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Our Work

Project Gallery

We strive to share as much or our research as possible, with the hope the automotive industry can benefit from the findings of our safety advances. Explore our projects, and discover what we work on.

Surrounding Environment Recognition Technology and Evaluation Metrics

Active Safety, Crash Avoidance, Projects

Develop a deep learning based full-scene recognition of vehicle environment from a vision sensor. Examples are vehicles, pedestrians, bicyclists, traffic signs, buildings, curbs, etc.

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Computer analyzed image of the road objects.

Development of Testing Methods for Vehicle Road Departure Assist Systems

Crash Data Analysis/Data & Analysis, Projects

By analyzing over 25,000 high resolution images available on Google Street View across the country, we were able to determine that grass, metal guardrail, concrete divider and curbs are the most common roadside boundary objects.

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Photo of a city with busy traffic at night.

Integrated Benefit Estimation

Crash Data Analysis/Data & Analysis, Projects

Estimate the Residual Safety Problem after Integrated Safety Systems (ISS) are deployed in the future. ISS consists of all active (auto braking for vehicle, pedestrian, bicyclist, lane keeping, etc.) and passive safety systems (advanced airbag, curtain shield airbag, roof strength, pedestrian protection active hood, etc.).

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Photo of a stop light in a busy city.

A Systems Approach to Interactions Between Driving Automation and People

Crash Data Analysis/Data & Analysis, Projects

Provide theoretical and mathematical framework of how drivers communicate at an intersection.

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Photo of woman having a relaxing car ride.

Naturalistic Observations and Simulation of Communication Between Road Users

Human Technology Integration, Human Factors, Projects

Identify what kind of communication we have with other road users (e.g., pedestrians, other vehicles) with cutting-edge technology of computer vision.

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Man sitting in the passenger seat of a vehicle with his seatbelt on.

Non-Driving Occupant Posture and Activities in Moving Vehicles

Human Factors, Projects

The objective of this project was to increase the scientific understanding of typical front-seat passenger postures through a naturalistic study observing in-vehicle behaviors.

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Photo of person using the driving simulator.

Motion and Muscle Activation of Young Volunteers in Evasive Vehicle Maneuvers

Human Factors, Projects

The objective of this study was to quantify key adult and child occupant kinematic, kinetic and muscle responses from sudden evasive vehicle maneuvers. This data is useful to develop future tools to better assess injury risk in crashes preceded by crash avoidance.

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Photo of person riding bike in traffic.

Development of Standard Bicyclist Crash Scenarios

Crash Data Analysis/Data & Analysis, Projects

Naturalistic driving data was collected from 110 drivers over the course of a year capturing vehicle telematics data and camera footage, to better understand how bicyclists and cars interact and identify dangerous events.

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Photo of driver abruptly stopping.

Passenger Response to Abrupt Evasive Maneuvers

Human Factors, Projects

This study observed volunteer passengers experiencing unexpected abrupt evasive maneuvers, including hard braking and swerving. Our goal was to understand passenger responses to abrupt vehicle maneuvers, to inform the development of onboard safety systems.

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Driver Modeling in Transfers of Control From Conditional Automation

Human Factors, Projects

We conducted a naturalistic driver study to understand how drivers interact with automated systems in everyday commuting, examining periods where a driver is likely to be highly vigilant along with incidents where driving task may be in low demand.

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