Visual Monitoring of Driver Inattention

Abstract

The increasing number of traffic accidents due to driver inattention has become a serious problem for society. Every year, about 45,000 people die and 1.5 million people are injured in traffic accidents in Europe. These figures imply that one person out of every 200 European citizens is injured in a traffic accident every year and that around one out 80 European citizens dies 40 years short of the life expectancy. It is known that the great majority of road accidents (about 90–95%) are caused by human error. More recent data has identified inattention (including distraction and falling asleep at the wheel) as the primary cause of accidents, accounting for at least 25% of the crashes [15]. Road safety is thus a major European health problem. In the “White Paper on European Transport Policy for 2010,” the European Commission declares the ambitious objective of reducing by 50% the number of fatal accidents on European roads by 2010 (European Commission, 2001). According to the U.S. National Highway Traffic Safety Administration (NHTSA), falling asleep while driving is responsible for at least 100,000 automobile crashes annually. An annual average of roughly 70,000 nonfatal injuries and 1,550 fatalities results from these crashes [32, 33]. These figures only cover crashes happening between midnight and 6 a.m., involving a single vehicle and a sober driver traveling alone, including the car departing from the roadway without any attempt to avoid the crash. These figures underestimate the true level of the involvement of drowsiness because they do not include crashes at daytime hours involving multiple vehicles, alcohol, passengers or evasive maneuvers. These statistics do not deal with crashes caused by driver distraction either, which is believed to be a larger problem. Between 13 and 50% of crashes are attributed to distraction, resulting in as many as 5,000 fatalities per year. Increasing use of in-vehicle information systems (IVISs) such as cell phones, GPS navigation systems, satellite radios and DVDs has exacerbated the problem by introducing additional sources of distraction. That is, the more IVISs the more sources of distraction from the most basic task at hand, i.e., driving the vehicle. Enabling drivers to benefit from IVISs without diminishing safety is an important challenge. This chapter presents an original system for monitoring driver inattention and alerting the driver when he is not paying adequate attention to the road in order to prevent accidents. According to [40] the driver inattention status can be divided into two main categories: distraction detection and identifying sleepiness. Likewise, distraction can be divided in two main types: visual and cognitive. Visual distraction is straightforward, occurring when drivers look away from the roadway (e.g., to adjust a radio). Cognitive distraction occurs when drivers think about something not directly related to the current vehicle control task (e.g., conversing on a hands-free cell phone or route planning). Cognitive distraction impairs the ability of drivers to detect targets across the entire visual scene and causes gaze to be concentrated in the center of the driving scene. This work is focused in the sleepiness category. However, sleepiness and cognitive distraction partially overlap since the context awareness of the driver is related to both, which represent mental occurrences in humans [26]. The rest of the chapter is structured as follows. In Sect. 2 we present a review of the main previous work in this direction. Section 3 describes the general system architecture, explaining its main parts. Experimental