Speed prediction models for heavy passenger vehicles on rural highways based on an instrumented vehicle study

Malaghan, Vinayak and Pawar, Digvijay S. and Dia, Hussein (2022) Speed prediction models for heavy passenger vehicles on rural highways based on an instrumented vehicle study. Transportation Letters, 14 (1). pp. 39-48. ISSN 1942-7867

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This study developed operating speed prediction models on tangents, curves, and tangent-to-curve transitions for heavy passenger vehicles (HPVs), using continuous speed profiles. Continuous speed profile data for HPVs were collected on two-lane rural highway sections, spanning a total length of 77 km. The curve radius, degree of curve, and preceding tangent length were found to be the influencing variables in predicting both the operating speed on the horizontal curves and the operating speed differential from tangent-to-curve transitions. The study also modeled the relationship between the differential of the 85th percentile operating speed (Formula presented.) and 85th percentile operating speed differential (Formula presented.). The analysis results from empirical data revealed that (Formula presented.) underestimates (Formula presented.) by 5.01 km/h. The reliability of the developed models was validated and compared with existing models from literature. The study highlights the significance of using continuous speed profile data to calibrate the operating speed models. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

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IITH Creators:
IITH CreatorsORCiD
Pawar, Digvijay Shttps://orcid.org/0000-0003-4228-3283
Item Type: Article
Uncontrolled Keywords: Continuous speed data; design consistency; heavy vehicles; operating speed; rural highways
Subjects: Civil Engineering > Construction & Building Technology
Others > Transportation Science Technology
Civil Engineering
Divisions: Department of Civil Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 29 Jul 2022 11:44
Last Modified: 29 Jul 2022 11:44
URI: http://raiith.iith.ac.in/id/eprint/10023
Publisher URL: http://doi.org/10.1080/19427867.2020.1811005
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