Human factors evaluation of the effectiveness of multi-modality displays in advanced traveler information systems

Liu, Yung-Ching; Schreiner, Christopher S.; Dingus, Thomas A. · 1999 · ROSA P / Turner-Fairbank Highway Research Center

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Summary

This study addresses the human factors design challenges of Advanced Traveler Information Systems (ATIS), specifically evaluating the effectiveness of multi-modality displays (combining visual and auditory information) compared to single-modality displays (visual or auditory alone). The research was motivated by the need to develop precise design guidelines for ATIS to ensure that the substantial information provided to drivers does not compromise safety or performance. The primary objectives were to determine under which circumstances multi-modality displays are beneficial and to identify the optimal single modality when multi-modality is not advantageous. The researchers conducted a driving simulator experiment involving drivers from two age groups: younger adults (18–25 years) and older adults (over 60 years). The experimental design manipulated four independent variables: display modality (auditory, visual, or multi-modal), driving load (low vs. high, defined by traffic density, road complexity, and lane width), and information complexity (simple vs. complex). Participants navigated simulated scenarios while performing secondary tasks, such as responding to warning information via button presses. Dependent measures included driving performance metrics (velocity variance, lane deviations, steering reversals), navigation accuracy (correct turns, missed turns), secondary task performance (reaction time, error rates), and subjective ratings of workload and preference. The results indicated that multi-modality displays generally yielded the best performance across multiple domains. For emergency response tasks, both multi-modality and auditory displays produced faster reaction times than visual displays, but the multi-modality display resulted in fewer errors than the auditory display. In navigation tasks, the multi-modality display achieved the highest rate of correct turns and the lowest number of navigation-related errors. Regarding driving performance, multi-modality displays supported better speed maintenance and safer driving behaviors, particularly under high driving load conditions. Subjectively, drivers rated multi-modality and auditory displays more favorably than visual displays in terms of workload and preference. The study concludes that multi-modality displays are superior for presenting critical, time-sensitive, or complex information, as they reduce driver workload and improve both navigation and driving safety. The authors propose five design guidelines: ATIS information should be kept as simple as possible (five or fewer items); if complexity is unavoidable, multi-modality displays should be used, especially in high-load situations; critical information requiring quick responses should always use multi-modality; multi-modality offers specific benefits for older drivers; and auditory cues should be used conservatively to avoid annoyance, reserving them for safety-critical alerts or status changes. These findings provide a foundation for optimizing ATIS interfaces to enhance mobility and safety.

Key finding

Multi-modality displays resulted in faster reaction times for emergency warnings, fewer navigation errors, better speed maintenance, and higher subjective preference ratings compared to visual or auditory single-modality displays.

Methodology

simulator

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• feedback modes
• road complexity
• multimodal feedback
• hud ar windshield
• haptic feedback
• mental demand
• multisensory crossmodal

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: design guidelines
• Empirical Findings: behavioral performance data
• Theoretical Contribution: theory or model