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Roads of Tomorrow: A Journey through Intelligent Transportation Systems

5/31/2024

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Case Study: Smart Intersection

 
Application Name:
Smart infrastructure monitoring and analytics using LiDAR, camera, and radar sensors.
2D, 3D, and 4D visual sensors enhance safety by monitoring the behaviors of mobility users and providing analytics at intersections, arterials, highways, and toll roads along critical infrastructure.
​

About Sensagrate
Sensagrate is a computer vision software company that provides traffic AI solutions on the edge to bring state-of-the-art innovation solutions that provide real-time, predictive analytics data to decrease congestion and emissions and improve public safety. SensaVision intelligent transportation system (ITS) products include computer vision software, computer vision on the edge, and traffic and safety data and analytics.

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5/31/2024

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Case Study: Pedestrian Behavior Monitoring

 
City of Scottsdale - Scottsdale Rd and Camelback Rd
Key Achievements:
  • See the final report for reference. Go to pages 12 through 43 for the report for the City of Scottsdale. https://www.scottsdaleaz.gov/Assets/ScottsdaleAZ/Boards/Transportation/agendas-minutes/2023-Agendas/03-16-23-regular-agenda-packet.pdf
  • To perform the pedestrian analysis, we identified counts of pedestrians and their movements at the intersection, including the crosswalk waiting area, time in the crosswalk, and assessed safety using near-miss collision analysis. It was critical to identify if pedestrians were experiencing any safety concerns. 
  • This data helps understand the correlation between real-life crashes and near-miss collisions to help validate the overall traffic safety trends. Real-time analytics enables proactive assessment of an intersection's health and safety within a short timeframe, rather than waiting for patterns to emerge over 1 to 5 years. 

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5/31/2024

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Case Study: Highway Monitoring - Counts, CO2 Emissions and Congestion

 
Case study report coming soon.

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5/31/2024

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Case Study: Near-Miss Collision Analysis

 
University of California, Los Angeles

In January 2025, Sensagrae extended its license agreement with UCLA to provide our computer vision AI camera software to provide real-time traffic and safety analytics. Our SensaVision Edge solution, which connects to 4 Axis Communication cameras and a NVIDIA Jetson device, provides real-time data and analytics. UCLA’s Transportation Department uses the near-miss collision data and analysis to gain insights into engagements between vehicle-to-vehicle, vehicle-to-non-vehicle, and non-vehicle-to-non-vehicle events. 

Key Achievements:
  • Provide proactive insights to safety events from near-miss collisions and wrong-way driving.
  • Provide a digital twin simulation to recreate the events of the near-miss for the customer to review. 
  • Provided a feedback loop to allow the customer to verify near-miss collision events and allow a human-centric element for the customer to approve events and provide feedback on their expectations of how they classify near-misses from their perspective. 
  • Actionable Insights: Automated process for near-miss collision events and recommendations from, USDOT’s Federal Highway Administration (FHWA), Highway Safety Programs, Proven Safety Countermeasures initiative (PSCi) for signalized intersections. This data enables customers to review countermeasure recommendations, identifying solutions to implement and reduce near-miss collision events. 

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5/31/2024

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Case Study: E-Scooter Monitoring and Behavior Analysis

 

Darryl Keeton

Founder and President of Sensagrate

View my profile on LinkedIn
In 2022, a university in Los Angeles wanted to identify the use of e-scooters on campus. The university banned e-scooters because of the challenges and issues when launched by the mobility sharing apps. 
Picture
Key ask: detecting e-scooter paths and behaviors

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