Highly Automated Learning for Improved Active Safety of Vulnerable Road Users
نویسندگان
چکیده
Highly automated driving requires precise models of traffic participants. Many state of the art models are currently based on machine learning techniques. Among others, the required amount of labeled data is one major challenge. An autonomous learning process addressing this problem is proposed. The initial models are iteratively refined in three steps: (1) detection and context identification, (2) novelty detection and active learning and (3) online model adaption.
منابع مشابه
O3: Children are Not Small Adults! What should be done to Better Protect Them?
Road Traffic injuries are known as the most prevalent childhood injury and besides being the greatest cause of child mortality, place an extraordinary burden on health care system. Children’s limitation in cognitive, physical and social development makes them more vulnerable in road traffic injuries than adults. Their small structure cause challenges to see and be seen and their risk taki...
متن کاملThesis for the Degree of Doctor of Philosophy
The overall objective of the thesis is to explore various types of real-world road traffic data and to assess the extent to which they can inform the design of active safety systems that aim to prevent car-to-vulnerable road user (VRU) accidents. A combined analysis of in-depth and police reported accident data provided information on driver behavior and contextual variables, which is valuable ...
متن کاملAutomatic road crack detection and classification using image processing techniques, machine learning and integrated models in urban areas: A novel image binarization technique
The quality of the road pavement has always been one of the major concerns for governments around the world. Cracks in the asphalt are one of the most common road tensions that generally threaten the safety of roads and highways. In recent years, automated inspection methods such as image and video processing have been considered due to the high cost and error of manual metho...
متن کاملWhere is my Device? - Detecting the Smart Device's Wearing Location in the Context of Active Safety for Vulnerable Road Users
This article describes an approach to detect the wearing location of smart devices worn by pedestrians and cyclists. The detection, which is based solely on the sensors of the smart devices, is important context-information which can be used to parametrize subsequent algorithms, e.g. for dead reckoning or intention detection to improve the safety of vulnerable road users. The wearing location r...
متن کاملImproving safety and mobility of Vulnerable Road Users through ITS applications
ITS Applications have in recent years assisted in reducing the number of fatalities in Europe. However, Vulnerable Road Users (VRUs) have not benefited as much as vehicle users. The EU-sponsored VRUITS project assesses the safety and mobility impacts of ITS applications for VRUs, assesses the impacts of current and upcoming ITS applications on the safety and mobility of VRUs, identifies how the...
متن کامل