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Capacity Analysis of Urban Arterial Midblock Sections Under Mixed Traffic Conditions

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Abstract

The main aim of the study is to model speed and to determine the capacity of six-lane divided urban arterials by develo** speed models. The various midblock sections are selected such that there is no influence of side frictions like pedestrian, on-street parking, etc. Speed-flow data was gathered at six midblock sections of urban arterial roads and extracted for every 5-min interval. The speed–flow relationship as observed from field data replicates the parabolic relationship between two parameters, and hence it may be hypothesized that the speed–density data would follow a linear relationship. Traffic density has been measured by using the basic relationships among speed, flow, and density. This linear speed-density relationship for heterogeneous traffic situations has been used, and efforts are put on to develop simultaneous speed equations for various vehicle categories. These equations are solved by develo** a MATLAB software program, and variation in speed with traffic composition and traffic volume on the road has been explained. Simultaneous equations are used to develop the speed-flow plot and capacity of the midblock sections as 5892 PCU/hr for one direction of flow. The study outcomes are useful to estimate the capacity of midblock sections using volume as input data. Once the speed is dropped to a congestion level, the section reaches a congested state, and traffic operations become chaotic. The congestion mitigation measures may be employed by rerouting existing traffic to reduce the congestion on the urban roadway network.

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Authors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, India

    Ashish Dhamaniya & Chintaman Santosh Bari

  2. Oriental College of Technology, Bhopal, India

    Manish Patkar

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  1. Ashish Dhamaniya
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  2. Chintaman Santosh Bari
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Correspondence to Ashish Dhamaniya.

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Dhamaniya, A., Bari, C.S. & Patkar, M. Capacity Analysis of Urban Arterial Midblock Sections Under Mixed Traffic Conditions. Int. J. ITS Res. 20, 409–421 (2022). https://doi.org/10.1007/s13177-022-00298-1

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