Introducing the Machine Intelligence Quotient: A new standard for evaluating autonomous vehicle intelligence

Researchers at Simon Fraser University have developed a groundbreaking Machine Intelligence Quotient (MIQ) framework aimed at redefining the assessment of intelligence in autonomous vehicles. The study, recently published in the journal of Artificial Intelligence and Autonomous Systems (AIAS), introduces a comprehensive methodology to quantify intelligence attributes across physical, cognitive, and functionality domains in vehicles.

The MIQ framework integrates multi-dimensional intelligence attributes, harmonizing them with human cognitive and decision-making processes to advance the design and functionality of future autonomous systems. By emphasizing the synchronization of these aspects, the MIQ provides a transformative approach that not only benchmarks intelligence but also fosters advancements that bring vehicle intelligence closer to human-like cognition.

"Autonomous vehicles are more than just transport mechanisms; they are platforms for innovation and intelligence," said Dr. Mehdi Cina, lead researcher of the study. "The MIQ framework is designed to provide a measure of intelligence of autonomous vehicles."

The development of the MIQ was inspired by the limitations of current evaluation metrics that focus narrowly on specific technical capacities without considering the vehicle's performance in dynamic, real-world scenarios. The newly proposed MIQ addresses these gaps by offering a robust metric that assesses a vehicle's intelligence as an integrated whole.

"MIQ sets a new standard in the field," added Prof. Ahmad Rad, co-author and the supervisor of the research. "It moves beyond traditional metrics to consider the overall adaptability, learning capability, and holistic integration of the vehicle’s systems, ensuring a comprehensive evaluation of intelligence in autonomous vehicles."

The practical application of the MIQ was demonstrated through a detailed case study involving the 2024 Hyundai Palisade. The study effectively applied the MIQ framework, providing tangible insights into the vehicle's intelligence capabilities across multiple categories. This application not only validated the framework but also showcased its potential to influence future designs and functionalities of autonomous systems.

This groundbreaking research paves the way for significant improvements in autonomous vehicle technology, with the potential to influence industry standards and consumer expectations. It also holds promise for enhancing regulatory frameworks by providing a standardized tool for assessing the intelligence of autonomous vehicles.

For further details about the MIQ framework and its implications for autonomous vehicle technology, please refer to the full article published in AIAS: Read the Article.

Cina M, Rad A, Rasuli AR. Developing a Machine Intelligence Quotient (MIQ) for evaluating autonomous vehicle intelligence: A conceptual framework. Artif. Intell. Auton. Syst. 2024(2):0007, https://doi.org/10.55092/aias20240007