TY - GEN
T1 - Traffic flow models with two kinds of vehicles in terms of the vector-valued cellular automata and their fuzzification
AU - Nishida, Yuki
AU - Watanabe, Sennosuke
AU - Fukuda, Akiko
AU - Watanabe, Yoshihide
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Numbers JP21K03359 and JP19K03624.
Publisher Copyright:
© 2022 Author(s).
PY - 2022/12/19
Y1 - 2022/12/19
N2 - Elementary cellular automata (ECA) rule 184 can be used as mathematical models of traffic flows. The slow-to-start model is obtained from the ECA rule 184 model by taking time lag for restart into consideration and is represented by 3-state 3-neighbor cellular automata (CA). In the present paper, we propose a traffic model where vehicles following the slow-to-start rule and those not following the slow-to-start rule are mixed. This model, called the mixed slow-to-start model, is represented by 4-state 3-neighbor CA. Further, we introduce the vector representation of CA with the slow-to-start rule and with the mixed slow-to-start rule, and then get their corresponding fuzzy CA. These fuzzy CA provide continuous-valued traffic models with the slow-to-start effect. Comparing the fundamental diagrams of the the slow-to-start model, the mixed slow-to-start model, and their fuzzy counterparts, we investigate the influence of the density and the mixing ratio of vehicles on traffic jams.
AB - Elementary cellular automata (ECA) rule 184 can be used as mathematical models of traffic flows. The slow-to-start model is obtained from the ECA rule 184 model by taking time lag for restart into consideration and is represented by 3-state 3-neighbor cellular automata (CA). In the present paper, we propose a traffic model where vehicles following the slow-to-start rule and those not following the slow-to-start rule are mixed. This model, called the mixed slow-to-start model, is represented by 4-state 3-neighbor CA. Further, we introduce the vector representation of CA with the slow-to-start rule and with the mixed slow-to-start rule, and then get their corresponding fuzzy CA. These fuzzy CA provide continuous-valued traffic models with the slow-to-start effect. Comparing the fundamental diagrams of the the slow-to-start model, the mixed slow-to-start model, and their fuzzy counterparts, we investigate the influence of the density and the mixing ratio of vehicles on traffic jams.
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U2 - 10.1063/5.0114966
DO - 10.1063/5.0114966
M3 - Conference contribution
AN - SCOPUS:85145455261
T3 - AIP Conference Proceedings
BT - 7th International Conference on Mathematics - Pure, Applied and Computation
A2 - Mufid, Muhammad Syifa�ul
A2 - Adzkiya, Dieky
PB - American Institute of Physics Inc.
T2 - 7th International Conference on Mathematics: Pure, Applied and Computation: , ICoMPAC 2021
Y2 - 2 October 2021
ER -