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Cycle Detection using Intelligent Transport Systems


Since 2009, 28 cyclists have been killed in collisions with large goods vehicles on Londonís roads; a large proportion of these occurred when the vehicle was turning left at the time of the accident. At Transport for London's request, TRL has been investigating the potential use of electronic means for detecting bicycles with the aim of reducing the number of cyclists who are killed or seriously injured after collisions with large goods and other heavy vehicles

Cycle Detection using Intelligent Transport Systems

The main problem is the inability of the vehicle driver to see cyclists in their blind spots (especially down the nearside of the vehicle and, for heavy trucks, immediately in front) despite improvements to mirror systems in recent years. Drivers may also be distracted by other on-road situations, so fail to use the right mirror at the crucial moment when the cyclist moves into the area of greatest risk.

Following a market survey of existing or near market products, trials of the best candidates have been undertaken.  This has involved TRL exploring the options for an RFID style solution in which the cycle is fitted with a low cost RFID tag and the vehicle is equipped with a detection system which monitors the areas of greatest risk to cyclists and provides the driver with a timely and reliable warning of cyclists in those areas.

Key features include the ability to provide alarms only within the area of greatest risk to the cyclist and not elsewhere (and hence develop a product which can be easily tuned for different vehicle configurations), and to keep the additional distraction to the driver to a minimum.

The research has also examined and tested tag-free solutions where the detection system is restricted to the heavy vehicle and no cycle based equipment is necessary. The requirements for such vehicle-only systems are similar, but have to demonstrate a high level of bicycle detection, whilst giving very low levels of false alarms from other vehicles or street furniture in the area of greatest risk.



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