The Levels of Autonomous Vehicles
From navigation and infotainment systems to new sensing technologies such as cameras and radar, the reliance on microprocessors and computer chips has become common in today’s vehicles. The abundance of computer chips in modern vehicles has made them as essential as aluminum, steel, and plastics. Automakers have harnessed the advanced processing power and sensing capabilities of these chips to usher about a new era in advanced driver assistance systems (ADAS).
ADAS features have been around for decades and date back to the early 1970’s when anti-lock braking systems (ABS) were first introduced in passenger vehicles. The trend that computing power is on the rise is demonstrated clearly by Moore’s Law which shows that the number of transistors on a computer chip has doubled about every two years. A corollary to Moore’s Law is that the cost of computing power has become less expensive over time. Despite this decrease in cost, a recent Deloitte analysis indicated electronics are responsible for nearly 40 percent of a new vehicle’s total cost. This highlights the integral role microprocessors and chips play in the auto industry.
Many modern vehicles come standard with a package of new safety features including systems such as automatic emergency braking (AEB), blind spot monitoring, lane keeping assist, and adaptive cruise control. Automakers such as Tesla, GM, and Ford have packaged these features together under trademarked names such as Autopilot, Super Cruise, and BlueCruise. Under specified circumstances, some of these active safety systems can operate without needing the driver to keep their hands on the steering wheel. Currently, there are no Federal Motor Vehicle Safety Standards (FMVSS) that address these driver assistance systems.
The Society of Automotive Engineers (SAE) has published SAE J3016 – Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles to provide insight on the role of the driver (human) when a driving automation system is engaged. This vehicle recommended practice outlines the six levels of automation and whether or not the driving automation is manual, executed with driver support, or is completely autonomous. SAE Levels 0, 1, and 2 require the driver to be actively driving while these driver support features are engaged. A driver must be ready to brake, accelerate, or steer as needed to maintain a level of safety. Distinguished from the levels below it, an SAE level 3 system is able to safely operate under certain conditions without requiring the driver to monitor the roadway or remain engaged in the driving task. It is important to note that a level 3 system does require an able driver to be present in the driver’s seat and be prepared to take back control of the vehicle when conditions change. SAE Levels 4 and 5 require no driver involvement and execute the driving tasks autonomously.
Dr. Daniel Wolfe is a Senior Forensic Scientist specializing in the reconstruction of motor vehicle, pedestrian, and bicycle collisions. He specializes in collisions involving nighttime recognition and conspicuity issues, including headlight mapping of vehicles, illumination from roadway lighting, and nighttime photography. He is certified as a BOSCH Crash Data Retrieval (CDR) technician, and is experienced in documenting evidence utilizing three-dimensional laser scanning. He is also accredited as a Traffic Accident Reconstructionist by the Accreditation Committee for Traffic Accident Reconstruction (ACTAR #3532).
Graphic courtesy of: SAE International Surface Vehicle Recommended Practice, “Taxonomy and Definitions for Terms Related to Driving Automations Systems for On-Road Motor Vehicles”, SAE Standard J3016, Revised 2021-04-30
