Development of an Interface between Signal Controller and Traffic Simulator. Bajpai, A. & Mathew, T. V In 1st Conference of Transportation Research Group of India, 12, 2011. Transportation Research Group of India.
abstract   bibtex   
Adaptive Traffic Control algorithm is an important strategy to manage traffic at an intersection. These are an improvement of vehicle actuated signal control, where explicitly strategies are formulated to compute the signal timing considering the current traffic state obtained from sensors. However, field evaluation of these strategies is cumbersome and expensive and hence simulators which model traffic system can be a good alternative. The main challenge in this is a good interface between the signal control system and the traffic simulators. The signal control system needs the state of the junction in terms of vehicle occupancy at every instant. On the other hand, traffic simulator needs information on whether the signal state has changed. This two way communication requires an efficient interface which is similar to client-server architecture. The simulator acts as the server where as the adaptive control strategy act like client. This paper proposes an efficient interface to couple adaptive control strategy and traffic simulator. This interface mediates between traffic control system and traffic simulator and provides online interaction to simulation from the control strategy. This interface facilitates pure procedural routines to communicate and is written in C language along with Python/C API. Additionally, a module to estimate the vehicular delay due to the control strategy is developed. This delay is estimated by defining effective length of queue, which is provided as a user input. This interface is tested using SUMO (Simulation for Urban Mobility), which is an open source, microscopic, space continuous and time discrete simulator developed by German Aerospace Centre. The traffic control strategy is analogous to the HCM vehicle actuated traffic control except that there is a queue prediction model which computes upper limits on the maximum green time. An isolated four arm junction having four phases is simulated for various flow conditions. The simulator supplied the state of the downstream detector to the traffic control algorithm at every simulation step and the control algorithm determines the signal time strategies (phase termination, green extension, and maximum green time). These strategies are communicated to the simulator. These communications were facilitated by the proposed interface. The average stopped delay is computed as the performance parameter. The interface was also coupled with another traffic simulator (VISSIM) and the results are compared. This interface justifies the concept of reusability by the evaluation of number of control strategy.
@inproceedings{Bajpai2011,
	author = {Ashutosh Bajpai and Tom V Mathew},
	booktitle = {1st Conference of Transportation Research Group of India},
	title = {Development of an Interface between Signal Controller and Traffic Simulator},
	year = {2011},
	month = {12},
	organization = {Transportation Research Group of India},
	abstract = {Adaptive Traffic Control algorithm is an important strategy to manage
	traffic at an intersection. These are an improvement of vehicle actuated
	signal control, where explicitly strategies are formulated to compute
	the signal timing considering the current traffic state obtained
	from sensors. However, field evaluation of these strategies is cumbersome
	and expensive and hence simulators which model traffic system can
	be a good alternative. The main challenge in this is a good interface
	between the signal control system and the traffic simulators. The
	signal control system needs the state of the junction in terms of
	vehicle occupancy at every instant. On the other hand, traffic simulator
	needs information on whether the signal state has changed. This two
	way communication requires an efficient interface which is similar
	to client-server architecture. The simulator acts as the server where
	as the adaptive control strategy act like client. This paper proposes
	an efficient interface to couple adaptive control strategy and traffic
	simulator. This interface mediates between traffic control system
	and traffic simulator and provides online interaction to simulation
	from the control strategy. This interface facilitates pure procedural
	routines to communicate and is written in C language along with Python/C
	API. Additionally, a module to estimate the vehicular delay due to
	the control strategy is developed. This delay is estimated by defining
	effective length of queue, which is provided as a user input.


	This interface is tested using SUMO (Simulation for Urban Mobility),
	which is an open source, microscopic, space continuous and time discrete
	simulator developed by German Aerospace Centre. The traffic control
	strategy is analogous to the HCM vehicle actuated traffic control
	except that there is a queue prediction model which computes upper
	limits on the maximum green time. An isolated four arm junction having
	four phases is simulated for various flow conditions. The simulator
	supplied the state of the downstream detector to the traffic control
	algorithm at every simulation step and the control algorithm determines
	the signal time strategies (phase termination, green extension, and
	maximum green time). These strategies are communicated to the simulator.
	These communications were facilitated by the proposed interface.
	The average stopped delay is computed as the performance parameter.
	The interface was also coupled with another traffic simulator (VISSIM)
	and the results are compared. This interface justifies the concept
	of reusability by the evaluation of number of control strategy.},
	file = {:https\://sumo.dlr.de/pdf/CTRG_Interface-SUMO.pdf:URL},
	groups = {used, TLS, IIT Bombay, assigned2groups},
	keywords = {Traffic simulator, Signal controller, Procedural Interface, SUMO (Simulation of Urban Mobility), VISSIM (Verkehr In St�dten - SIMulationsmodell)},
	owner = {dkrajzew},
	timestamp = {2012.02.07}
}

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