Lucas Buckland
CEO & Co-Founder at BOVI.TECH
United States
Summary
👤
Senior🎓
Top SchoolLucas Buckland is a vehicle autonomy leader and serial founder with 12+ years of hands-on experience designing and productionizing autonomous controls for on- and off-road platforms. As CEO and Co-Founder of BOVI.TECH and formerly VP of Engineering at Designated Driver, he blends executive strategy with deep embedded-systems expertise—especially CAN bus and low-level vehicle control for steering, throttle, braking, and gear systems. His work on the widely used Apollo open autonomous driving platform includes implementing Gem controller protocols and signal logic, reflecting both practical product delivery and open-source collaboration. Across roles at PolySync, AutonomouStuff, and TrackR he moved research projects into production, halved vehicle build times, and significantly improved embedded power and RF designs. He holds an M.S. in Electrical and Electronics Engineering from UC Santa Barbara and is known for reverse-engineering production vehicles to enable robotic integration—bringing a pragmatic, hardware-oriented approach to autonomy challenges.
8 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.) Electrical and Electronics Engineering, Master of Science (M.S.) Electrical and Electronics Engineering at UC Santa Barbara
English, Japanese
Github Skills (9)
can-bus10
embedded10
c-language10
cprogramming-language10
sys10
apollo9
protocol-buffers8
autonomous-driving8
self-driving-car7
Programming languages (2)
Github contributions (5)
ApolloAuto/apollo
Apr 2018 - Apr 2018
An open autonomous driving platform
Role in this project:
Embedded Systems Engineer / IoT Developer
Embedded Systems Engineer / IoT DeveloperContributions:24 commits, 9 PRs, 7 comments in 18 days
Contributions summary:Lucas's primary contributions focused on developing and modifying control functionalities for a vehicle's CAN bus system, specifically targeting the Gem controller. The user added and updated protocol files, enabling the controller to interface correctly with the chassis. Furthermore, the user implemented and modified control features related to steering, throttle, braking, and gear shifting and incorporated turn signal functionality, thus refining the core interaction logic of the vehicle.
autonomousmachine-learningautonomyautonomous-drivingapollo
lbucklandAS/image_pipeline
May 2018 - Aug 2018
Contributions:2 pushes, 1 branch in 3 months
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