is ideally suited to vehicular networks, particularly where delivery of safety traffic is an essential requirement.

Given the future context of fully integrated Intelligent Transport Systems, reliable wireless communications is a necessity. Traditionally, a single wireless technology is selected for communication but by using heterogeneous wireless communication, advantage can be taken of the different transmission characteristics. This paper proposes a novel Multiple Interface Scheduling Algorithm (MISA) which schedules uplink packets over multiple technologies for which no coordination is required among access networks. The algorithm incorporates a dynamic scoring approach for each of the available networks based on selected system performance parameters. A key feature of the proposed scheduler is that it is located between the IP layer and the MAC layer, hence a single IP address is used, and it is not necessary to modify the wireless standards. A model has been developed to simulate the proposed algorithm and the system performance for three multi radio transmission diversity schemes. The results show the advantage that can be gained in throughput by cooperatively using multiple technologies.

This paper proposes green energy efficiency metrics for low-power wireless sensors operating at ground level. The metrics are derived from our previous work on energy efficiency analysis for general wireless networks and a radio propagation model for near ground level wireless sensors. A numerical analysis is carried out to investigate the utilization of the green energy efficiency metrics for ground level communication in wireless sensor networks. The proposed metrics have been developed to calculate the optimal sensor deployment, antenna height and energy efficiency level for the near ground wireless sensor. As an application of the proposed metrics, the relationship between the energy efficiency and the spacing between the wireless sensor nodes is studied. The results provide an accurate guidance for energy efficient deployment of near ground level wireless sensors. 

Abstract— this paper investigates the use of a wireless sensor network (WSN) for communicating between road-based nodes. These nodes are situated at ground level and two-way wireless communication is required between the nodes and from the nodes to a roadside control unit. Measurements have been carried out to examine the propagation close to the ground to determine the maximum distance between roadbased nodes as a function of the antenna height. The results show that for a frequency of 2.4 GHz, a range of up to 8m is achievable with 2mW EIRP. An empirical near-ground level radio propagation model is derived and the predicted results from this model are shown to match closely to the measured results.