"Do as I say": Analysis of In-vehicle Assistant Command Pattern Differences between Germany and Mexico

In-vehicle assistants (IVAs) are moving from fixed command grammars toward large language model (LLM) driven conversational agents, where the quality of the system’s response depends heavily on how the driver phrases the request. Yet we know little about how drivers actually formulate spoken commands, and almost nothing about how this varies across cultures and languages. We present the design and motivation of PromptDrive, a web-based, remote, unattended driving-simulator platform that elicits spoken command utterances under three priming styles (Direct, Goal-based, and Contextual) delivered through a simulated head-up display. We ran a cross-cultural, multilingual pilot study with university students in Germany and Mexico, assembling a trilingual (German, Spanish, English) corpus of command utterances for two vehicle functions, navigation and climate control. In this work we frame the cross-cultural IVAs prompting problem, situate it in prior work on cross-cultural HCI, and prompting, and motivate why command-phrasing patterns may differ systematically between a German and a Mexican driver population. We report preliminary observations from 30 participants and 383 utterances: priming style shifts how drivers phrase requests, with Direct cues yielding the shortest commands and Goal-based cues the most specific, while retrospective workload did not differ across styles and drivers preferred the Direct framing. Because the achieved sample fell short of the planned size and the cells are unbalanced, these results are exploratory; the paper’s primary contributions are the conceptual framing, the elicitation protocol, and evidence that the platform supports unattended multilingual collection at a distance.