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Motorcycle movement model based on markov chain process in mixed traffic

Mardiati R.a, Trilaksono B.R.a, Gondokaryono Y.S.a, Wibowo S.S.a

a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 Institute of Advanced Engineering and Science.Mixed traffic systems are dynamically complex since there are many parameters and variables that influence the interactions between the different kinds of vehicles. Modeling the behavior of vehicles, especially motorcycle which has erratic behavior is still being developed continuously, especially in developing countries which have heterogeneous traffic. To get a better understanding of motorcycle behavior, one can look at maneuvers performed by drivers. In this research, we tried to build a model of motorcycle movement which only focused on maneuver action to avoid the obstacle along with the trajectories using a Markov Chain approach. In Markov Chain, the maneuver of motorcycle will described by state transition. The state transition model is depend on probability function which will use for determine what action will be executed next. The maneuver of motorcycle using Markov Chain model was validated by comparing the analytical result with the naturalistic data, with similarity is calculated using MSE. In order to know how good our proposed method can describe the maneuver of motorcycle, we try to compare the MSE of the trajectory based on Markov Chain model with those using polynomial approach. The MSE results showed the performance of Markov Chain Model give the smallest MSE which 0.7666 about 0.24 better than 4th order polynomial.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Maneuver Intention,Markov Chain,Mixed Traffic,Vehicle Movement[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors would like to thank the Indonesia Endowment Fund for Education (LPDP Indonesia) and the Indonesian Ministry of Religious Affairs for their financial support of this study.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.11591/ijece.v8i5.pp3149-3157[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]