Transportation planning has long pursued enhanced accessibility—the potential to reach destinations—and mobility—the realized quality of travel. Advances in data science, artificial intelligence, and autonomous vehicles have expanded these goals through predictive modeling, real-time optimization, and new transport modes. Yet growing emphasis on local accessibility and slow mobility, as in the 15-minute city and machizukuri, highlights the importance of well-being, social connection, and sustainability in the context of transportation. Theories on the benefits of inconvenience and Rosa’s resonance suggest that unlimited accessibility may erode meaning by removing effort, surprise, and unpredictability. Hence, future planning must balance optimization with human-centered values. Our workshop aims to further three specific goals:

• Establish mathematical frameworks and guarantees for unreliability.

• Distinguish “good” from “bad” unreliability and quantify the long- and short-term impacts. 

• Consider contemporary methods from machine learning and AI for improving traveller experience.