The traditional taxi prediction methods model the taxi trajectory as a sequence of spatial points. It cannot represent two-dimensional spatial relationships between trajectory points. Therefore, many methods transform the taxi GPS trajectory into a t...
Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in utilitarian ways, trying to cause as little overall damage as possible. These trolley dilemmas have gained renewed atte...
A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver's point of attention. Accurate ...
This study aimed to extract information from body pressure distribution, including comfort, participant body size, and seat characteristics by using supervised deep learning, and body pressure characteristics corresponding to sensory evaluation by us...
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illus...
Due to the increased availability of digital human models, the need for knowing human movement is important in product design process. If the human motion is derived rapidly as design parameters change, a developer could determine the optimal paramet...
OBJECTIVE: Though autonomous emergency braking (AEB) systems for car-to-cyclist collisions have been under development, an estimate of the benefit of AEB systems based on an analysis of accident data is needed for further enhancing their development....
Negotiations among drivers and pedestrians are common on roads, but it is still challenging for a self-driving vehicle to negotiate for its right of way with other human road users, especially pedestrians. Currently, the self-driving vehicles are pro...