A simulation model to reduce the fuel consumption through efficient road traffic modelling
Simulation Modelling Practice and Theory
Controlling traffic dynamically is a complex task which includes meeting the increasing traffic demand and decreasing delays at the intersection. The current traffic controllers based on fixed transition phase of green/red/yellow lights are not capable of dealing with the changing of real time traffic conditions at the intersections. Moreover, Due to shortage of manpower it becomes unfeasible to employ traffic men for each intersection, throughout the day and if somehow it is available, it incurs high cost. A fuzzy based model for controlling congestion at the crossroads, which covers the demands of real time traffic conditions, is designed. This paper presents a novel traffic simulator to simulate the designed fuzzy model and traffic control system with fixed time and the performance so obtained is compared. In the proposed simulator, traffic is generated as per the user suggested density of traffic on each lane. The waiting vehicle's average delay is reduced effectively in fuzzy controlled model due to adaptive green light time based on the queue length, arrival rate of vehicles and the waiting time. It has been noticed that the average percentage delay reduction experienced by the vehicles waiting for their turn in fuzzy model is 21.1% as compared to the fixed time model. Experimentally observed results on real time scenario has shown an average improvement of 3786 min. in delay per day. This leads to a reduction of 33.1275gm/day in CO2 emission and a saving of 45.43 liters of fuel per day at one intersection.
Open Access Status
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