From the 1 of 8 linked papers with an AI index.
8 papers
Weight Certificates for Convex Multi-Objective MPC: Geometric Characterization, Construction, and Foreclosure
Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +1
Automated-driving rulebooks rank rule violations lexicographically, and model predictive control enforces that ranking either exactly, through sequential programs per tick,…
From Operational Design Domain to Action: A Systematic Behavioral Taxonomy for Autonomous Driving
Chaitanya Shinde, Hadi Hajieghrary, Miguel Hurtado
Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe what the ADS must demonstrably do…
Importance Sampling and PCA for Finding Failures in Commercial Autonomous Vehicles
Hailey Warner, Duncan Eddy, Shreya Parjan +6
Methods for discovering rare failures in autonomous systems have so far been demonstrated almost exclusively in simulations with simple, academic driving stacks, leaving open wheth…
Real-Time Rulebook-Aware Nonlinear MPC for Autonomous Driving with Priority-Biased Tiered Slacks
Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +2
The paper introduces W‑SQP, a weighted tiered‑slack nonlinear model predictive controller that enforces multiple driving rules in real time while providing auditable per‑rule resid…
Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability
Chaitanya Shinde, Hadi Hajieghrary, Paul Schmitt +3
The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded in a human-driven vehicle par…
RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selection
Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +2
Autonomous driving stacks must pick one trajectory from a multi-modal candidate set; choosing by model confidence ignores safety, traffic-law, and comfort constraints. We present \…