Dr. Hubele outlines the journey of a trained mechanical engineer Hugh DeHaven, from surviving a plane crash in 1917 to becoming the Father of Crashworthiness Research. His near-death experience inspired him to explore how airplane interiors could be better designed to protect occupants. The resistance he met while advocating for airplane safety helped to inform his later work in car safety. Most significantly, in 1942, DeHaven published an analysis of failed suicide attempts by individuals who jumped from tall buildings. He showed that lives could be saved in airplane and vehicle crashes when destructive forces were slowed and their impact blunted. The building blocks for making cars safer had been laid.

In this chapter, one key event highlights how data became critical to the car safety movement. Dr. John O. Moore of the Cornell ACIR group testified before a 1956 congressional hearing. He used creative infographics reproduced in this chapter to show how occupants’ body parts were being severely injured by certain vehicle components. He concluded his testimony with a list of ranked items to be fixed in cars, starting with the steering wheel. ACIR’s findings were cited over 100 times during the hearings and were used to create the first Federal Motor Vehicle Safety Standards that are still in effect today.

Dr. Hubele immerses the reader in the science and art of interpreting trends and patterns in car safety data. Simple graphs of fatality statistics show the declining counts in traffic deaths since the mid-1970s. Plus, easy to understand fatality rates, such as deaths per vehicle registered, deaths per licensed driver and deaths per miles driven illustrate the modern approach to data displays. Here, the reader learns to keep in mind that rates, especially those computed over long periods of time, are subject to social, economic, and marketing trends. Societal changes, from the number of female drivers to the types of cars we drive to the use of seat belts, can make it challenging to interpret fatality rate trends. Such complexity has helped to fuel the great car safety debates.

This chapter illustrates the role of data in a regulatory debate by focusing on the proposed federal standard for stronger vehicle roofs. The federal analysts argued that stronger roofs would save lives in rollover crashes. Car manufacturers disagreed. They believed that stronger roofs would make no difference in the fatality rates. In this chapter, Dr. Hubele uses illustrations and simple examples to show how the data were used to shore up the different points of view. Ultimately the federal government had to make a decision about the roof strength requirement.

In this chapter, Dr. Hubele explores the idea that the combination of driver behavior and vehicle size is a major car safety problem. Driver behavior may be rooted in the Peltzman effect, also known as the Gladiator effect. That is, do drivers of larger vehicles feel more protected and hence take more driving risks? When two vehicles of different sizes collide, data show that occupants of the smaller car die at a higher rate, sometimes 20 times higher, than occupants of the larger vehicle. Such risk inequality is called the vehicle incompatibility problem. Using past and recent research together with illustrations and simple graphs, Dr. Hubele discusses the attempts by our federal government to reduce this unequal risk on the road. However, the most recent data trends show that the problem may be increasing.

The Corporate Average Fuel Economy (CAFE) program is one of the greatest examples of the role of data in car safety debates. The federal government designed this program in 1975 to lessen U.S. dependence on foreign oil. CAFE required carmakers to increase the fuel economy of their vehicle fleets. To meet this new standard, carmakers made some cars smaller and lighter to balance out gas guzzlers. As cars got lighter, two renowned economists declared that fuel economy standards resulted in a “safety tax,” putting occupants in smaller cars at higher fatality risks. A fractious public debate occurred over the next 20 years with a major redesign of the CAFE program. Each side armed itself with a favored data set and analysis to argue for lessening or increasing the fuel economy of vehicles. In the midst of the movement to combat climate change and the emerging electric vehicle market, federal analysts recently declared that the newest CAFE standards no longer exacted a “safety tax.”

Dr. Hubele provides insight into the federal 5-Star Safety Rating system and the Insurance Institute for Highway Safety’s Top Safety Picks. This private consumer-facing system improves on the federal system by adding different, tougher criteria. Data show that carmakers work to meet these more difficult tests and use their rating to market their vehicles. Nevertheless, this chapter highlights the data-driven debate about the limitations of both of these systems. Dr. Hubele talks about vehicle incompatibility and common dummy models that fail to represent female and senior body types. Due to the long process and expense of improving the federal program, Dr. Hubele suggests that the federal program should be reduced or eliminated. Furthermore, the safety rating system, Auto Grades, presents a more realistic ranking of how well vehicles protect drivers in real crashes.

In this chapter, Dr. Hubele describes the role of data in two prominent recall debates: the rear-mounted fuel tank in Jeep SUV’s and Tesla’s sudden unintended acceleration. Both sides of these debates used data to support their positions. And, in the end, the federal analysts had to make a decision to recall the vehicles or not. Using actual stories of owners’ experiences, Dr. Hubele illustrates the evolving problem of data in the recall process of modern, highly electronic vehicles.

A 2005 NHTSA study found that “drivers’ actions or inactions led” to a crash 94% of the time. Does it then make sense to use computers to prevent these errors? Automated driver-assistance systems, or ADAS, aim to do just that. ADAS include things like forward-collision warning, lane change/merge guidance, and road departure alarm systems. In this chapter, Dr. Hubele traces the 60-year journey of one such system: forward-collision warning. In spite of evidence that this technology could potentially prevent 51% of all rear-impact crashes, the industry was very slow to offer this life-saving device to car buyers. Finally, NHTSA issued a data-backed ultimatum in 2016. Either carmakers could voluntarily make rear-impact prevention technology standard on all future cars or face a new regulation. Twenty manufacturers signed a voluntary agreement to widely introduce the technology by 2025. Dr. Hubele uses stories and simple graphics to show the human-impact of this foot-dragging approach to reducing human error.

The self-driving car industry promises that its vehicles will eliminate human error and prevent crashes. In this chapter, the reader learns that when companies remove the human driver from behind the wheel, data move in. Sometimes data's role is to accelerate progress. Sometimes it taps the cautionary brakes. Autonomous vehicle advocates use data to boast that their cars complete billions of miles of training and testing without incident. Detractors use data from highly-publicized crashes of semi-autonomous vehicles to assert that these cars are unprepared for the road. But the debate does not end there. Numerous federal reports raise other questions, from issues of cybersecurity to data ownership. And who is responsible when a crash occurs? Dr. Hubele describes how each issue needs to be addressed and how data will undoubtedly be used by all sides to defend their positions. She predicts that it will be decades before society knows if the self-driving industry can deliver on its promise to completely remove the human driver from our roads." after the last word "brakes.