Material Detail

This open-access educational module examines the kinematics, dynamic control, perception architectures, and multi-agent coordination of Autonomous Ground Vehicles (AGVs) and connected autonomous fleets.

Core Technical Topics

• Kinematics & Dynamics: Unicycle (differential-drive) and Ackermann bicycle steering models, coupled with tire-road lateral friction boundaries and slip angle dynamics.

• Path Tracking & Control: Stanley and Pure Pursuit lateral tracking controllers, alongside Real-Time Iteration (RTI) Model Predictive Control (MPC) deployment on automotive Electronic Control Units (ECUs).

• Perception & Sensor Fusion: Kalman filter multi-sensor fusion algorithms, and adverse weather perception strategies utilizing 4D imaging radar and thermal Long-Wave Infrared (LWIR) cameras.

• Behavioral Prediction: Human intent and trajectory prediction using Spatio-Temporal Graph Neural Networks (ST-GNNs) in complex pedestrian and traffic environments.

• Fleet Coordination & Security: Vehicle-to-Everything (V2X) communication frameworks and IEEE 1609.2 Public Key Infrastructure (PKI) cryptosecurity for distributed fleet management.

Pedagogical Assets

• 12 fully worked numerical engineering problems with complete mathematical formulations and step-by-step solutions.

• Interactive conceptual quick reviews and self-assessment checkpoints.

• Standardized cross-platform layout designed for undergraduate curriculum adoption and persistent academic reference.

Target Audience & Level Designed for upper-division undergraduate engineering courses (Automotive, Robotics, Mechatronics, and Control Systems), advanced university-preparatory STEM programs, and autonomous vehicle engineers.

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