THE AUTONOMOUS DRIVING SERIES: FROM SENSOR TO FLEET A camera sees a glare, a van hides a pedestrian, and the driver ahead brakes for no reason a machine can easily name. That late-afternoon intersection is ordinary, yet it contains everything that makes autonomous driving hard.

This series by Neil Carden maps that territory in three distinct stages — and it never pretends the hard parts are easy. The first book, Foundations of Autonomous Driving, starts at the physical layer.

Sunlight on a windshield, a delivery van hiding a pedestrian, a brake check that no rule book can encode — these are the ordinary moments every self-driving vehicle must survive. It walks through the Sense–Think–Act cycle, from cameras, radar, LiDAR, and drive-by-wire to sensor fusion, localization, prediction, planning, and the safety case that lets any of it leave the test track.

No deep ML background needed; you leave with the full stack in your head. The second book, Engineering Autonomous Driving Systems, is where the mental model becomes a working system.

It's written for engineers who know that a stack of accurate models can still fail when perception, planning, and control aren't coordinated under real-time pressure. You get ROS 2, Autoware,...