In order to formulate a high-level understanding of driver behavior from massive naturalistic
driving data, an effective approach is needed to automatically process or segregate data into …

Intelligent vehicles and Advanced Driver Assistance Systems (ADAS) are being developed
rapidly over the past few years. Many applications such as vehicle localization, environment …

Apparatus and methods are described for roadway lane line detection. An aerial image
including a plurality of pixels is received and provides to a classification model. The classi …

Traffic signs are a key element in driver safety. Governments invest a great amount of
resources in maintaining the traffic signs in good condition, for which a correct inventory is …

Side swipe accidents occur primarily when drivers attempt an improper lane change, drift out
of lane, or the vehicle loses lateral traction. In this paper, a fusion approach is introduced …

Automated driving is becoming a reality. In this new reality, High Definition (HD) Maps play
an important role in path planning and vehicle localization. Lane boundary geometry is one …

Part of the challenges in the quest for smart cities is to enable effective navigation for
different types of mobile users: from pedestrians, through drivers, to autonomous vehicles …

Automatic Extraction of road network from satellite images is a goal that can benefit and
even enable new technologies. Methods that combine machine learning (ML) and computer …

Measuring the quality of roads and ensuring they are ready for autonomous driving is
important for future transportation systems. Here we focus on develo** metrics and …

The documentation of roadway factors (such as roadway geometry, lane marking
retroreflectivity/classification, and lane width) through the inventory of lane markings can …