TY - JOUR
T1 - Automated vehicle control systems need to solve social dilemmas to be disseminated
AU - Tanimoto, Jun
AU - Futamata, Masanori
AU - Tanaka, Masaki
N1 - Funding Information:
This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI (Grant No. JP 19KK0262 and JP 20H02314 ) awarded to Professor Tanimoto. We would like to express our gratitude to them.
Publisher Copyright:
© 2020
PY - 2020/9
Y1 - 2020/9
N2 - A new cellular automata traffic model based on the revised S-NFS model was established to consider a mixed flow of automated and human-driven vehicles assuming a multi-lane system. The model further classified automated vehicles into two categories: (1) vehicles with adaptive cruise control and (2) those with cooperative adaptive cruise control that supports so-called platoon driving. A vehicle that favors maximizing individual payoff, which ensures minimizing its own travel time, while maximizing global traffic flux was expected as the entire society. Intensive simulations, wherein automated and human-driven vehicles were presumed as cooperative (C) and defective (D) strategies, respectively, revealed that a D-strategy is always better than a C-strategy to maximize individual payoff as long as a smaller cooperative fraction is imposed. Meanwhile, social optimal could be realized by a situation comprising only automated vehicles. Such a stag-hunt social dilemma implied that an automated vehicle control system (AVCS) cannot permeate into a population of human-driven vehicles if the dissemination stage starts from a single vehicle with an AVCS.
AB - A new cellular automata traffic model based on the revised S-NFS model was established to consider a mixed flow of automated and human-driven vehicles assuming a multi-lane system. The model further classified automated vehicles into two categories: (1) vehicles with adaptive cruise control and (2) those with cooperative adaptive cruise control that supports so-called platoon driving. A vehicle that favors maximizing individual payoff, which ensures minimizing its own travel time, while maximizing global traffic flux was expected as the entire society. Intensive simulations, wherein automated and human-driven vehicles were presumed as cooperative (C) and defective (D) strategies, respectively, revealed that a D-strategy is always better than a C-strategy to maximize individual payoff as long as a smaller cooperative fraction is imposed. Meanwhile, social optimal could be realized by a situation comprising only automated vehicles. Such a stag-hunt social dilemma implied that an automated vehicle control system (AVCS) cannot permeate into a population of human-driven vehicles if the dissemination stage starts from a single vehicle with an AVCS.
UR - http://www.scopus.com/inward/record.url?scp=85085550453&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085550453&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2020.109861
DO - 10.1016/j.chaos.2020.109861
M3 - Article
AN - SCOPUS:85085550453
SN - 0960-0779
VL - 138
JO - Chaos, solitons and fractals
JF - Chaos, solitons and fractals
M1 - 109861
ER -