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New A.I. Patent Will Detect Aggressive Driving with Machine Learning

by Martin Anderson | Unite.AI

A recent patent application has proposed a system for identifying ‘aggressive driving behavior’ at junctions using machine learning algorithms deployed in civic edge computing devices.

In contrast to recent innovations of AI research into in-vehicle ‘road rage’ analytics (primarily intended for the benefit of insurance companies), the system proposed is instead municipal in nature, and could be aimed at facilitating penalties for drivers that are not conforming to the ambient norms of ‘safe’ driver behavior. It is also specifically intended to provide bad drivers with related in-car audiovisual alerts.

The patent was filed at the US Patent and Trademark Office on 29th April 2021 on behalf of the Board Of Regents of the University of Michigan, and the Denso corporation, a Japanese automotive components manufacturer owned by Toyota.

The UMich patent is not a proprietary, in-car system aimed at insurance oversight, nor designed solely to produce forensic data, but rather relies on well-resourced edge computing nodes deployed at traffic intersections to provide immediate and actionable feedback, by collating data from roadside edge computing resources and from sensors installed (presumably by law) in nearby vehicles. Source: https://pdfaiw.uspto.gov/76/2021/50/012/1.pdf

The UMich patent is not a proprietary, in-car system aimed at insurance oversight, nor designed solely to produce forensic data, but rather relies on well-resourced edge computing nodes deployed at traffic intersections to provide immediate and actionable feedback, by collating data from roadside edge computing resources and from sensors installed in nearby vehicles. Source: https://pdfaiw.uspto.gov/76/2021/50/012/1.pdf

The proposed framework is not entirely passive or dependent on civic equipment, but would also require in-vehicle technologies capable of turning cars into contributing sensors for the system. Effectively, this would turn every equipped vehicle into a traffic monitoring node, though the same oversight would also be turned on the driver themselves, with the additional benefit of access to the vehicle’s onboard data streams. The schematic for the in-car installation (pictured below right) submitted in the patent includes direct sensor data from the vehicles brakes, throttle, steering wheel and odometer, as well as requiring access to maps data.

Both the roadside and in-vehicle installations feature CUDA-enabled GPU and local storage resources, and both feature cloud connectivity.

Warnings For Aggressive Drivers

According to the patent application, the system is designed to interact with a fractious driver:

‘When the system for predicting aggressive driving behavior 1 predicts aggressive driving in a subject vehicle, a warning message such as the warning in FIG. 8A may be output to the audio visual device 413 in the subject vehicle to warn an aggressive driver to slow down.’

Additional potential warnings include in-car alerts for speed and oncoming vehicles:

Warnings depicted in the patent application. Source: https://pdfaiw.uspto.gov/fdd/76/2021/50/012/0.pdf

Warnings depicted in the patent application. Source: https://pdfaiw.uspto.gov/fdd/76/2021/50/012/0.pdf

The patent says that in another possible scenario, any available audio-visual devices (including smartphones owned by the driver) in the vehicle may be used to provide warnings, including audio warnings. Read Full Article >

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