Using Glance Behaviour to Evaluate ACC Driver Controls in a Driving Simulator
This paper examines the glance behaviour of drivers while interacting with two different driver-vehicle interface concepts for an Adaptive Cruise Control (ACC) system. With the integrated concept, the speed and following distance controls were located on the steering wheel whereas with the divided concept the speed control was moved to the dashboard. A virtual Head-Up Display (HUD) was used to show the ACC settings and current speed. Twelve subjects (19 to 53 years old) drove a rural road course in a fixed-base driving simulator while being verbally instructed to adjust the speed and/or following distance of the ACC system. Dividing the controls between the steering wheel and dashboard caused significantly larger mean and maximum glance times and a lower glance frequency to the displays and controls. The percent glance time “off-road” furthermore increased significantly during task completion. Other significant results were observed between the task type and task length.
Driving simulation platform applied to develop driving assistance systems
This study presents a driving simulation platform with low cost for the development of driving assistance systems (DAS). The platform uses a combination of two simulation loops: hardware-in-the-loop (HIL) and driver-in-the-loop (DIL). Its hardware consists of a simulation computer, a monitor computer, a vision computer, DAS actuators and a car mock-up. Its main software includes a monitor software running in the monitor computer, a vision rendering software running in the vision computer and Matlab/Simulink-based simulation model running in simulation computer. When designing its monitor software, a graphical user interface driven-by S-function method is adopted to eliminate the delay in the displaying of the simulation data. The vision rendering software uses a parametric adjustment method based on the principle of optical projection, improving the driver's perception of being immersed in the virtual traffic scene. The application of the developed platform is demonstrated by HIL experiments of vehicle actuators and DIL experiments of adaptive cruise control (ACC) algorithm. These experiments not only demonstrate the potential merit of the platform of speeding up DAS development, but also illustrate that the proposed control algorithms for actuators possess good tracking capability, as well as that the developed ACC algorithm is capable of improving driver comfort and reducing driver workload.
DRIVER-VEHICLE INTERACTION WHILE DRIVING WITH ACC IN BORDERLINE SITUATIONS
An interaction model for the driver-vehicle-environment loop is established to clarify terms like subjective borderline situation or traffic conflict. In addition, the reasons for occurrence of borderline situations are outlined. In an experiment in real traffic three versions of Adaptive Cruise Control (ACC) were tested, differing mainly in the maximum deceleration which could be applied by the system. The goal of this experiment was to study borderline situations caused by a mismatch between the driver's internal model of the ACC and the real ACC. The drivers showed different frequencies of braking intervention depending on the ACC version. The decision making on intervention could be modeled using the predicted minimum approach time distance as a criterion. It can be shown that drivers are able to learn ACC system behaviour thus reducing driver workload caused by the intervention decision process, and this workload turned out to be highest with an ACC with medium deceleration capability. As a result, adequate display systems can be developed now to reduce borderline situations by supporting the driver's prediction capabilities. (A) For the covering abstract, see IRRD 490001.