Comparison of manual vs Comparison of manual vs. speech-based interaction with in-vehicle information systems Jannette Maciej, Mark Vollrath Accident Analysis and Prevention 41 (2009) 924–930

Introduction The National Highway Traffic Safety Administration estimates that approximately 25% of the accidents in the years 1995–1999 which were registered by the police were due to inattention of the driver. Secondary tasks add to the mental workload of the driver and which will probably further increase distraction.

Chisholm et al. (2008) found a significant increase of reaction time to several hazards while selecting a specific song in an MP3 player. Reed and Robbins (2008) conducted a simulator study to investigate the impact of text messaging while driving.

From multiple resource theory, speech-based human–machine-interaction should be much better suited while driving because this taps different resources than driving. Speaking and listening may also impair driving (for an overview, see Horrey and Wickens, 2006).

A direct comparison of the effect of device control via speech and via display and manual control during car driving is required.

Method- Driving task This study used the Lane Change Task (LCT, Mattes, 2003) to evaluate the distraction caused by the different in-vehicle information systems (IVIS). The driver sees a straight section of a three-lane road and is instructed to keep the current lane while driving at a constant speed of 60 km/h.

One trial consists of 18 lane changes in a random order (left vs One trial consists of 18 lane changes in a random order (left vs. right, movement across one lane vs. movement across two lanes) and takes about 3min. lane-keeping- SDLP lane-changing- reaction time was measured from the point where the sign became legible to the point where the driver started to steer.

The lane change was assumed to begin 30m before each sign and to take 10 m -mean deviation. Besides the three driving parameters described above (SDLP, reaction time, mean deviation), gaze behavior and subjective distraction was measured after each condition.

Method- Secondary task anMP3-player hands-free car kitwas used which could either be operated by touch screen or via speech. First navigation system(12操作，6視覺確認，多輸 入次數) Second navigation system(6操作，2視覺確認，單 輸入次數)

In the first task, the subjects had to enter specific points-of interests (POI) in several cities. In the second task the drivers had to enter an address.

Method- Subjects The subjects were 30 drivers (16 male, 14 female) 有一個最後放棄 The age ranged from 19 to 59 with a mean age of 33.2 (SD = 11.9).

Method-Experimental design For the experiment a within-subjects design was used. Each subject did every secondary task (audio, phone, navigation system address and point of interest), manually and via speech interface while driving the LCT which adds up to eight conditions. A ninth condition the second navigation system was included for address entry with the speech interface, only.

Results

Discussion This experimental setting was very well able to demonstrate the strong distraction effect caused by the manual control of the different systems. This was mainly due to visual distraction as 30– 40% off-the-screen glance time show.

Speech interfaces improved driving performance for all systems with the exception of point-of-interest entry in the navigation system. POI task 需要多次視覺確認。 These improvements were not strong enough to reach the baseline performance level in all parts of the driving task.

Speech control clearly reduces the visual distraction introduced by manual control of different systems typically used in the car. They estimated that these secondary tasks substantially increased the risk of a critical situation or an accident. As this study was conducted in a laboratory, drivers were not exposed to the same risk as on an actual road.