A Critical Review of Proactive Detection of Driver Stress Levels Based on Multimodal Measurements
| Autor: | Andry Rakotonirainy, Vinod Chandran, Bahareh Nakisa, Mohammad Naim Rastgoo, Dian Tjondronegoro |
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| Rok vydání: | 2018 |
| Předmět: |
Private transport
050210 logistics & transportation Ambient intelligence General Computer Science Warning system Computer science 05 social sciences 02 engineering and technology Human-centered computing Theoretical Computer Science Dangerous driving Contextual design Risk analysis (engineering) Traffic congestion Economic cost 0502 economics and business 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing |
| Zdroj: | ACM Computing Surveys. 51:1-35 |
| ISSN: | 1557-7341 0360-0300 |
| Popis: | Stress is a major concern in daily life, as it imposes significant and growing health and economic costs on society every year. Stress and driving are a dangerous combination and can lead to life-threatening situations, evidenced by the large number of road traffic crashes that occur every year due to driver stress. In addition, the rate of general health issues caused by work-related chronic stress in drivers who work in public and private transport is greater than in many other occupational groups. An in-vehicle warning system for driver stress levels is needed to continuously predict dangerous driving situations and proactively alert drivers to ensure safe and comfortable driving. As a result of the recent developments in ambient intelligence, such as sensing technologies, pervasive devices, context recognition, and communications, driver stress can be automatically detected using multimodal measurements. This critical review investigates the state of the art of techniques and achievements for automatic driver stress level detection based on multimodal sensors and data. In this work, the most widely used data followed by frequent and highly performed selected features to detect driver stress levels are analyzed and presented. This review also discusses key methodological issues and gaps that hinder the implementation of driver stress detection systems and offers insights into future research directions. |
| Databáze: | OpenAIRE |
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