Deep Transfer Learning for Vulnerable Road Users Detection using Smartphone Sensors Data
نویسندگان
چکیده
منابع مشابه
Autonomous Emergency Braking for Vulnerable Road Users
A simple, but realistic, model of an autonomous emergency brake (AEB) system was studied. Using Matlab, the model was applied to 543 car‐to‐pedestrian and 607 car‐to‐bicyclist real‐world collisions gathered from the highly detailed German In‐Depth Accident Study Pre‐Crash Matrix (GIDAS PCM) and weighted for representativeness. All collisions were to the front of the car. The aim was ...
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Avoiding collisions with vulnerable road users (VRUs) using sensor-based early recognition of critical situations is one of the manifold opportunities provided by the current development in the field of intelligent vehicles. As especially pedestrians and cyclists are very agile and have a variety of movement options, modeling their behavior in traffic scenes is a challenging task. In this artic...
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In its latest global assessment of road safety, the World Health Organization (WHO) reminded us that half of the 1.2 million fatalities occurring each year on the world’s roads concern vulnerable road users (VRUs), with children and elderly being overrepresented among victims [1]. ‘‘Vulnerable road user’’ is a term applied to those most at risk in traffic, i.e. those unprotected by an outside s...
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Mobile devices including smartphones and wearable devices are increasingly gaining popularity as platforms for collecting and sharing sensor data, such as the accelerometer, gyroscope, and rotation sensor. These sensors are used to improve the convenience of smartphone users, e.g., supporting the mobile UI motionbased commands. Although these motion sensors do not require users’ permissions, th...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2020
ISSN: 2072-4292
DOI: 10.3390/rs12213508