TY - GEN
T1 - Modular Modelling for Urban Traffic Networks based on Multi-Agent Systems and Petri Nets
AU - Flores-Geronimo, M.
AU - Hernandez-Martinez, E. G.
AU - Ferreira-Vazquez, E. D.
AU - Flores-Godoy, J. J.
AU - Fernandez-Anaya, G.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/4/12
Y1 - 2019/4/12
N2 - Inspired on the focus of multi-agent systems used in groups of robots, this paper describes a novel modeling methodology for urban traffic networks based on the interconnections of simple generic differential equations about distinct streets and intersections. These nonlinear fluid equations represent features like vehicular density, average vehicle velocities, occupation capacities and the interconnections between adjacent street segments and intersections. In order to enable more realistic traffic light actions, individual petri nets are defined for each the intersections, enabling or disabling the flow of vehicles. Therefore, the main contribution is the definition of a hybrid modular scheme of continuous differential equations with discrete-event systems. A numerical simulation of a simple intersection using Matlab shows the performance of the approach and its scalability to more complex traffic networks.
AB - Inspired on the focus of multi-agent systems used in groups of robots, this paper describes a novel modeling methodology for urban traffic networks based on the interconnections of simple generic differential equations about distinct streets and intersections. These nonlinear fluid equations represent features like vehicular density, average vehicle velocities, occupation capacities and the interconnections between adjacent street segments and intersections. In order to enable more realistic traffic light actions, individual petri nets are defined for each the intersections, enabling or disabling the flow of vehicles. Therefore, the main contribution is the definition of a hybrid modular scheme of continuous differential equations with discrete-event systems. A numerical simulation of a simple intersection using Matlab shows the performance of the approach and its scalability to more complex traffic networks.
UR - http://www.scopus.com/inward/record.url?scp=85065044283&partnerID=8YFLogxK
U2 - 10.1109/COMROB.2018.8689413
DO - 10.1109/COMROB.2018.8689413
M3 - Contribución a la conferencia
AN - SCOPUS:85065044283
T3 - 2018 20th Congreso Mexicano de Robotica, COMRob 2018
BT - 2018 20th Congreso Mexicano de Robotica, COMRob 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th Congreso Mexicano de Robotica, COMRob 2018
Y2 - 12 September 2018 through 14 September 2018
ER -