[vc_empty_space][vc_empty_space]
The impact of location and number of traffic counts in the accuracy of O-D matrices estimated from traffic counts
Kresnanto N.C.a, Tamin O.Z.b
a Departmen of Civil Engineering, Janabadra University, Indonesia
b Departmen of Civil Engineering, Institute Technology Bandung (ITB), 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]Theoretically, the more data traffic count we have, the better will be the estimated O-D matrix. However, this is costly and requires long process. Therefore, the objective and contribution of this research is to obtain the best locations and the optimum number of traffic counts. The model considered 3 (three) major factors i.e. (a) proportion factor of the trip interchange for each link, (b) independence and inconsistency conditions, and (c) physical link condition. In this research, equilibrium assignment is used to consider the congestion effect in route choice selection. The model has been tested in Bandung consisting of 125 zones and 2279 links (arterial, collector, and local roads). The best links obtained in the second stage is re-evaluated again using link condition criteria and finally obtain the best location of traffic count. The study has also found that the optimum number of traffic count data is 90 links (around 3,6% of total links).[/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]Data traffic,Equilibrium assignment,Major factors,O-D matrix,Optimum number,Proportion factor,Route choice,Traffic counts[/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][/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][/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][/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]