Role of Intelligent Transpiration System (ITS) in Attention Allocation

Seeking information is the key element of attention allocation. Providing information to drivers is to help drivers drive more safely and easily. Technology advancement makes it easier for drivers to obtain real-time traffic information and is supposed to make driving safer. However, different information affects drivers differently. It is important to understand the characteristics of information and its impact on driving safety. Otherwise, distracting drivers’ attention to information systems would lead to less control on driving tasks and situational awareness (Thompson et al. 2012).

ITS is an integrated system composed by techniques of computer, electronic engineering, communication, information and sensing to enhance transportation safety and efficiency (Praveen et al. 2005, Smith and Venkatanarayana 2005). Considering that the primary contribution of ITS is the real-time information while driving, the following discussion of information characteristics and the impact on attention allocation will focus on the category of real-time information. There are three types of ITS safety systems: route information, warning and automated control.

(1) Route information

Goal of providing route information to drivers is to improve the driver’s understanding of traffic situations and their influences on driving. From a user perspective, providing more information is to support decision-making and thus reduce driving tasks (Brookhuis and de Waard 1999, Creaser et al. 2007).

Gathering real-time information enhances driver’s controllability about the journey and allows them to pre-allocate their attention resources to deal with future traffic conditions (Vashitz et al. 2008).

Real-time information is usually provided through In-Vehicle Information System (IVIS) or Variable Message Sign (VMS). Most VMS provide information and operation suggestion in accordance to the demand of general driving population under certain environment conditions. Al-Ghamdi (2007) conducted experiment of fog warning system which detect of visibility and adjust the speed limit through VMS. Results showed that real-time information provided by VMS

can effectively change drivers’ driving behavior. Intersection Decision Support (IDS) is another application of VMS which assists drivers’ decision making of entering the stop controlled intersection (Laberge et al. 2006, Creaser et al. 2007, Neale et al. 2007). By collecting the data of traffic flow on the main lane and estimating the time to collision, IDS can provide the operation suggestion whether it is safe to enter the intersection or not.

Other than the providing information through VMS, IVIS can further customize and personalize information in accordance to individual drivers’ needs, such as route navigation, traffic jam, weather, traffic flow conditions, accident prone site and other business application. Several research indicated that the use of IVIS can increase the driving safety by enhancing the controllability of driving (Boyle and Mannering 2004, van Driel et al. 2007, Vashitz et al. 2008).

Accidents in long tunnels are more serious even though the frequency is comparatively low. Driving in a long tunnel induces more mental workload than driving in normal conditions. In order to enhance the communication between tunnel traffic control and drivers, tunnel IVIS is used to provide route navigation, speed limit, location of emergency events and closest emergency exit (Vashitz et al. 2008). Advanced Driver Assistance is another application of IVIS (van Driel et al. 2007). Through the collection of traffic flow data, the Advanced Driver Assistance is able to provide information of traffic jam to drivers. By telling drivers the location of upcoming traffic jam or the distance that drivers might take to pass the traffic jam, Advanced Driver Assistance can mitigate the negative impact of driver’s frustration if they are already in the jam. The system also allows drivers to change routes if they are not in the jam yet.

Previous research indicated that drivers prefer the route information system which can provide more information. However, shifting attention from driving task to the information perception and comprehension may induce distraction (Liang et al. 2007, Vashitz et al. 2008). Issue of information overload should be seriously concerned.

(2) Warning

The second type of ITS safety information is the warning system which aims to remind and attract driver’s attention for critical event or threat to safety.

There are two major kinds of warning systems.

The first system is the Vehicle Collision Warning System (CWS).

Conventional CWS use vehicle sensors mounted on the subject vehicle to search for obstacle and measure the distance between subject vehicle and threads. When

vehicles or other obstacles enter the defined dangerous zone, the system would inform driver and give operation recommendation (Shaheen and Niemeier 2001, Vahidi and Eskandarian 2003, Praveen et al. 2005, Tan and Huang 2006, Maltz and Shinar 2007). Recently, Cooperative CWS (CCWS) was proposed. Rather than using sensors on subject vehicles to identify the risks, such system works relying on the communication between subject vehicles and other vehicles around. Each vehicle on roads is equipped with self-sensing system to obtain its own driving state, including position, speed and acceleration/deceleration.

Besides, communication devices mounted on each vehicle send and receive those driving state which can be used to calculate related position, speed, angle and time to collision to surrounding vehicles (Tan and Huang 2006, Polychronopoulos et al. 2007). However, current development of CCWS faces several limitation and difficulties. First, not every vehicle or obstacle on roads is capable of cooperative devices. Any objects without CCWS can be seen as black hole of information and serious thread of safety (Tan and Huang 2006).

The second system focuses on the maneuver of drivers. Take speed control for example, in order to keep speed under the legal limit, drivers have to check speedometer frequently. To decrease the task of checking speed and to prevent unconscious speeding, Manual Speed Alerting (or Electronic Speed Check, ESC) is adopted to collect speed limit from roadside equipment or GPS and to alert drivers when the speed exceeds limit (Young and Regan 2007, Marmeleira et al.

2009). Furthermore, considering the fact that drivers can access to enormous information, shifting attention may cause distraction and fail to perceive critical information. Feedback mechanism of IVIS and distraction Alert is proposed to warn drivers when frequency and duration of glance is higher than the acceptable level (Donmez et al. 2007).

(3) Automated control

Purpose of automated control system is to exclude human factors from driving. Two major functions of automated control systems are assistance of driving tasks and restriction of dangerous behaviors.

Automated Highway System (AHS) aims to reach the goal of “hands-free”

and “feet-free” driving (Vahidi and Eskandarian 2003). Core technique of AHS is Advance Vehicle Control System (AVCS), which is consisted of Adapted Cruise Control (ACC) and steering control. ACC is designed to control speed at design level and to slow down automatically when lead vehicle decelerate. Despite of the speed control, automated lateral control relies on the detection of lane mark

(Young and Regan 2007). Owing to the automated control of each vehicle in the platoon, no lane changing or passing are allowed. Speed variance, which is seen as a major contributing factor of accidents, can be decreased to a very low level since all vehicles are set to drive in the same speed. AHS can effectively enhance operation safety and efficiency on highways (Carbaugh et al. 1998, Vahidi and Eskandarian 2003, Young and Regan 2007).

The other form of automated control systems is similar to the function of warning system. Instead of warning drivers to decelerate or avoid collisions, automated control systems overrule drivers’ maneuver and operate vehicle to safety conditions. Take speed alert for example, Intelligent Speed Adapter (ISA) not only provide warning of speeding, but also decrease speed automatically (Molin and Brookhuis 2007, Young and Regan 2007). Moreover, Emergency Lane Assists (ELA) is the extension of CWS and Rear Proximity Warning System which remind drivers to avoid collision with other vehicles (Eidehall et al. 2007). ELA is a new concept of lane guidance system which aims to prevent dangerous lane departure. By monitoring vehicles on adjacent lanes and the position of lane mark, a torque is applied to the steering if the lane-change maneuver is considered as dangerous behavior. Only when the adjacent lane is safe for lane-changing, ELA will allow vehicles to cross the lane mark.

In the ideal conditions, without intervention by human, drivers only have to consume attention resource to monitor the driving operation when using automated systems. As long as the systems are function properly, the level of attention demand can be maintained in a very low level without compromising safety. However, the successful adaptation of automated system relies on the drivers’ acceptability. Previous research showed that drivers have high acceptability of ITS device except the automation system which has the function of overrule drivers’ maneuver. Drivers claimed that such systems remove the power of controlling vehicles from drivers (Molin and Brookhuis 2007, van Driel et al. 2007, Young and Regan 2007). Instead of being controlled by systems, drivers prefer to obtain more information from route information and warning systems (Marell and Westin 1999, Donmez et al. 2007, Young and Regan 2007, Vashitz et al. 2008, Bruyas et al. 2009). The final decisions are mostly decided by drivers (Al-Ghamdi 2007).

Despite the difference in information content and complexity, different ways to display and present information might influence drivers differently. Visual display is usually adopted in route information systems that driver must attend to. Location of visual information is critical. It is suggested that the visual distraction have great

concern to risk perception than auditory distraction and is difficult to adjust (Hatfield and Chamberlain 2008). To minimize the distraction of visual information, (Neale et al. 2007) indicated that the visual information should be located near driver’s central and peripheral vision where they usually focus on while driving.

Other than the route information systems, auditory and haptic approach is the better way to display the warning information (Maltz and Shinar 2007, Neale et al.

2007). However, content of information is limited in auditory ITS systems. The auditory information should be short and clear enough of drivers to perceive and comprehend efficiently (Maltz and Shinar 2007). The reasons which visual display is not suitable for warning system can be discussed in two folds. First, drivers would rather put their visual attention on the road for situational awareness than focusing on the visual warning of conflicting traffic. Second, the warning messages are usually appear unexpectedly. Without continuously monitoring the system, drivers may not have the chance to perceive that information even though the visual warning systems provide alerts. Focusing on the monitor for visual warning may create more serious dangerous (Neale et al. 2007).

While information is generally beneficial, improper use of it can gain negative effects. Only providing the proper information to right driver at the proper time and place can exert positive effects and reduce accident risk. Complex laws proposed by (Elvik 2006) state that accident risks are increased with the information drivers must attend to during a given unit of time. Moreover, side effects of information should also be considered. Drivers influenced by multiple sources of information are more likely to be distracted and miss critical information. Therefore, information overload will not help drivers and may even cause serious problems by distracting them. To prevent negative effects resulting from interference of ITS systems or other sources, analyses of information optimization and allocation is crucial for future ITS development and application (Verwey 2000).