Traffic Composition during the Morning Peak Period

Using registration plate analysis, this paper investigates 1) the proportions of ‘unique’ vehicles, 2) the proportions of vehicles re-appearing from day-to-day and their individual arrival variances and 3) the numbers of locally registered vehicles among those seen during the morning commute period...

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Main Authors: Tom Cherrett, Mike McDonald
Format: Article
Language:English
Published: TU Delft Open 2002-01-01
Series:European Journal of Transport and Infrastructure Research
Online Access:https://journals.open.tudelft.nl/ejtir/article/view/3675
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spelling doaj-ed68cd03500442eeb610a8a51cd54d732021-07-26T08:52:00ZengTU Delft OpenEuropean Journal of Transport and Infrastructure Research1567-71412002-01-012110.18757/ejtir.2002.2.1.36753262Traffic Composition during the Morning Peak PeriodTom Cherrett0Mike McDonald1Transportation Research Group, University of SouthamptonTransportation Research Group University of SouthamptonUsing registration plate analysis, this paper investigates 1) the proportions of ‘unique’ vehicles, 2) the proportions of vehicles re-appearing from day-to-day and their individual arrival variances and 3) the numbers of locally registered vehicles among those seen during the morning commute period on three roads in Southampton. During incidents, a traffic controller would hope to divert the more familiar drivers onto less congested parts of the network using VMS and other media. Knowing the proportions of regular and unique drivers which make up the peak commuting periods would help in the timely dissemination of this traffic information. The proportions of unique vehicles varied significantly with road and time. Vehicles appearing on more than one day formed 80% of the traffic before 08:15 but only 60% between the 08:45 and 09:00 peak period during the 1996 Bassett Avenue survey. Although the proportions of vehicles re-appearing from day to day varied significantly with road, their arrival variances were found to be very similar. On average, 65% of the returning vehicles re-appeared within +/- 5 minutes of their previous day’s time implying that this frequency of arrival could be part of an habitual behaviour pattern. The results suggest that for occasions where congestion can be anticipated in advance, such as prior to emergency roadworks or special events, warning messages would be most effective before 08:30 a.m. when the largest proportion of regular vehicles would be using the roads. If regular users are more familiar with the local road network than one-off ‘unique’ vehicles, and would be more likely to divert on receiving incident information relevant to their route, then later in the morning, the proportion of knowledgeable local drivers falls substantially. (Some mathematical expressions are not shown, please refer to the paper)https://journals.open.tudelft.nl/ejtir/article/view/3675
collection DOAJ
language English
format Article
sources DOAJ
author Tom Cherrett
Mike McDonald
spellingShingle Tom Cherrett
Mike McDonald
Traffic Composition during the Morning Peak Period
European Journal of Transport and Infrastructure Research
author_facet Tom Cherrett
Mike McDonald
author_sort Tom Cherrett
title Traffic Composition during the Morning Peak Period
title_short Traffic Composition during the Morning Peak Period
title_full Traffic Composition during the Morning Peak Period
title_fullStr Traffic Composition during the Morning Peak Period
title_full_unstemmed Traffic Composition during the Morning Peak Period
title_sort traffic composition during the morning peak period
publisher TU Delft Open
series European Journal of Transport and Infrastructure Research
issn 1567-7141
publishDate 2002-01-01
description Using registration plate analysis, this paper investigates 1) the proportions of ‘unique’ vehicles, 2) the proportions of vehicles re-appearing from day-to-day and their individual arrival variances and 3) the numbers of locally registered vehicles among those seen during the morning commute period on three roads in Southampton. During incidents, a traffic controller would hope to divert the more familiar drivers onto less congested parts of the network using VMS and other media. Knowing the proportions of regular and unique drivers which make up the peak commuting periods would help in the timely dissemination of this traffic information. The proportions of unique vehicles varied significantly with road and time. Vehicles appearing on more than one day formed 80% of the traffic before 08:15 but only 60% between the 08:45 and 09:00 peak period during the 1996 Bassett Avenue survey. Although the proportions of vehicles re-appearing from day to day varied significantly with road, their arrival variances were found to be very similar. On average, 65% of the returning vehicles re-appeared within +/- 5 minutes of their previous day’s time implying that this frequency of arrival could be part of an habitual behaviour pattern. The results suggest that for occasions where congestion can be anticipated in advance, such as prior to emergency roadworks or special events, warning messages would be most effective before 08:30 a.m. when the largest proportion of regular vehicles would be using the roads. If regular users are more familiar with the local road network than one-off ‘unique’ vehicles, and would be more likely to divert on receiving incident information relevant to their route, then later in the morning, the proportion of knowledgeable local drivers falls substantially. (Some mathematical expressions are not shown, please refer to the paper)
url https://journals.open.tudelft.nl/ejtir/article/view/3675
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