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Quantification of the Natural Variation in Traffic Flow
12 July South African Transport Conference SESSION 3B Frans De Jongh: AECOM Megan Bruwer: Stellenbosch University
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Traffic Variations Artificial Natural Hourly Manual Surveys Daily
Automatic Counts Natural Hourly Daily Monthly Annual
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Introduction Purpose of study: Assumptions and limitations:
Define natural traffic variations around SA Develop method to adjust traffic volumes Assumptions and limitations: Urban and rural differences not considered Applicable to higher order urban roads Traffic data grouped into regions All vehicles classifications together Limited count stations per region
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Traffic Variation Hourly Variation: Jordaan and van As (1991)
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Traffic Variation Daily Variation: Monthly Variation:
Jordaan and van As (1991) hourly variation traffic pattern remains consistent over the days of the week, with slight variation on Friday PM Monthly Variation: Karacasu, et al. (2011) observed that monthly traffic varied according to season, climate AND proximity to tourist destinations Tourist sites: more traffic in summer Climate: increase in summer traffic less significant in very hot climate
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Traffic Variation: Importance?
Representative traffic: Modeling: prepare transport models using neutral traffic with no seasonal influence (Chauke, 2015) Design of transport infrastructure: 30th highest hourly traffic volume (Van As & Joubert, 1989) 0.25 of AADT high peaking 0.12 of AADT limited peaking
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Data Collection 18 CTOS 10 regions Jan 2007 to Oct 2015
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Modification Factors Identifies the peak Scale of 0 to 1
Indicate traffic volume as a ratio to the peak Hourly Daily Monthly traffic volume
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Hourly Traffic Variation
Subject to Work / school hours Traffic congestion Road category CTOS 710: N2 Cape Town
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Hourly Traffic Variation: Weekday
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Hourly Traffic Variation: Weekday
Pretoria Port Elizabeth Bloemfontein
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Hourly Traffic Variation: Weekday
Kimberley Vryburg Potchefstroom
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Hourly Traffic Variation: Weekend
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Hourly Traffic Variation: Weekend
Durban Vryburg Port Elizabeth
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Daily Traffic Variation
Subject to Work week / weekend Public holiday Road category CTOS 710: N2 Cape Town
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Daily Traffic Variation
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Daily Traffic Variation
Pretoria Vryburg Port Elizabeth
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Monthly Traffic Variation
Subject to School terms / holiday Religious holidays Seasons CTOS 710: N2 Cape Town
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Monthly Traffic Variation
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Monthly Traffic Variation
Kimberley Vryburg Bloemfontein
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Monthly Traffic Variation
Cape Town Port Elizabeth Pretoria
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Annual Variation Economic vs Traffic Growth Rate
Traffic Growth Rate 2007 to 2015: +1.6% per annum
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Application of Modification Factors
Natural Traffic Variations Hourly Daily Monthly Annual 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 AV: Adjusted Volume CV: Counted Volume MFAV: MF for hour desired MFCV: MF for hour counted 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝐷𝑎𝑖𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐷𝑎𝑖𝑙𝑦 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑀𝐹 𝐶𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝐴𝑉=𝐶𝑉 1+ 𝑖 𝑛
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Application of Modification Factors
Natural Traffic Variations Hourly Daily Monthly Annual 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝐷𝑎𝑖𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐷𝑎𝑖𝑙𝑦 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑀𝐹 𝐶𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝐴𝑉=𝐶𝑉 1+ 𝑖 𝑛 𝐴𝑉=𝐶𝑉 𝑀𝐹 𝐴𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐻𝑜𝑢𝑟𝑙𝑦 𝑀𝐹 𝐴𝑉−𝐷𝑎𝑖𝑙𝑦 𝑀𝐹 𝐶𝑉−𝐷𝑎𝑖𝑙𝑦 𝑀𝐹 𝐴𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑀𝐹 𝐶𝑉−𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑖 𝑛
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Conclusions and Recommendations
Modification factors established on scale of 0 to 1 Use case 1: define traffic variation Use case 2: apply factors to establish peak traffic volumes Similar hourly and daily traffic variations in all regions Monthly variation quite different among regions Recommendations: Only for urban higher order roads, investigate other classes Investigate application of modification factors to calculate design volumes
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THANK YOU Questions? Contact: Megan Bruwer
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