Enhancing Autonomous Vehicles with Commonsense: Smart Mobility in Smart Cities
Recent advances in AI include a Law firm hiring a robot lawyer and companies developing autonomous vehicles with robot drivers. Findings from our study have gauged the current cognitive capacity of such systems, indicating areas for improvement. We focus on autonomous vehicles, i.e., those that conduct automated driving and need to make autonomous, i.e., independent decisions. We propose an approach enabled with commonsense knowledge (CSK) from worldwide repositories to simulate intuitive humanlike decision-making in autonomous vehicles. We consider the repository WebChild with a multitude of CSK concepts, properties and relations. We investigate this and related domain-specific knowledge bases (domain KBs) to harness them within our proposed approach. Accordingly we build a transportation domain KB incorporating CSK and the needs of autonomous vehicles. This would be useful in guiding automated driving and making the systems get closer to the thresholds of human cognition. This work thereby makes contributions to smart mobility in smart cities. The paper presents our vision with design, implementation, experiments, recommendations and a future roadmap. As a broader impact, it propels more joint work between AI, Law and related areas.
MSU Digital Commons Citation
Persaud, Priya; Varde, Aparna; and Robila, Stefan, "Enhancing Autonomous Vehicles with Commonsense: Smart Mobility in Smart Cities" (2018). Department of Computer Science Faculty Scholarship and Creative Works. 266.