Abstract:
Distracted drivers are a major factor in road safety that critically and continuously threaten the roads. While highly distracted drivers can be observed by surrounding v...Show MoreMetadata
Abstract:
Distracted drivers are a major factor in road safety that critically and continuously threaten the roads. While highly distracted drivers can be observed by surrounding vehicles, detecting moderate abnormalities such as delayed driver response is crucial for road safety and cannot be observed by the surrounding vehicles. The main challenge arises from the fact that normal human drivers’ behavior is unknown and difficult to be estimated. This study uses velocity output-only measurements available from sensors in mixed autonomous and human-driven platoons to detect low to moderately distracted human drivers within the same platoon. The output measurements are related mathematically to each other, which is known as transmissibility relations. Transmissibility is constructed and formulated to treat the unknown normal human behavior as an external factor that acts on the platoon. Thus, transmissibility becomes independent of the unknown human behavior and is then used to obtain an estimation of the human-driven vehicle’s velocity. Next, a residual-based technique is used between the estimated and measured velocities to detect abnormal driving behaviors. As an example of distracted drivers, we apply the proposed approach to a class of low to moderately-drunk drivers. The proposed approach is verified first numerically and then applied to a set of laboratory mobile robots.
Published in: 2022 IEEE 61st Conference on Decision and Control (CDC)
Date of Conference: 06-09 December 2022
Date Added to IEEE Xplore: 10 January 2023
ISBN Information: