The main cause of traffic accidents is drivers' human errors such as cognitive, judgment, and execution errors. To mitigate errors, research on the measurement quantification driver workload well development smart vehicles needed. Drivers' behavior while driving includes straight, turning left or right, U-turns, rapid acceleration, deceleration, changing lanes. measure quantify a workload, both subjective caused by varied behaviors should be taken into account basis understanding visual,...

Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy however challenging, given multitude circumstances surrounding drivers, unique traits individuals, and computational constraints imposed by embedded platforms. Prior work fails jointly meet these runtime/accuracy requirements mostly rely on a single...

If the automated vehicle fails to drive automatically, human driver must control vehicle. So far, drivers have had little experience of taking over during driving and there is a lack research how they react in this situation. This paper analyzed drivers' TOR reaction time when are switching manual response take-over request (TOR) while performing non-driving secondary tasks. The results show that need different reflective depending on tasks thus consider type TORs based status driver.

Cognitive models and empirical studies of problem solving in visuo-spatial causal domains suggest that tasks such invoke cognitive processes involving mental animation imagery. If these internal are externally manifested the form eye movements, present situations which trajectory a user's visual attention can provide clues regarding his or her information needs to an Attentive User Interface [Vertegaal 2002]. In this paper, we briefly review research related involves imagery, describe...

Driving is an essential activity in today's busy and complex society, it demands physical mental abilities, collectively known as a driving workload. For safe comfortable driving, would be useful to detect when drivers are being overloaded. Analyzing driver's workload using electroencephalograph (EEG) for this purpose. However, very inconvenient obtain EEG during actual since the measuring device needs attached driver. In paper, we develop model predict level utilizing basic information...

This study investigates the influence of Non-Driving Related Tasks (NDRTs) on subjective driver readiness and take-over performance in level 3 automated driving system, effect driver's performance. A simulator was used to measure system-initiated transition situation while performed different NDRTs. The results demonstrate that NDRT has a significant influences performance; negative correlation with time, contrary, positive vehicle control quality. influenced resulting participants' We...

A variety of methods used to measure a driver's workload do not include information such as the characteristics and attitudes. subjective driving prediction tool (DWPT) was developed overcome this limitation. The purpose study is validate DWPT, which composed three subfactors: situational inadaptability, risk-taking personality, interpersonal inadaptability. For reason, we conducted simulator experiment gather drivers' behaviors. path scenario included various tasks. Thirty male drivers...

In the case of level 3 automated vehicles, in order to safely and quickly transfer control authority rights manual driving, it is necessary that a study be conducted on characteristics human factors affecting transition driving. this study, we three experiments compare influence driver’s quality response when re-engaging stabilizing The were sequentially by dividing them into normal driving situation, an obstacle occurrence situation front, congestion surrounding roads. We performed...

The aim of this study is to find out whether the provision situation awareness (SA) information effective in reducing transition time that control authority transited from automated driving manual driving. In level 3 automobile, driver must remain a fallback ready state which he/she can drive at any time, so human factor driver's SA required. Thirty-six drivers licensed performed three experiment scenarios with an feature activated. Participants were asked enter some sentence his/her...

Risk management in dynamic decision problems is a primary concern many fields, including financial investment, autonomous driving, and healthcare. The mean-variance function one of the most widely used objective functions risk due to its simplicity interpretability. Existing algorithms for optimization are based on multi-time-scale stochastic approximation, whose learning rate schedules often hard tune, have only asymptotic convergence proof. In this paper, we develop model-free policy...

Driver's role in automated driving depends on the stage. It is important to transmit vehicle control authority between driver and system at SAE Level 2 3. Therefore, a readiness model required evaluate judge of driver. In this paper, we proposed estimator (DRE) that can perform function determining analyzing whether switch from automatic manual drive. near future, will implement out DRE be tuning optimized for driver, since ability health status individual are different.

IoT (Internet of Things) is a core technology hyper connected society that connects and interacts with all things, spaces environments in the real world. Recently, has evolved into edge computing enhances data processing analysis by decentralizing power was performed central cloud to an end device. Since structure suitable for manufacturing environment requiring real-time fast response, many studies have considered as optimized platform constructing smart factory. Therefore, we design...

With the proliferation of vehicles and advancement information technology, technology telematics, which provides valuable services to people by collecting analyzing from drivers, Telematics environments (e.g. traffic information, road condition, weather etc.), has been a hot research area in IT automotive recently. There are needs for telematics makes more profitable. based insurance could be one possible business model. In this paper, we have investigated trends industry discussed required...

This paper presents a driver status recognition method based on data fusion that changes the autonomous driving mode in our co-pilot system. Our research has following two novelties: first, of information-based driver-status between direct using states driver's face and eyes an indirect patterns vehicle information; second, ability to transfer from through information methods. Four parameters are calculated these methods: percent eye closure, gaze direction, steering wheel angle, speed....

From the statistics about rental car accidents, traffic accident death by drunken driving, speeding, and centerline invasion occurs frequently to twenties drivers compared with other age groups. Specially, speeding is a dangerous driving behavior. In this paper, we analyzed characteristics of young middle-aged using FOT (Field Test) data which was collected on real urban, local road highway. We performed independent samples t-test know difference time, average speed maximum dependent ages...

Abstract Level 3 autonomous vehicles require conditional driving in which and manual are alternately performed; whether the driver can resume within a limited time should be examined. This study investigates demographics subjective tendencies of drivers affect take‐over performance. We measured analyzed reengagement stabilization after request from system to using vehicle simulator that supports driver's mechanism. discovered correlated with speeding wild tendency as well workload...

We observe and analyze the characteristics of control authority transition according to driver's age gender in a highly automated vehicle driving environment this paper. made scenarios performed experiments using simulator. experimented five tasks such as No NDRT, Conversation, Drink, Texting Movie. measured time it took driver take when takeover request (TOR) occurred analyzed data an independent sample t-test. According gender, TOR times showed significant differences some tasks....

Although various wearable devices are being used as essential tools for mental health analysis, the accuracy of data from these is still controversial. In this paper, we acquired four types (Empatica E4, Samsung GalaxyWatch3, Polar Verity Sense, H10) and compared HRV features such HR, SDNN, RMSSD, LH/HF, etc. Additionally, correlation between RR Interval (RRI) values ECG PPG was analyzed.

The aim of this study is to investigate the cognitive workload characteristics which can be applied human factors that are switching operation control in autonomous vehicles. For purpose, we analyze test driver's EEG and driving data measured while on real roads find out difference state according behaviors Urban Road. We performed a paired sample t-test using preprocessed between normal ratio overload behavior. also k-means clustering see if drivers could divided into groups status behavior...

Autonomous vehicles have recently attracted considerable attention as a new type of transportation system that can improve convenience and quality life. However, current versions autonomous still require human intervention in specific situations, certain situations the driving mode must be switched from to manual. It is difficult determine whether driver readiness perfect at moment which because lack concentration tension. A amount time required recover stable state after taking over...

Car manufacturers are developing conditionally automated driving vehicles that sometimes require a driver''s control. There is lack of research on reaction when switching from automatic to manual operation. This paper analyzed drivers'' experiences and workload after drive in response take-over request (TOR) while performing non-driving secondary tasks. The results show drivers experience different depending the tasks thus need generate TORs.

This work represents the heuristic experiments and results of transition performance from automated driving to manual in terms modality channel usage for take-over request (TOR). The are designed with dependent measurements independent conditions. Statistical analysis is performed obtain claims about TOR.