Application - Solution Overview + Alignment

Solution Name

One-line solution summary:

Smart roadside cameras leverage machine learning to detect distracted drivers and enforce hands-free driving laws.

What specific problem are you solving?

Distracted Driving and use of cell phones while driving is the #1 problem in transportation safety. It’s the new drunk driving, causing 1.5 million car crashes, 800,000 injuries and over 6,000 deaths each year in the USA alone. It costs the U.S. economy $180B/year. Globally it causes 10 million injuries and 240,000 deaths per year. The National Transportation Safety Board ranks “Eliminate Distracted Driving” on their ‘2021-2022 Top Ten Most Wanted List’, and highlights enforcement as key to achieving this goal. 24 U.S. states have “hands-free” distracted driving laws, with a simple visual test to detect violations. These laws are difficult to enforce manually ‘by eye’ at highway speeds. 

There are equity challenges in traffic safety and traffic enforcement. The most common reason for contact with the police is being a driver in a traffic stop. Bias is a public concern. BIPOC citizens die far more frequently in traffic crashes than others. 2020-2021 were the worst years for traffic fatalities since 2006-2007, with 42,060 deaths in 2020 despite Americans drove 13% fewer miles. 2021 has had 18% higher fatalities. During 2020, Black Americans experienced a 23% increase in traffic fatalities

There is a need for equitable, scalable solutions.

Pitch your solution.

The solution is a smart camera system with machine learning, analogous to a ‘speed enforcement camera’ or ‘red light camera’ for distracted driving. The camera can be mounted on an overpass or the roadside. The system observes passing vehicles and automatically detects hands-free distracted driving violations. Evidence of violations are captured in video or still images in a secure, encrypted evidence package for use in traffic court.  Traffic safety experts state an unmet need for evidence of violations, admissible in court. Data privacy is built into the center of the system. Sworn enforcement personnel can review the evidence, confirm violations, and issue tickets via mail.

Broad adoption would reduce distracted driving, make the roads safer for all users, and reduce the cost of traffic enforcement, crashes, and the number of police encounters. In addition, the NTSB and Governors Highway Safety Association highlight automated systems as key to equitable traffic enforcement.

Explain why you selected this stage of development for your solution.

  • We have demonstrated a working prototype camera system and machine vision pipeline, and have demonstrated image capture and identification of distracted drivers in real-world settings on highways and roads. 

  • Completed engineering feasibility studies. 

  • We are actively working on pilot deployments.

  • We have conducted extensive (150+) customer discovery interviews with multiple stakeholders in traffic safety: police, DOTs, traffic safety advocates, legislators, and federal and local government. Stakeholders emphasize the need for the technology and are eager for an on-road demonstration and pilot projects. They state “I want it, and I need it now”.

  • We recently won a contract to conduct additional technology research and development.

Our solution's stage of development:

Prototype: A venture or organization building and testing its product, service, or business model

Where are you based?

Boston, MA, USA

Solution Team

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