SEEK: Salford Environment for Expertise and Knowledge

Journal Article (Refereed)
May 2013

Drivers' lane utilization for United Kingdom motorways

Yousif, S & Al-Obaedi, J & Henson, R R 2013, 'Drivers' lane utilization for United Kingdom motorways', Journal of Transportation Engineering, 139(5), pp.441-447.

Abstract

Lane utilization represents how the rate of traffic flow is distributed among the available number of lanes in a given section. This utilization or split is affected by several factors including traffic flow rates as well as the presence and amount of heavy goods vehicles within the traffic. The importance of studying lane utilization comes from the fact that it is one of the input parameters for any traffic micro-simulation models which are increasingly being used in order to assess and suggest solutions for traffic problems.

This paper uses two sources of data to model lane utilization including "Motorway Incident detection and Automatic Signaling" MIDAS data and individual vehicles raw data. The latter source of data is specifically used to model how heavy goods vehicles (HGVs) are distributed between motorway lanes as flow increases since MIDAS data does not specify the proportions of HGVs by lanes. Since the data used to develop the models in this paper are based on a relatively large set of data (compared with those represented by older models), one could argue that these models are more representative of current lane utilization on UK motorways. The development of laneutilization models for HGV traffic will help in providing more realistic predictions of traffic behavior when represented by micro-simulation models and in the assessment of such commercial vehicles using the lanes when it comes to pavement design.

Notes

This paper made use of an extensive set of traffic data from UK motorways to model lane utilisation. The models were tested against earlier ones.  The suggested models will help practicing engineers to make more realistic assumptions (rather than making illogical ones) when inputting data to those traffic software which are widely used in industry to predict and evaluate traffic conditions and operations on motorways.

Journal Impact factor for Transportation Engineering – ASCE  = 0.5

Number of external citations = newly published (May 2013) but some interest has been received by practicing engineers working for consultants in the UK.

 

Authors

SEEK Members

External Authors

JST Al-Obaedi

R R Henson

Publication Details

Journal Name
Journal of Transportation Engineering

Volume
139(5)

Pagination
441-447.