American Journal of Mechanical Engineering, 2017, Vol. 5, No. 1, 18-23 Available online at http://pubs.sciepub.com/ajme/5/1/4 ©Science and Education Publishing DOI:10.12691/ajme-5-1-4 Driver Attention Based on Eye-movement and Time-series Analysis - Concept of Driver State Detection Devices Toshiya Arakawa * Department of Mechanical Systems Engineering, Aichi University of Technology, Gamagori, Aichi, Japan *Corresponding author: arakawa-toshiya@aut.ac.jp Abstract In this study, the transition of drivers’ states of attention from “excessive attention state” to “unfocused attention state” because of increasing time, existence of a leading vehicle, adaptability to driving conditions in different areas, such as urban or suburban environments, and decreasing tension was examined from the viewpoint of the drivers’ eye movements. The variability of the driver’s eye gazing was observed to gradually increase when a leading vehicle was present, i.e., the driver's process resource was concentrated on the leading vehicle at the beginning of the driving but on both leading vehicle and surrounding conditions before the end of driving. In addition, it was found that the difference between the unfocused attention state and excessive attention state was shown by the change in eye movement, depending on whether drivers were driving in urban or suburban areas. This shows that the driving conditions induced changes in the distribution of process resource. Keywords: driver attention state, eye gazing, eye movement, driving condition, process resource Cite This Article: Toshiya Arakawa, “Driver Attention Based on Eye-movement and Time-series Analysis - Concept of Driver State Detection Devices.” American Journal of Mechanical Engineering, vol. 5, no. 1 (2017): 18-23. doi: 10.12691/ajme-5-1-4. 1. Introduction Traffic-related accidents have been reported to have decreased in recent years; however, the accidents caused by “unfocused driving,” remain a major problem that cannot be overlooked despite the development and production of advanced driver assistance system. For example, one report stated that unfocused driving, i.e., when the driver is either distracted or falls asleep at the wheel, is the most significant factor contributing to fatal traffic crashes (661 cases), more than “inattentive driving” (459 cases) and “speeding” (212 cases) [1]. Thus, “unfocused attention” is often considered undesirable for drivers. When individuals continue driving for a long time, their attention span tends to decrease to a certain extent as they become accustomed to their surrounding conditions. This type of unfocused attention is considered to be desirable because it allows the drivers to give sufficient attention to objects in their surroundings compared with the situation when excessive attention is given by drivers with the objective of driving safely. Thus, the unfocused attention state can be considered to have two aspects; one that is appropriate for driving and another that is not. The second one can lead to a drowsy state because of decreasing tension. These states are expressed using a model, as shown in Figure 1. The left block shows the excessive attention state, wherein the driver is able to obtain all required information such as traffic lights, signs, and traffic flow. The central block shows the unfocused attention state, wherein the driver rationalizes his driving and after becoming accustomed to the surrounding conditions, tends to obtain the minimum information required for driving. The right block shows the “low arousal state,” which is caused by reduced tension; hence, is inadequate for driving purposes. Figure 1. Driver’s state during unfocused driving A driver visually obtains information from his surroundings and then processes it to control the vehicle. This is called “process resource,” [2] and it has also been reported in previous studies on this topic [3,4]. Furthermore, it has been stated that this process resource varies with the skill, attention, and effort of the driver and can be affected by a number of other factors despite being examined for the same driver [5,6]. It has been reported that there is a relation between eye-movement (which is the main method for visual input) and attention [7]. In this study, smooth pursuit and saccadic movements are used as components of eye movement. The smooth-pursuit eye movement occurs when the visual target moves smoothly and slowly with a maximum speed of approximately 30 deg/s. The characteristic of this type of movement is that drivers can perceive information without having to