TY - GEN
T1 - A decomposition method with discrete abstraction for simultaneous traffic signal control and route selection problem with first-order hybrid Petri Nets
AU - Yamazaki, Ryotaro
AU - Nishi, Tatsushi
AU - Sakurai, Soh
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - We propose a decomposition method for simultaneous traffic signal control and route selection problem with first-order hybrid Petri Nets. The traffic signal control problem is formulated as an optimal firing sequence problem for first order hybrid Petri Nets where a passage of the vehicles is represented by the real number of vehicles and discrete states represent the traffic signal states. A simultaneous traffic signal control and route selection model is developed with the selection of the route for a specific vehicle with traffic flows with the same traffic signals. A discrete abstraction model is introduced to reduce the computational expense for the Lagrangian relaxation technique. Computational results show the superiority of the discrete abstraction model over existing methods.
AB - We propose a decomposition method for simultaneous traffic signal control and route selection problem with first-order hybrid Petri Nets. The traffic signal control problem is formulated as an optimal firing sequence problem for first order hybrid Petri Nets where a passage of the vehicles is represented by the real number of vehicles and discrete states represent the traffic signal states. A simultaneous traffic signal control and route selection model is developed with the selection of the route for a specific vehicle with traffic flows with the same traffic signals. A discrete abstraction model is introduced to reduce the computational expense for the Lagrangian relaxation technique. Computational results show the superiority of the discrete abstraction model over existing methods.
UR - http://www.scopus.com/inward/record.url?scp=85044967730&partnerID=8YFLogxK
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U2 - 10.1109/COASE.2017.8256128
DO - 10.1109/COASE.2017.8256128
M3 - Conference contribution
AN - SCOPUS:85044967730
T3 - IEEE International Conference on Automation Science and Engineering
SP - 352
EP - 357
BT - 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
PB - IEEE Computer Society
T2 - 13th IEEE Conference on Automation Science and Engineering, CASE 2017
Y2 - 20 August 2017 through 23 August 2017
ER -