Bootstrapping as a Means to Assess Driving Styles of Adaptive Cruise Control Users

• Activity Number: 651
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Social Statistics Section
• Author(s): Linda Ng Boyle and Huimin Xiong*+ and Jane Moeckli and Timothy Boyle
• Companies: University of Washington and University of Washington and University of Iowa and University of Iowa
• Keywords: Bootstrapping ; driver behavior

Abstract

Bootstrapping is a statistical tool based on a resampling procedure. It has been successfully used in situations when large sample sizes cannot be achieved or when a theoretical distribution is unknown. This was observed in a study of use patterns related to Adaptive Cruise Control (ACC). Although ACC is available in many high-end vehicles, the number of participants who are active users within one system type is still relatively small and gathering drivers for such a study can be a challenge. However, these early studies are essential to assess the safety of ACC for future users. In a study using a motion-based driving simulator, 23 drivers were partitioned into three cluster groups based riskiness. The bootstrapping sampling technique was used to assess differences in trust and driving styles among the clusters. The findings suggest that the safety consequences of ACC use was quite different across drivers groups and were indeed related to trust and driving styles. The most risky drivers tend to have relatively high trust and aggressive driving styles.