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Abstract. Prior researchers indicate that mental load is one of the most important contributors to a traffic accident. The aim of the paper is to investigate the impact and the correlation of road condition and driving experience on driver's mental workload. The driving test consists of 3 road complicity situation (urban road, highway, rural road) with 26 drivers with average 21 years old in different experience level (average 4.08 years' experience). NASA TLX questioner is used as subjective driver's mental load measurement with three dimensions relate to the demands imposed on the subject (Mental, Physical and Temporal Demands) and three to the interaction of a subject with the task (Effort, Frustration, and Performance). There are 3 cameras placed on the left side, right side and front car to identify the road condition. According to experiment, it was found that drivers felt that frustration level, business, and mental-demand factors dominate the impact on high-level workload (96.15%). Highway road conditions provide an average overall workload score of 62 (OWS) which was better compared to city road (OWS = 69) and rural road (OWS = 66). Based on street complexity, it is necessary to improve road conditions that resemble highway road by reducing potential hazard. Keywords: Mental driving workload, NASA TLX, Overall workload score (OWS) I IntroductionDriving is main human activity which is conducted to support daily activities and mobility in the shortest time possible. This initiated large government investment in providing safe and convenient transportation system. The driving complexity causes road accidents, not only due to physical factors such as cars and road conditions but also due to human factors themselves such as human error and excessive stress levels. Fastenmeir and Gstalter [1] research define that the complexity of driving depends on elements such as road design (highway, rural road, city road), road layout (straight, curved, inclined, junction) and traffic flow (high density). The study of the situation and the pattern of the relationship between drivers with cars and driving environments in order to reduce or avoid possible risk. The driver's ability to meet driving needs becomes an important capital in realizing safety driving [2]. The ability to adapt quickly, such as reducing speed, changing the direction of the vehicle is very much dependent on driving experience and mental condition (load) of the driver.Schlegel [3] defines driving workload as the total amount of resources or driver's ability to achieve a driving task. Further driving workload reflects the driving need to achieve performance tasks that depend on individual drivers and skills. Driving workload depends on the task (demand, complexity, and difficulties), drivers (age, fatigue, abilities, experience, etc.) and environment (dynamic/changing, familiar, etc.). Total driving workload consists of every aspect relating to driving task and nondriving task [4]. Driving tasks consist of street monitors making lateral/longitudinal ac...

The multiple crashes in Indonesia are categorized into a frequently occurring accident, which often causes death. The aim of this paper is to examine the driver psychophysiology during braking in response to the vehicle in the front, which is varied. The research was initiated with a literature review regarding the electrooculography (EEG), safe braking distance, Emotive Epoc+, and Central Nervous System (CNS). The research was initiated with a literature review regarding the Electroencephalography (EEG), safe braking distance, Emotive Epoc+, and Central Nervous System (CNS). Research design with direct driving experiments on the road is used to analyze what happens to the driver's brain when braking at a certain distance (psychophysiology factor). The collected sampling data are from 4 male healthy drivers with the age between 20 - 40 years and average driving experience of more than 5 years. The measurement of brain activities into a spectrum of colors and Emotive BCI 16 electrodes through the performance matrices was conducted for the existing condition and condition suitable with the safety distance permitted. Experiments have been tested in 4 different road conditions of residential road (speed <30Km/h), city road (speed <50Km/h), rural road (speed <80Km/h) and motorway (speed <100Km/h). Safety distance measurement used standard data with residences road = 10m, city road = 29m, rural road 73m, and motorways = 115m. Results of brainwave signal have been recorded by Emotive Epoc Brain Activity map and Emotive BCI matrix and have been used to analyse the driver’s psychophysical. The findings show that the level of stress in the existing condition is very wherein for the braking in the densely populated residence = 87, urban areas = 83, intercity = 76, and motorways = 60. In contrast, following the safety distance rules have successfully reduced mental stress to average 47 as proofed by lower beta signal especially on occipital lobe (vision function) and on frontal lobe (attention function). Improper infrastructure such as narrow road at heavy residential damaged driver relaxes and increased stress level as indicated by increasing brain signal significantly. Meanwhile, driving while concerning the safety braking distance psychophysiologically through the identification of brain activity will be able to lower the driver’s stress and fatigue level.

A driver's mental and physical states while driving on hazardous roads significantly determine the incident of traffic accident. The objectives of this paper are to analyze the impact of road complexity on the psychophysiological load experienced by drivers through the use of Electroencephalography (EEG). Three conditions were examined through driving simulation, namely motorway, rural road, and city road. The data were collected from three respondents (drivers) who had different driving experiences, including < 3 years, 3 to 5 years, and > 5 years. Besides, each respondent would go through two tests with different situations: a normal situation and interfered situation (noises). The tool used was Emotive EPOC neuroheadset with 5 channels (electrode) which represent brain parts, such as the frontal (AF3 and AF4), temporal (T7 and T8), and parietal/occipital Pz. The simulation test results show that the beta signal for the motorway road situation in the occipital lobe, which functioned as visual, is more dominant compared to electrodes in other parts. Meanwhile, data from the rural road and the city road indicate a strong signal of emotions and visuals. In addition, based on the metrics performance result, the drivers' level of stress reached its highest on the city road, as much as 45, followed by the rural road = 44 and the motorway = 42. While for the concentration index, the city road achieved 47, the rural road = 50 and the motorway = 53. EEG can be used as the basis for drivers performance assessment within different road situations so that the alert system for drivers can be engineered better.

SUMMARYEfforts to advance brain computer interface (BCI) to aid people who have lost communication and movement abilities (neuromuscular disorders) are becoming popular and are obtaining funding from many Institutes. But it has remained untapped in other areas e.g. manufacturing, the military, the law, etc. Hence, the aim of the project is to investigate the impact of environmental sound (noise & music) on human thinking using the Electroencephalography (EEG) tool. The project is started with a subject literature review and then concentrates on the investigation of the kind of BCI signals and how EEG works. The information will be analyzed and classified to serve as references in the analysis of environmental noise level and music. The project is divided into two scenarios of treatment: the noise -silent -noise -silent form and the second treatment using noise -the silent -musicnoise form. The next step is measuring and then analyzing the brain signals in a variety of sound levels. In this state, the comparisons of impact sound from two treatments are presented. Finally, the project shows that the music sound treatment produces a stable graph of brain response when compared with the noise sound treatment. As a consequence, people within pleasant sound will be more relaxed and focused on doing the task.