San Mateo, CA, United States of America

John Douglas Logan


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: John Douglas Logan: Innovator in Autonomous Vehicle Testing

Introduction

John Douglas Logan is a prominent inventor based in San Mateo, CA (US). He has made significant contributions to the field of autonomous vehicles, particularly in the area of fault injection testing. His innovative techniques are designed to enhance the safety and reliability of autonomous systems.

Latest Patents

Logan holds a patent for "Autonomous vehicle fault injection testing." This patent describes techniques for simulating faults associated with vehicle components. The process involves a computing device that receives an indication to simulate a fault, which is coupled to the vehicle component via a control line. The device can activate a relay or switch to simulate the fault and gather data on the vehicle's response. This includes measuring the vehicle's trajectory and assessing whether backup systems functioned correctly in response to the fault. The computing device then determines the difference between the actual vehicle response and the intended response relative to a threshold difference.

Career Highlights

Logan is currently employed at Zoox, Inc., where he continues to develop innovative solutions for autonomous vehicles. His work focuses on improving the safety and performance of these vehicles through advanced testing techniques. With a patent portfolio that includes 1 patent, Logan is recognized for his contributions to the field.

Collaborations

Some of Logan's notable coworkers include Andrew Scott Crego and David Martins Belo. Their collaboration fosters an environment of innovation and creativity, driving advancements in autonomous vehicle technology.

Conclusion

John Douglas Logan is a key figure in the realm of autonomous vehicle innovation, with a focus on fault injection testing. His work at Zoox, Inc. and his patented techniques contribute significantly to the safety and reliability of autonomous systems.

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