The University of Southampton
University of Southampton Institutional Repository

Monitoring and evaluation of smart motorway schemes

Monitoring and evaluation of smart motorway schemes
Monitoring and evaluation of smart motorway schemes
Smart motorway schemes aim to address congestion issues and improve journey time reliability by utilising a set of advanced Intelligent Transport Systems applications and making use of the existing road space as much as possible. The M42 Smart Motorway Pilot, introduced in September 2006 by the Highways Agency (known as Highways England since April 2015), established the concept of Hard Shoulder Running (HSR) for the first time in the UK, together with variable mandatory speed limits during periods of congestion. Following the success of the Pilot, smart motorways are being rolled-out to other sections of Highways England’s strategic road network. This research has been carried out to understand the performance of smart motorways and its limiting factors.

A review of the concept of highways capacity was carried out to understand the parameters that influence traffic conditions during smart motorway operations. This was followed by a series of analysis using empirical data which examined the performance of existing smart motorways schemes on the M42 and M6 motorways near Birmingham, UK. Overall, smart motorway schemes have significantly reduced average journey times and journey time variability, improved motorway capacity and smoothed traffic flow. The level of benefits observed varied from one scheme to another mainly due to the different site conditions (road geometry, traffic demand and patterns). However, each scheme consistently demonstrated considerable improvements when compared to non-smart motorway conditions.

One of the aims of smart motorways is to improve the distribution of traffic between lanes. Examination of the data showed that hard shoulder utilisation increased with traffic demand, however, it was potentially underutilised and influenced by the proportion of traffic leaving at the next junction. A multivariate analysis was carried out to establish a model which described motorway capacity during smart motorway operations using various traffic parameters. The findings from this research can be applied to assist in the application of smart motorways both in and outside of the UK, to reduce wasted time for commuters, business trips and freight movement.

It is recommended that the study is taken further with the newly introduced smart motorway schemes, which will include additional parameters such as local physical characteristics of the road (e.g. width, gradient, curvature) and the operation of All Lane Running.
University of Southampton
Ogawa, Mami Jennifer
857c3c7c-ec44-4df9-af40-f2aa534777a5
Ogawa, Mami Jennifer
857c3c7c-ec44-4df9-af40-f2aa534777a5
Hounsell, Nicholas
54781702-9b09-4fb7-8d9e-f0b7833731e5

Ogawa, Mami Jennifer (2017) Monitoring and evaluation of smart motorway schemes. University of Southampton, Doctoral Thesis, 236pp.

Record type: Thesis (Doctoral)

Abstract

Smart motorway schemes aim to address congestion issues and improve journey time reliability by utilising a set of advanced Intelligent Transport Systems applications and making use of the existing road space as much as possible. The M42 Smart Motorway Pilot, introduced in September 2006 by the Highways Agency (known as Highways England since April 2015), established the concept of Hard Shoulder Running (HSR) for the first time in the UK, together with variable mandatory speed limits during periods of congestion. Following the success of the Pilot, smart motorways are being rolled-out to other sections of Highways England’s strategic road network. This research has been carried out to understand the performance of smart motorways and its limiting factors.

A review of the concept of highways capacity was carried out to understand the parameters that influence traffic conditions during smart motorway operations. This was followed by a series of analysis using empirical data which examined the performance of existing smart motorways schemes on the M42 and M6 motorways near Birmingham, UK. Overall, smart motorway schemes have significantly reduced average journey times and journey time variability, improved motorway capacity and smoothed traffic flow. The level of benefits observed varied from one scheme to another mainly due to the different site conditions (road geometry, traffic demand and patterns). However, each scheme consistently demonstrated considerable improvements when compared to non-smart motorway conditions.

One of the aims of smart motorways is to improve the distribution of traffic between lanes. Examination of the data showed that hard shoulder utilisation increased with traffic demand, however, it was potentially underutilised and influenced by the proportion of traffic leaving at the next junction. A multivariate analysis was carried out to establish a model which described motorway capacity during smart motorway operations using various traffic parameters. The findings from this research can be applied to assist in the application of smart motorways both in and outside of the UK, to reduce wasted time for commuters, business trips and freight movement.

It is recommended that the study is taken further with the newly introduced smart motorway schemes, which will include additional parameters such as local physical characteristics of the road (e.g. width, gradient, curvature) and the operation of All Lane Running.

Text
Final e-thesis for e-prints OGAWA 22957103 - Version of Record
Available under License University of Southampton Thesis Licence.
Download (4MB)

More information

Published date: January 2017

Identifiers

Local EPrints ID: 413955
URI: https://eprints.soton.ac.uk/id/eprint/413955
PURE UUID: f361a9ac-e765-43e2-9a28-cd46d47c4319

Catalogue record

Date deposited: 11 Sep 2017 16:31
Last modified: 13 Mar 2019 19:36

Export record

Contributors

Author: Mami Jennifer Ogawa
Thesis advisor: Nicholas Hounsell

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×