A Fresh take on an Old Problem: Using Analytics to Gain New Insights into Ways to Reduce Fatal Motor Vehicle Accidents
Janel Nixon, PhD, President and Founder – Integrative Engineering LLC
Each year, 40,000 Americans die in motor vehicle crashes, making motor vehicle crashes the leading cause of death among Americans between the ages of 3 and 36. According to the U.S. Department of Transportation, the total societal cost of these crashes exceeds $200 billion annually. Despite these staggering statistics, many of these research efforts to date have failed to draw the sort of definitive conclusions that could potentially lead to beneficial policy changes or new regulation. Researchers have attempted to detect trends involving the driver’s age or gender, vehicle speed, time of day or month, or the weight of the vehicle. However, the primary shortcoming of these studies is that they all tend to view the vehicle in a vacuum – they look at the data associated with individual vehicles without accounting for the interaction that occurred between the vehicles that crashed with each other. This paper explores the hypothesis that individual vehicle characteristics are less important than the compatibility of the vehicles involved in the accident. It’s not so much the weight of a vehicle that’s important, but rather it’s the discrepancy in weight, center of gravity, and the delta in bumper height between the involved motor vehicles. This paper demonstrates how JMP is used to test this hypothesis, and to finally detect a trend that provides some new and valuable insight into this problem. It also stands as a case study for how analytics can be used across organizations to guide policy-making and new regulation in a way that delivers the maximum benefit to society.