Driving simulation platform applied to develop driving assistance systems

Abstract

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.

Effect of Warning System on Interactive Driving Behavior at Unsignalized Intersection under Fog Conditions: A Study Based on Multiuser Driving Simulation

“…e most significant aspect was that the warning system immensely reduced the risk of driving, judging from the mean profile of PET under different warning conditions. ese findings confirmed previous research results on the warning system [44][45][46][47].…”

Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection

“…Campagne et al [3] studied the relationship of driver's age difference to traffic accidence numbers using EEG recorder, and the result showed that driver's vigilance would decrease and the number of operation mistakes would grow as the age increases. Brundell-Freij and Ericsson [4], Leng et al [5], Pêcher [6], Di Stasi [7], Taubman-Ben-Ari [8], Cai and Lin [9], Parker et al [10], Trick et al [11], Lansdown [12], Daffy [13], Wang et al [14][15][16], Weng and Meng [17], Verschuur and Hurts [18], Zhang et al [19], Gosselin et al [20], and Hu et al [21], Danciu et al [22] have studied driver behavior characteristics from different angles. However, in the field of vehicle active safety, there are few researches on driver's affective characteristics from microcosmic and dynamic perspective.…”

A Novel Approach to Neural Network-based Motion Cueing Algorithm for a Driving Simulator

“…Driving simulators have become an important part of the product development cycle in the automotive industry. They enable more cost-effective and shorter development processes [1], [2], and provide safe, reproducible, and controlled environments to assess, for example, the comfort of the driver by conducting subjective experiments [3], [4]. Regarding the benefits of the simulators, the automotive industry is increasingly concentrating on replacing real vehicle studies with driving simulations especially for validating the perfor-mance of Advanced Driver Assistance Systems (ADAS) and autonomous driving prototypes.…”