  Cyclops, introduced in this paper, is an open research platform for everyone
that wants to validate novel ideas and approaches in the area of self-driving
heavy-duty vehicle platooning. The platform consists of multiple 1/14 scale
semi-trailer trucks, a scale proving ground, and associated computing,
communication and control modules that enable self-driving on the proving
ground. A perception system for each vehicle is composed of a lidar-based
object tracking system and a lane detection/control system. The former is to
maintain the gap to the leading vehicle and the latter is to maintain the
vehicle within the lane by steering control. The lane detection system is
optimized for truck platooning where the field of view of the front-facing
camera is severely limited due to a small gap to the leading vehicle. This
platform is particularly amenable to validate mitigation strategies for
safety-critical situations. Indeed, a simplex structure is adopted in the
embedded module for testing various fail safe operations. We illustrate a
scenario where camera sensor fails in the perception system but the vehicle
operates at a reduced capacity to a graceful stop. Details of the Cyclops
including 3D CAD designs and algorithm source codes are released for those who
want to build similar testbeds.
