TY - JOUR
T1 - Underlying social dilemmas in mixed traffic flow with lane changes
AU - Sueyoshi, Fumi
AU - Utsumi, Shinobu
AU - Tanimoto, Jun
N1 - Funding Information:
This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan , KAKENHI (Grant No. JP 19KK0262 , JP 20H02314 and JP 20K21062 ) awarded to Professor Tanimoto. We would like to express our gratitude to them.
Publisher Copyright:
© 2022
PY - 2022/2
Y1 - 2022/2
N2 - A new cellular automata traffic model based on Revised S-NFS model is established to consider a mixed flow system in which the maximal velocity of the agents is distributed, as is the case in a real traffic flow fields composed of compact vehicles, trucks, and buses. These vehicles are assigned on of two different strategies: cooperator (C), who remains in his original lane, and defector (D), who undertakes lane-changing to maximize his own payoff, i.e., average velocity. In a systematic series of multi-agent simulations, we quantitatively compare flow characteristics in the default system (where maximal velocity is constant across all agents), mixed traffic flow systems (which permit a distribution of maximal velocities), and correlated–mixed traffic flows, in which an agent with a higher maximal velocity tends to have a D strategy whereas one with a lower maximal velocity tends to have a C strategy. We discuss what kind of game class is underlying in each traffic flow system. Furthermore, we quantitatively study the social efficiency deficit, an index of dilemma extent, for each of the flow systems.
AB - A new cellular automata traffic model based on Revised S-NFS model is established to consider a mixed flow system in which the maximal velocity of the agents is distributed, as is the case in a real traffic flow fields composed of compact vehicles, trucks, and buses. These vehicles are assigned on of two different strategies: cooperator (C), who remains in his original lane, and defector (D), who undertakes lane-changing to maximize his own payoff, i.e., average velocity. In a systematic series of multi-agent simulations, we quantitatively compare flow characteristics in the default system (where maximal velocity is constant across all agents), mixed traffic flow systems (which permit a distribution of maximal velocities), and correlated–mixed traffic flows, in which an agent with a higher maximal velocity tends to have a D strategy whereas one with a lower maximal velocity tends to have a C strategy. We discuss what kind of game class is underlying in each traffic flow system. Furthermore, we quantitatively study the social efficiency deficit, an index of dilemma extent, for each of the flow systems.
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U2 - 10.1016/j.chaos.2022.111790
DO - 10.1016/j.chaos.2022.111790
M3 - Article
AN - SCOPUS:85122619386
SN - 0960-0779
VL - 155
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
M1 - 111790
ER -