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Michael Carey is trial lawyer with experience in complex commercial litigation and products liability defense. With his creative and authentic approach to jury presentation, Mr. Carey has taken numerous cases to successful verdict in state and federal courts across the country. In addition to his trial work, Mr. Carey has defended and prosecuted appeals before the Minnesota Appellate Courts and the Eighth and Ninth Circuits.

In addition to his trial and appellate practice, Mr. Carey serves as co-leader of the Firm’s Mobility and Advanced Transportation Team. He counsels mobility industry clients on proactive risk mitigation strategies relating to Automated Driving Systems (ADS) and other advanced automotive safety technologies. He is also frequently called on to publish and present on legal issues and advances in this emerging field.

Partnering with MICHauto and The Right Place, Dykema developed a five-minute flash survey to evaluate the current state of the automotive industry. Please click here to participate in the survey. The results will be analyzed to provide insight regarding the impact COVID-19 has had on businesses in the automotive industry. Dykema will also share feedback

The good news is that improved safety is far and away the predominant force behind development of advanced driving technologies. This is evident from the NHTSA’s latest Automated Vehicles 3.0, in which the word “safety” appears no less than 318 times. Industry has also prioritized safety as the race to commercialize autonomous driving technology will require, as a threshold matter, broad acceptance from the public in order to realize investment returns. Driverless vehicles promise other benefits too. The simple convenience of reading a book or taking a nap while commuting home from the office sounds wonderful. But until the technology is considered safe enough for our shared roads, such ancillary perks are merely hypothetical. 
Continue Reading Driverless Vehicles Will Be Here as Soon as They Are Safe Enough, but What Does That Actually Mean?

Currently, nearly all advanced automotive technologies operate under what are known as deterministic models. In a deterministic system, the outcome is dictated by a set of known initial conditions. These systems offer welcome predictability and repeatability. In contrast, probabilistic models yield different outcomes given the same initial condition, introducing an element of probability guided randomness. The latter model is considered necessary for autonomous vehicle functionality, but this is easier said than done.

Each model type has pros and cons. For starters, in the area of advanced automotive technologies, programming a deterministic model is more manageable. For example, automatic emergency braking systems are generally calibrated to recognize the rear of a preceding vehicle and apply braking when that vehicle slows and a crash is imminent. But how would that same system respond to a boulder rolling onto the roadway in the path of an equipped vehicle? The deterministic model is not well-suited for a curveball like this. The driver wants the same outcome – braking assistance – but the system only recognizes a certain set of predetermined conditions that do not include rolling boulders. 
Continue Reading Our Expectations for Advanced Vehicle Technologies are Outpacing the Technology