Autonomous vehicle and automated driving technology is advancing rapidly, as evidenced by the increased number of vehicles on the road with these capabilities. More than 50 companies are testing vehicles with automated driving technology that can operate without interaction from the driver, including Tesla vehicles that have the hardware needed for limited or full self-driving under certain conditions. While the artificial intelligence of autonomous vehicles provides enhanced safety features for drivers, accidents will continue to happen as a result of driver error, vehicle error, or both.
Although some states have enacted legislation related to autonomous vehicles, consistent laws and regulations governing them are lacking. When litigating cases involving autonomous vehicle accidents, lawyers should be prepared to assess who, or what, is liable, and manage discovery of the plethora of electronic information that autonomous vehicles generate.
There are six levels of automation defined by the Society of Automotive Engineers and the National Highway Traffic Safety Administration:
Level 0 – no automation
Level 1 – driver assistance
Level 2 – partial automation
Level 3 – limited self-driving (conditional automation)
Level 4 – full self-driving under certain conditions (high automation)
Level 5 – full self-driving under all conditions (full automation)
Automated driving system (ADS) vehicles are those with the capability of driving without driver intervention under certain conditions, such as those classified as Levels 3–5. All autonomous vehicles include software that controls aspects of driving functions. Currently, most autonomous vehicles on the road are semiautonomous, which is any vehicle classified lower than Level 5 and which requires human operation in certain conditions. Semiautonomous vehicle features include parking assistance, emergency brake application, lane drift detection, and self-driving in certain conditions.
One of the benefits of autonomous vehicles is the data generated to monitor traffic and detect and respond to problems. Examples of data produced by autonomous vehicles include information about the operations of the vehicle itself, images generated from on-board cameras, data generated from sensors that identify where the vehicle is in relation to other objects, and the vehicle’s speed and direction.
As the number of autonomous vehicles on the road grows, there is an increased interest in generating autonomous vehicle policies and laws across the states. Currently, a federal framework for autonomous vehicle law does not exist, as the technology is advancing more quickly than the legal system can adapt. There is also a lack of state and federal codified standards and best practices to aid in responding to litigation claims involving autonomous vehicles.
The National Highway Traffic Safety Administration has provided guidance in support of automated vehicle technology, including technical assistance to states for consideration in drafting policies and legislation relating to ADS. As of June 2018, 37 states and the District of Columbia had enacted legislation or issued executive orders relating to autonomous vehicles. Some of the aspects being regulated include testing and deploying autonomous vehicles and whether a human operator must be present in the autonomous vehicle.
Each feature of autonomous vehicles brings potential discovery issues when an accident occurs and litigation ensues. For example, as a driver may disengage from an autonomous driving function, or the autonomous vehicle may not be familiar with local driving practices, an accident could be caused by driver error, vehicle error, or both. This aspect of discovery will help determine where liability should be attributed. In addition, the plethora of data created by autonomous vehicles provides more potentially discoverable electronic information, which may require expert interpretation. Lawyers should consider not only driver and vehicle behavior in autonomous vehicles as it relates to products liability lawsuits but also strategies for discovering electronic information to support those claims.
As most of the autonomous vehicles on the road require driver operation in certain conditions, accidents can be caused by driver error or vehicle error, alone or in combination. For example, drivers can disengage the autonomous driving functions or input commands to the vehicle that may violate traffic laws or otherwise disengage the safety features of the autonomous vehicle. Autonomous vehicle technology may also lead to drivers under- or over-trusting the vehicle’s capabilities, and confusion regarding whether the vehicle or the driver should be monitoring or engaging functions at a given point in time. This aspect of discovery will help determine where liability should be attributed and whether a plaintiff is pursuing claims of negligence against the driver of the vehicle or strict liability against the manufacturer.
When considering theories of liability in an autonomous vehicle case, lawyers should consider driver behavior in addition to the vehicle’s particular features. Increased trust in autonomous driving functions may lead a driver to neglect the driver’s monitoring responsibilities, resulting in the driver being unprepared to take control of the vehicle when necessary to avoid an accident. Autonomous vehicle driving systems can fail or become disabled. Thus, accidents involving autonomous vehicles may involve theories of liability relying on driver behaviors and vehicle factors, such as potential software or mechanical errors.
Autonomous vehicles generate an enormous volume and range of data relating to the operations of the vehicle, including images and videos recorded by sensors and cameras, speed and direction of the vehicle, and whether any software or mechanical systems were not functioning properly. With this volume of data comes potentially discoverable electronic information.
In cases involving autonomous vehicle accidents, the data is the vehicle’s version of the incident. Data generated by the autonomous vehicle’s sensors should be sought in discovery because it may be used to reconstruct precrash events and elucidate the cause of an accident without the use of an eyewitness. The data generated by the autonomous vehicle may qualify as self-authenticating, computer-generated information under Federal Rule of Evidence 902, if the record is concurrently submitted with a written certification from a qualified person. The data from autonomous vehicles may also streamline litigation by providing an easier method to authenticate key evidence.
Parties should anticipate having to deal with the struggles associated with understanding complicated technology. Expert discovery in areas of computer technology may be useful in litigation proceedings to explain the technology, the data, and the various components that work together to enable autonomous driving functions.
As autonomous vehicles become more available and widely used, so will the number of accidents involving them. Lawyers able to navigate the plethora of data autonomous vehicles generate will successfully litigate cases on behalf of their clients.
