Recent advances in Artificial Intelligence raise interest in its participation in design activity, which is commonly considered to be complex and human-dominated. In this work, we aim to examine AI roles in early design stages. The human ideation components and design tools related to AI are discussed in a framework of AI-augmented design support. The framework develops a hierarchy of design cognition (basis), approaches and principles. The cognitive models are constructed in an empirical study of 30 designers (26 for analysis, 4 for pilot study) by concurrent Think-Aloud protocol and behavior analysis. The process of producing new design ideas is explained by a transparent analysis of designers’ language and behaviors. Three strategies to organize cognitive activities in design ideation are summarized: develop structured consideration, relate to a scenario, and stick-to designing. These strategies suggest AI could act as (1) representation creation, (2) empathy trigger and (3) engagement, in principles of “knowledge-driven” and “decompose-and-integrate”. The design support with AI provides new perspectives on computer-based design tools that limit to well-defined design variables. The framework is built on a generic notion of design activity and “mimic” human design rationales, expected to benefit research of domain-independent computational design supports and cognitive supports.

The vibrotactile modality has great potential for presenting takeover requests (TORs) to get distracted drivers back into the control loop. However, few studies investigate the effectiveness of directional vibrotactile TORs. Whether TORs should be directed toward the direction of hazard (stimulus-response incompatibility) or the direction of avoidance action (stimulus-response compatibility) remains inconclusive. The present study explored the impact of directional vibrotactile TORs (toward-hazard, toward-action, and non-directional) on takeover performance. The influences of TORs lead time (3 s, 4 s, 6 s, and 8 s) and non-driving related tasks (NDRTs) (playing Tetris games and monitoring the road) on the effect of directional TORs were also probed. A total of 48 participants were recruited for our simulated driving study. Results showed that when drivers were engaged in NDRTs during automated driving, directional TORs were more effective than non-directional TORs. Specifically, at the lead times of 6 s and 8 s, both toward-hazard and toward-action TORs could shorten steering response times, compared with the non-directional TORs. At the lead times of 3 s and 4 s, toward-action TORs were more beneficial, as the maximum lateral acceleration was smaller than toward-hazard and non-directional TORs. However, when drivers monitored the road during automated driving, no obvious difference existed between directional and non-directional TORs, regardless of how long the lead time was. The findings in the present study shed light on the design and implementation of the tactile takeover system for automobile designers.