Academic journal article Human Factors

Imperfect In-Vehicle Collision Avoidance Warning Systems Can Aid Drivers

Academic journal article Human Factors

Imperfect In-Vehicle Collision Avoidance Warning Systems Can Aid Drivers

Article excerpt

INTRODUCTION

Intelligent transportation systems (ITSs) are increasingly becoming technically feasible and economically affordable (Lee, 1997; Walker, Stanton, & Young, 2001). Unlike in-vehicle safety systems such as air bags and safety belts, which focus on injury reduction, many new in-vehicle systems now focus on accident prevention by providing assistance to the driver during the driving task. One such driving aid is an in-vehicle collision avoidance warning system designed to alert the driver in instances of unsafe headway to a lead vehicle.

With automated driver aids, the twin issues of the impact on driver performance and user acceptability of imperfect aiding devices are increasingly important. There is good reason for caution in the use of devices that alert drivers. An alerting signal can potentially distract or annoy the driver, causing degradation in driving performance. This is especially true for a system with a high false alarm rate (Parasuraman, Hancock, & Olofinboba, 1997; Parasuraman & Riley, 1997). False alarms require allocation of attention by the driver to a situation that would ordinarily not demand attention. At best, it is annoying to the driver; at worst, the false alarm can distract the driver from real hazards. The driver can also choose to disable the system, rendering it useless.

Several recent studies on various aspects of similar systems have concluded that drivers are more cautious when using warning systems than when driving without them and that they consequently drive more slowly and maintain longer headways (e.g., Ben-Yaacov, Maltz, & Shinar, 2002; Burns, Knabe, & Tevell, 2000; Dingus et al., 1997; Shinar & Schechtman, 2002).

The degree to which the reliability of the warning system affects the driver's usage of the system is therefore a critical issue. In one study, false alarm rates of up to 60% were found to influence younger drivers, leading them to drive with shorter headways as the number of false alarms increased, whereas older drivers were not thus affected (Dingus et al., 1997). In cases of missed alarms, overreliance on a warning system can be hazardous; even experienced drivers can show overreliance (Young & Stanton, 2000). The cutoff point in system reliability at which the system ceases to be helpful or has adverse effects has not yet been established. In this study, we aim to further the knowledge base in the quest to define usability and acceptability of warning systems at various reliability levels.

Although it is easier to study certain driving situations in simulators rather than on the actual road, researchers are justifiably cautious when relating driver behavior in simulated scenarios to on-road behavior. The distinction between the two reflects the difference between maximal and typical behavior (Naatanen & Summala, 1976). In most experimental situations it is difficult to elicit typical behavior, and instead the driver's "best" behavior, relative to the task demands, is obtained. This shortcoming is not limited to driving simulators but extends to all studies in which the drivers are voluntary participants who are aware of the task demands and the fact that they are being measured. This limitation leads some researchers (e.g., Kiefer, 2000; Lee, McGehee, & Brown, 2000) to question some simulator studies as tools to predict driving behavior. Nevertheless, most researchers acknowledge that because of the flexibility in experimental design and creation of desired conditions, simulator studies are still beneficial in measuring various aspects of actual driving behavior (Lee et al., 2000; McGehee, Mazzae, & Baldwin, 2000).

A recent study tested the utility of an in-vehicle collision avoidance warning system (IVCAWS) on the road (Ben-Yaacov et al., 2002). It was found that the system enabled the drivers to estimate headway more effectively, that errors by the device did not impair user performance, and that the drivers' newfound headway estimation ability persisted for as long as 6 months (the maximum duration evaluated). …

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