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Engaging in non-driving related activities while traveling in a moving vehicle is known to induce motion sickness symptoms, such as nausea and vomiting. According to the sensory conflict theory, enhancing situation awareness by giving information about the outside situation of the vehicle to the passengers is proven in reducing these symptoms. A visual modality prototype was developed to enhance situation awareness while performing non-driving related activities. This prototype has an overlapping view function that enables users to read and at the same time view the front view of a moving vehicle. This study was done to assess the most suitable opacity and text size of the reading material of the prototype. Twenty-two (22) participants participated in a fixed-base driving simulator study. A pre-recorded video of a journey was played on the simulator screen while the participants were engaging with the prototype. A rating scale (range from 1 to 5) and User Experience Questionnaire-Short (UEQ-S) (range from -2 to 2) were used in the study. The result shows that the opacity at 70% and the text size at 120% received the highest average score at 3.45 and 3.50, respectively. The UEQ-S shows a positive result with a 1.08 or above-average benchmark on the overall scale. The findings from this study encourage this prototype to be further tested on the real-road vehicle for future works. [ABSTRACT FROM AUTHOR]

A fully automated vehicle (AV) is projected to free users from driving activities. However, motion sickness (MS) is expected to be experienced by the users when engaging in Non-Driving Activities (NDRAs) such as reading, and watching a video because they will be exposed to low-frequency movement that contributes to the development of motion sickness. This study analyzed the difference in users' ride comfort when traveling in an AV in a real-road situation. The Wizard of Oz method was implemented for the participants to experience fully automated driving. The study was divided into three stages: pre-, during, and post-driven, to measure the user's comfort, safety, likeness, and motion sickness level through self-report questionnaires. Three conditions of NDRA consisting of baseline (doing nothing), reading, and watching a video were tested among the young participants (18 to 28 years old, Mean=21.4, Standard Deviation=2.84). Statistical analysis showed a statistically significant difference between the three different NDRAs. Reading imposed the highest experienced MS followed by watching a video and doing nothing. Understanding ride comfort in AV riding is vital in designing an AV that makes the passenger enjoy the ride without any discomfort feeling (motion sickness), especially when engaging in any NDRAs. [ABSTRACT FROM AUTHOR]

This paper discusses the interaction between a pedestrian and autonomous vehicle during crossing the zebra lane by using inference statistical analysis. In this study, a video-based experiment was carried out at the university campus. On a straight road, two Perodua Myvi were utilized to test vehicle behaviour (yielding, non-yielding), driving style (assertive, defensive), and vehicle appearances (autonomous, manual) over distances of 100 m, 75 m, 50 m, and 25 m. The driver is dressed in a suit that hides the driver to signify that the driver is invisible to the pedestrian. Sixty-six (66) individuals were shown either manually or automatically operating the vehicle. Participants were asked to rate their decision to cross the road when the vehicle approached at the pre-defined distances. According to the findings, the vehicle's driving style and appearance has no substantial impact on participants' willingness to cross the zebra lane. For both automated and manually driven vehicles, the vehicle's behaviour had a considerable impact on pedestrians' willingness to cross a road. There was also no statistically significant (p>0.05) three-way interaction between vehicle behaviour, driving style, and vehicle appearance. There was no statistically significant (p>0.05) simple two-way interaction between vehicle behaviour and driving style. Finally, the experiment's limitations were reviewed, followed by recommendations for future study. [ABSTRACT FROM AUTHOR]

This paper aims to classify Malaysian drivers' driving styles (DS) using the Multidimensional Driving Styles Inventory (MDSI). Previously, an MDSI study was performed in Malaysia but was not carried out using the native language. In this study, 430 respondents participated, and the MDSI data were analyzed using exploratory factor analysis (EFA). The Malaysian driving style profile distribution was then determined using the three methods: sum scores by the factor, weighted sum scores, and Barlett's method. Besides, the differences between the sociodemographic variables for the proposed driving styles were also reported. The results revealed five Malaysian driving style factors: careful, risky, angry-impatient, dissociative, and anxious. The sociodemographic variables' results significantly affect careful, risky, angry-impatient, and anxious driving styles. This study indicates that Malaysian MDSI provides valid measures and useful instruments to classify the types of driving styles in Malaysia. [ABSTRACT FROM AUTHOR]