Split Cycle Offset Optimisation Technique (SCOOT) is a real time adaptive traffic control system for the coordination and control of traffic signals across an urban road network. Originally developed by the Transport Research Laboratory[1] for the Department of Transport in 1979, research and development of SCOOT has continued to present day. SCOOT is used extensively throughout the United Kingdom as well as in other countries.[2][citation needed]
SCOOT automatically adjusts the traffic signal timings to adapt to current traffic conditions, using flow data from traffic sensors.[3] Sensor data is usually derived from inductive loops in the carriageway but other forms of detection are increasingly being used.
Adjacent signal controlled junctions and pedestrian/cycle crossings are collected together into groups called "regions". SCOOT then calculates the most appropriate signal timings for the region.[1] SCOOT changes the stage lengths or the splits to ensure that the delays are balanced as much as possible, changes the cycle time to ensure that delays are minimised and finally changes the offset between the signal installations to ensure that the timings are co-ordinated as well as possible.
SCOOT has been demonstrated to yield improvements in traffic performance of the order of 15% compared to fixed timing systems.[3]
In early 2021, TRL released SCOOT 7, having updated the algorithm to work with future mobility needs.[4]
See also
editReferences
edit- ^ a b "Traffic Advisory Leaflet 4/95: The "SCOOT" Urban Traffic Control System" (PDF). Department of Transport. April 1995. Archived (PDF) from the original on 21 March 2014. Retrieved 4 September 2013.
- ^ Carr, Dave. "SCOOT: Basic Principles" (PDF). Institute of Highway Engineers. Archived from the original (PDF) on 26 October 2017. Retrieved 25 October 2017.
- ^ a b "Urban traffic control systems: Evidence on performance". Institute for Transport Studies, University of Leeds. Archived from the original on 19 October 2012. Retrieved 4 September 2013.
- ^ "SCOOT™". TRL Software. Archived from the original on 22 January 2021. Retrieved 2 February 2021.
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