Assessing Driver’s Trust, Compliance, and Reliance in an Automated Flood Warning System: Effects of Error Types and System Reliability

Author:

Mao Tianyi1,Garcia Katherine R.1ORCID,Chen Jing1

Affiliation:

1. Rice University, Houston, TX, USA

Abstract

The increasing threat of inland flooding due to precipitation changes and floodplain development necessitates efficient real-time flood detection and communication methods. While automated floodwarning systems facilitate such communication, they are susceptible to errors like false alarms and misses, which could undermine drivers’ trust during flood events. This study examined how system accuracy and error type impact perceived system reliability, as well as drivers’ trust and behaviors. Our results showed that both false alarms and misses lowered drivers’ perceived system reliability, and drivers were more inclined to follow recommendations from a system with higher reliability compared to one with low reliability. Misses and false alarms influenced drivers’ reliance and compliance behaviors differently. These findings help predict how system reliability level and error type shape drivers’ responses to automated flood-warning systems, potentially contributing to their design and calibration.

Funder

National Science Foundation

Publisher

SAGE Publications

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