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<p>The higher autonomous driving system level defined by SAE(Society of Automotive Engineers) brings the less burden on manual driving of the driver and the more dependence on automated driving through the Automated Driving System(ADS). The obligation to drive is on the driver at levels 1 and 2, and the driver is relieved of the Dynamic Driving Task (DDT) at level 4 and above. However, at level 3, ADS can be disengaged by a driver depending on driving conditions. If the autonomous vehicle is unable to drive on its own or is expected to pose a significant risk due to autonomous driving, the ADS must be forcibly disengaged by the driver. In this study, we collected autonomous vehicle’s driving data and driving environment information in driver-initiated ADS disengagement situation through Field Operational Test (FOT) and analyzed the effective factors that make a driver disengage ADS through correlation analysis between the data. The FOT is conducted on D-Live platform, an ADS field operational test platform in Daegu metropolitan city. The data collected by D-Live platform reflects the various types of data in real-time and non-real-time such as vehicles’ driving data, road and weather conditions, and even incident events information. Consequentially, driver-initiated ADS disengagement situation could be analyzed not only from the perspective of autonomous vehicles but also from the perspective of infrastructure system, and the effective factors could be derived from a wider possibility.</p>

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A Study on the Effective Factor of the Driver-Inititated Disengagement of Autonomous Driving System Through Real-road Field Operational Tests

  • 期刊论文

  • 发表日期：

    2026年3月9日

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  • Dong Whan Lee,
  • Tae Lim Kim,
  • Jae Ung Choi,
  • Seong-Jin Kwon

摘要

The higher autonomous driving system level defined by SAE(Society of Automotive Engineers) brings the less burden on manual driving of the driver and the more dependence on automated driving through the Automated Driving System(ADS). The obligation to drive is on the driver at levels 1 and 2, and the driver is relieved of the Dynamic Driving Task (DDT) at level 4 and above. However, at level 3, ADS can be disengaged by a driver depending on driving conditions. If the autonomous vehicle is unable to drive on its own or is expected to pose a significant risk due to autonomous driving, the ADS must be forcibly disengaged by the driver. In this study, we collected autonomous vehicle’s driving data and driving environment information in driver-initiated ADS disengagement situation through Field Operational Test (FOT) and analyzed the effective factors that make a driver disengage ADS through correlation analysis between the data. The FOT is conducted on D-Live platform, an ADS field operational test platform in Daegu metropolitan city. The data collected by D-Live platform reflects the various types of data in real-time and non-real-time such as vehicles’ driving data, road and weather conditions, and even incident events information. Consequentially, driver-initiated ADS disengagement situation could be analyzed not only from the perspective of autonomous vehicles but also from the perspective of infrastructure system, and the effective factors could be derived from a wider possibility.