IIT Madras researchers develop demand-responsive signal control to address traffic jams

Researchers at the Indian Institute of Technology IIT Madras have developed a possible solution to traffic snarls on Indian roads through the use of a probebased approach for realtime retiming of traffic signalsAccording to officials this is probably the first time a probebased demandresponsive signal control has been developed for Indian conditionsThe researchers conducted a study in which traveltime data from four sampleprobe vehicles were used to calculate Green and Red timings for each signal cycleA signal cycle is the time between one green signal to the next green signal or one red signal to the next red signal for a selected movementWhile a lot of time effort and money have been spent on experimenting with offtheshelf trafficresponsive signalling software from abroad these have not worked well in Indian traffic conditions since their implementation required a number of sensors and large traffic stream data which was not easy to collect said Lelitha Vanajakshi Ministry of Road Transport and Highways MoRTH Chair Professor at IIT MadrasMoreover these software were rarely flexible for incorporating Indian traffic characteristics in their algorithms resulting in excessive queues and delays at the intersection in spite of large capital investments Vanajakshi addedThe findings have been published in the International Journal of Transportation ResearchThe traffic composition in India is very different from that in the Western countries In India the traffic is usually referred to as belonging to the category of mixed traffic conditions with a variety of vehicle classes juxtaposed with lanefree movementTherefore in this study the effect of composition has been included in the algorithms which makes it versatile for use across different cities with varying vehicle compositions said Bhargava Rama Chilukuri Faculty Department of Civil Engineering IIT MadrasAlso readMumbai Sameer Wankhede once again summoned by CBI for questioning on May 24In the study the researchers have used traveltime data which is invariant to the vehicle class instead of the traditional input which is traffic flow This makes the algorithms easy to implement with a variety of probebased data sources such as Bluetooth WiFi and radio frequency identification scannersAnother advantage is that these data sources are lowcost efficient and can collect travel information of large samples of vehicles for trafficcontrol applications We formulated a mathematical optimization problem that uses the sample traveltime data to compute optimal green and red durations such that the varying traffic demand is met while ensuring minimal queues and delaysThis algorithm can also be extended to oversaturated intersections and optimum signal coordination across a series of intersections which present themselves as areas of future research Chilukuri saidThis story has been sourced from a third party syndicated feed agencies Midday accepts no responsibility or liability for its dependability trustworthiness reliability and data of the text Midday managementmiddaycom reserves the sole right to alter delete or remove without notice the content in its absolute discretion for any reason whatsoever