Simulating autonomous driving styles: Accelerations for three road profiles

Abstract

Abstract. This paper presents a new experimental approach to simulate projected autonomous driving styles based on the accelerations at three road profiles. This study was focused on the determination of ranges of accelerations in triaxial direction to simulate the autonomous driving experience. A special device, known as the Automatic Acceleration and Data controller (AUTOAccD), has been developed to guide the designated driver to accomplish the selected accelerations based on the road profiles and the intended driving styles namely assertive, defensive and light rail transit (LRT). Experimental investigations have been carried out at three different road profiles (junction, speed hump, and corner) with two designated drivers with five trials on each condition. A driving style with the accelerations of LRT has also been included in this study as it is significant to the present methodology because the autonomous car is predicted to accelerate like an LRT, in such a way that it enables the users to conduct activities such as working on a laptop, using personal devices or eating and drinking while travelling. The results demonstrated that 92 out of 110 trials of the intended accelerations for autonomous driving styles could be achieved and simulated on the real road by the designated drivers. The differences between the two designated drivers were negligible, and the rates of succeeding in realizing the intended accelerations were high. The present approach in simulating autonomous driving styles focusing on accelerations can be used as a tool for experimental setup involving autonomous driving experience and acceptance.

Development of On-Road Automated Vehicle Simulator for Motion Sickness Studies

“…For that reason, the defensive AC driving style was selected for the validation study. The defensive AC driving style settings were implemented based on Karjanto et al (2017) on which the lateral acceleration was aimed to be at around 0.29 g or 2.84 m/s 2 while longitudinal acceleration was kept to a minimum. In addition, the driving wizard drove the Mobility Lab with a constant rate of acceleration and deceleration to mimic a driving style of a real AC (Baltodano et al, 2015).…”

“…Furthermore, the highest peak of the acceleration in the y-axis was almost ten times larger compared to the highest peak in the x-axis. The significant differences between the x-axis and y-axis amplitudes were anticipated as this study would like to simulate a defensive AC driving style based on the previous settings (Karjanto et al, 2017;Yusof et al, 2016). Furthermore, by visually inspecting both x-and y-directions (see Figure 3), there are several overlapped peaks of acceleration at different frequencies from the two driving wizards indicating that both drivers produced almost identical accelerations at the same frequencies.…”

“…Renault Espace IV is one of the cars that offer this kind of seat arrangement, and because of its smart railing system, a rearward seating is also possible and safe. A device called Automatic Acceleration and Data controller (AUTOAccD) that was developed and tested (Karjanto et al, 2017) to assist the designated driver in achieving the intended AC driving styles during the experiments was also implemented inside the Mobility Lab. AUTOAccD consisted of an Arduino board that was connected to an accelerometer.…”

“…Both the current and Griffin and Newman (2004a) studies had a similar condition in which drivers drove a suburban-type of the route with corners and junctions. However, in this particular study, the focus of the setup was limited and specified to defensive AC driving style with finite settings as defined by Karjanto et al (2017), while in their study they only defined it as "normal manner" driving style. Since the development of Mobility Lab is focusing on the user experience in the AC, the mean value of the MSDV y at both 6.68 and 7.29 ms -1.5 indicates sufficient motion to get people to experience MS.…”

Gaining Situation Awareness through a Vibrotactile Display to Mitigate Motion Sickness in Fully-Automated Driving Cars

“…To simulate FAD car riding experience, the driving wizard (DW) was implemented based on [32] with the help of a device called Automatic Acceleration and Data controller (AUTOAccD) [33]. The function of AUTOAccD was to guide the DW to induce a certain range of accelerations when simulating the FAD on the real road.…”