One-year feasibility study processing existing datasets, to understand the parameters needed for modelling human drivers and how to extend them to make vehicle rules for CAVs, improving current technology and modelling impacts to balance comfort, capacity and safety. The aim is to ensure CAV behaviour meets the needs of both regulators and customers.
Roads deemed difficult for driverless vehicles to navigate, such as small side roads with parked cars either side and a narrow running lane through the middle.
Aimsun used an existing model of Birmingham and then simulated the closure of various parts of the network examining the impact on network speeds and throughputs. These closures were used as a surrogate for situations where a Level 5 driverless vehicle were to break down or be incapable of proceeding and require additional control from a remote operations centre.
Aimsun was able to accurately simulate the effects of introducing unforeseen impacts on traffic while the project as a whole examined patents on rules for CAVs; an improved understanding of early mixed fleet operation of human and automated vehicles and how to make early level self-driving vehicles attractive to users. Additionally, improved understanding for highways authorities and vehicle makers was delivered regarding how to deploy CAVs on a variety of real-world roads.