Analysis of Autonomic Indexes on Drivers' Workload to Assess the Effect of Visual ADAS on User Experience and Driving Performance in Different Driving Conditions

Abstract

Advanced driver assistance systems (ADASs) allow information provision through visual, auditory, and haptic signals to achieve multidimensional goals of mobility. However, processing information from ADAS requires operating expenses of mental workload that drivers incur from their limited attentional resources. The change in driving condition can modulate drivers' workload and potentially impair drivers' interaction with ADAS. This paper shows how the measure of cardiac activity (heart rate and the indexes of autonomic nervous system (ANS)) could discriminate the influence of different driving conditions on drivers' workload associated with attentional resources engaged while driving with ADAS. Fourteen drivers performed a car-following task with visual ADAS in a simulated driving. Drivers' workload was manipulated in two driving conditions: one in monotonous condition (constant speed) and another in more active condition (variable speed). Results showed that drivers' workload was similarly affected, but the amount of attentional resources allocation was slightly distinct between both conditions. The analysis of main effect of time demonstrated that drivers' workload increased over time without the alterations in autonomic indexes regardless of driving condition. However, the main effect of driving condition produced a higher level of sympathetic activation on variable speed driving compared to driving with constant speed. Variable speed driving requires more adjustment of steering wheel movement (SWM) to maintain lane-keeping performance, which led to higher level of task involvement and increased task engagement. The proposed measures appear promising to help designing new adaptive working modalities for ADAS on the account of variation in driving condition.

Explore User Behaviour in Semi-autonomous Driving

“…Figure 4 shows the distance each participant covered in the limited time of experiment, although the value of distance varies, it can be observed from the slop that driver number 2 demonstrated the best speed control aspect and then was Driver 1 and Driver 3, considering that they were requested to complete the task as soon as possible, obeying the safety requirement. SDLP is considered as the index for lane-keeping performance (lower the number, better the performance), and SDSW together with SWM, are considered as indexes for steering wheel management (Ariansyah et al, 2018). Performance measure from three pilot-tests are compared in Table 2, with their corresponding rank.…”

Perception of Driving Simulations: Can the Level of Detail of Virtual Scenarios Affect the Driver's Behavior and Emotions?

“…Vehicular and physiological measures are commonly used to assess the driver's behavior [4], [18]. While vehicular data provide information about the execution of the driving task [65], physiological measurements like the frequency-domain measure of Heart Rate Variability (HRV) [23], Skin Conductance (SC), are valuable indexes to measure cognitive effort and workload [24].…”

Study on the Structural Configurations and Pressure Regulation Characteristics of the Automatic Pressure Regulating Valve in the Electronically Controlled Pneumatic Brake System of Commercial Vehicles

“…In the development of driving automation, the response time of the driver for external stimuli is crucial. Even though driving people have the same cognition and control ability, under larger mental loads or distracted, the driving operations may appear seriously out of control [1][2][3][4][5]. Therefore, in addition to the need for an optimized strategy for the response of the driver reaction time in an automated driving system, the automatic pressure regulating valve (APRV) as an actuator, its structure constructed for the safety of commercial vehicle driving, and the development of automatic driving is particularly critical.…”