Formal Verification of Autonomous Vehicle Platooning

The coordination of multiple autonomous vehicles into convoys or platoons is expected on our highways in the near future. However, before such platoons can be deployed, the new autonomous behaviors of the vehicles in these platoons must be certified. An appropriate representation for vehicle platooning is as a multi-agent system in which each agent captures the "autonomous decisions" carried out by each vehicle. In order to ensure that these autonomous decision-making agents in vehicle platoons never violate safety requirements, we use formal verification. However, as the formal verification technique used to verify the agent code does not scale to the full system and as the global verification technique does not capture the essential verification of autonomous behavior, we use a combination of the two approaches. This mixed strategy allows us to verify safety requirements not only of a model of the system, but of the actual agent code used to program the autonomous vehicles

In-car advisory system for lane-changing in a connected vehicle environment

This thesis investigates the potential of in-car advisory systems to suggest location and timing where and when lane-changes should be executed, by evaluating traffic flow conditions with data that is available using vehicle-to-vehicle communication. After investigating existing literature regarding car-following and lane-changing models, as well as driving support assistance systems and vehicle communication applications and practice, a new lane-changing model is introduced, with the objective to serve as a basis for the development of the in-car advisory system. In particular, the model accounts for information about position and speed of vehicles that are downstream from the considered vehicle current position, namely, out of the sight of a driver. Based on the proposed model, a decision system to deliver lane-changing advices to the driver is implemented, with the goal of avoiding or reducing traffic congestion. A set of simulations using the microscopic traffic simulator AIMSUN are performed to test the effectiveness of the proposed system

In-car advisory system for lane-changing in a connected vehicle environment

This thesis investigates the potential of in-car advisory systems to suggest location and timing where and when lane-changes should be executed, by evaluating traffic flow conditions with data that is available using vehicle-to-vehicle communication. After investigating existing literature regarding car-following and lane-changing models, as well as driving support assistance systems and vehicle communication applications and practice, a new lane-changing model is introduced, with the objective to serve as a basis for the development of the in-car advisory system. In particular, the model accounts for information about position and speed of vehicles that are downstream from the considered vehicle current position, namely, out of the sight of a driver. Based on the proposed model, a decision system to deliver lane-changing advices to the driver is implemented, with the goal of avoiding or reducing traffic congestion. A set of simulations using the microscopic traffic simulator AIMSUN are performed to test the effectiveness of the proposed system.Outgoin

Beam Alignment for Millimetre Wave Links with Motion Prediction of Autonomous Vehicles

Intelligent Transportation Systems (ITSs) require ultra-low end-to-end delays and multi-gigabit-per-second data transmission. Millimetre Waves (mmWaves) communications can fulfil these requirements. However, the increased mobility of Connected and Autonomous Vehicles (CAVs), requires frequent beamforming - thus introducing increased overhead. In this paper, a new beamforming algorithm is proposed able to achieve overhead-free beamforming training. Leveraging from the CAVs sensory data, broadcast with Dedicated Short Range Communications (DSRC) beacons, the position and the motion of a CAV can be estimated and beamform accordingly. To minimise the position errors, an analysis of the distinct error components was presented. The network performance is further enhanced by adapting the antenna beamwidth with respect to the position error. Our algorithm outperforms the legacy IEEE 802.11ad approach proving it a viable solution for the future ITS applications and services.Comment: Proc. of IET Colloquium on Antennas, Propagation & RF Technology for Transport and Autonomous Platforms, to appea