Title :
Augmenting GPS speed limit monitoring with road side visual information
Author :
Eichner, M.L. ; Breckon, Toby P.
Author_Institution :
Cranfield Univ., Cranfield, UK
Abstract :
Frequently drivers fail to be aware of the current speed limit at any given moment in time. Present commercial GPS navigation systems have functionality to warn drivers about speeding on the basis of the road type information stored in the map. Unfortunately any temporary restrictions (e.g. caused by road works) are not taken into account. The system we propose here combines advantages of GPS and an optic sensor for reliable current speed limit monitoring. Our solution was initially developed as standalone vision system presented in details in [3], although integrating it together with GPS navigation adds new features and allows correct operation in majority of European countries. Our vision system includes the detection and recognition of both numerical limit and national limit (cancellation) signs. The system utilizes RANSAC-based colour-shape detection of speed limit signs and neural network based recognition.
Keywords :
Global Positioning System; computerised monitoring; image colour analysis; image recognition; neural nets; object detection; optical sensors; roads; shape recognition; traffic engineering computing; European countries; GPS navigation system; GPS speed limit monitoring; Global Positioning System; RANSAC-based colour-shape detection; national speed limit signs; neural network based recognition; numerical speed limit signs; optic sensor; random sampling and consensus; road side visual information; road type information; GPS; driving assistance; neural networks; recognition; vision;
Conference_Titel :
Road Transport Information and Control - RTIC 2008 and ITS United Kingdom Members' Conference, IET
Conference_Location :
Manchester
Print_ISBN :
978-0-86341-920-1