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Abstract
VALIDATION STRATEGIES FOR HD MAP-DRIVEN SUPER CRUISE DEPLOYMENT IN GENERAL MOTORS VEHICLES
Mohammed Sharfuddin*
ABSTRACT
General Motors’ Super Cruise is a state-of-the-art hands-free driving system that relies heavily on high-definition (HD) mapping for safe and accurate vehicle automation. This paper presents a comprehensive validation framework developed to support the recent expansion of Super Cruise’s HD map coverage from 400,000 to approximately 750,000 miles, encompassing both primary and secondary roads in the United States and Canada. The validation strategy focuses on sensor fusion accuracy, lane-level precision, and real-world scenario testing. Leveraging Dynamic Map Platform North America’s (DMP) centimeter-level HD map accuracy, including over 450 roadway features, this framework aims to ensure consistent Super Cruise performance across diverse driving environments. Key contributions include methodologies for segment-based validation, integration of multi-sensor data, and scalable testing protocols. The paper also discusses the challenges of validating autonomous driving on rural and secondary roads. The study draws upon prior work on HD map data optimization, scalable data monitoring, and enterprise process improvement strategies to reinforce validation robustness.
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