General Behavioral Impact of Smart System Warnings: A Case of Advanced Driving Assistance Systems

Cenying Yang*, Ashish Agarwal, Prabhudev Konana

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Various sensors embedded in smart products can now provide alerts and warnings to users. However, these alerts can also influence user general behavior. We evaluate the effect of advanced driving assistance systems (ADAS) warnings on general driving behavior using automotive telematics data from a large automotive company. We categorize ADAS systems in terms of the response urgency and theorize that less urgent alerts lead to deliberate learning (System 2), improving driving behavior, while highly urgent warnings trigger automatic responses (System 1), potentially leading to risk compensation and worsening driving behavior. Our results show that the presence of a blind spot detection warning, which is less urgent with no immediate action, reduces the daily number of hard braking (speeding) events by 6.76% (9.34%). However, lane departure and forward collision warnings, which are highly urgent and require immediate responses, increase the daily number of hard braking (speeding) events by 5.65% (5.34%). Additionally, we find that, over time, the positive (negative) impact of the blind spot detection (lane departure and forward collision) feature improves (worsens). Finally, we quantify that the presence of the blind spot detection feature decreases the collision rate by 2.17% (3.14%) through a reduction in hard braking (speeding) incidents. However, the presence of lane departure and forward collision features reduces the safety benefits of preventing collisions by 1.71% (1.66%) due to an increase in hard braking (speeding) events. Our results call for the need to integrate user behavior into the design of smart features such as ADAS and related services. © The Author(s) 2025.
Original languageEnglish
JournalProduction and Operations Management
Online published15 Apr 2025
DOIs
Publication statusOnline published - 15 Apr 2025

Funding

This work is funded by City University of Hong Kong Strategic Research Grant.

Research Keywords

  • Advanced Driving Assistance System and Warnings
  • Automotive Telematics
  • Smart Products
  • User Behavior

RGC Funding Information

  • RGC-funded

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