Literature DB >> 21376903

Empirical analysis of gross vehicle weight and free flow speed and consideration on its relation with differential speed limit.

Ahmad Abdullah Saifizul1, Hideo Yamanaka, Mohamed Rehan Karim.   

Abstract

Most highly motorized countries in the world have implemented different speed limits for light weight and heavy weight vehicles. The heavy vehicle speed limit is usually chosen to be lower than that of passenger cars due to the difficulty for the drivers to safely maneuver the heavy vehicle at high speed and greater impact during a crash. However, in many cases, the speed limit for heavy vehicle is set by only considering the vehicle size or category, mostly due to simplicity in enforcement. In this study, traffic and vehicular data for all vehicle types were collected using a weigh-in-motion system installed at Federal Route 54 in Malaysia. The first finding from the data showed that the weight variation for each vehicle category is considerable. Therefore, the effect of gross vehicle weight (GVW) and category of heavy vehicle on free flow speed and their interaction were analyzed using statistical techniques. Empirical analysis results showed that statistically for each type of heavy vehicle, there was a significant relationship between free flow speed of a heavy vehicle and GVW. Specifically, the results suggest that the mean and variance of free flow speed decrease with an increase GVW by the amount unrelated to size and shape for all GVW range. Then, based on the 85th percentile principle, the study proposed a new concept for setting the speed limit for heavy vehicle by incorporating GVW where a different speed limit is imposed to the heavy vehicle, not only based on vehicle classification, but also according to its GVW.
Copyright © 2010 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2011        PMID: 21376903     DOI: 10.1016/j.aap.2010.12.013

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  Influence of Trajectory and Dynamics of Vehicle Motion on Signal Patterns in the WIM System.

Authors:  Artur Ryguła; Andrzej Maczyński; Krzysztof Brzozowski; Marcin Grygierek; Aleksander Konior
Journal:  Sensors (Basel)       Date:  2021-11-26       Impact factor: 3.576

Review 2.  Identifying Interactive Factors That May Increase Crash Risk between Young Drivers and Trucks: A Narrative Review.

Authors:  Melissa R Freire; Cassandra Gauld; Angus McKerral; Kristen Pammer
Journal:  Int J Environ Res Public Health       Date:  2021-06-16       Impact factor: 3.390

  2 in total

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