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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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. 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