A quantitative measure of congestion in Stellenbosch using probe data
Please cite as follows:
Ter Huurne, D. & Andersen, J. 2014. A quantitative measure of congestion in Stellenbosch using probe data, in Proceedings of the rst International Conference on the use of Mobile Informations and Communication Technology (ICT) in Africa UMICTA 2014, 9-10 December 2014, STIAS Conference Centre, Stellenbosch: Stellenbosch University, Department of Electrical & Electronic Engineering, South Africa, ISBN: 978-0-7972-1533-7.
The conference is available at http://mtn.sun.ac.za/conference2014/
See also the record http://hdl.handle.net/10019.1/95703
ENGLISH ABSTRACT: This paper aims to quantify and evaluate congestion in Stellenbosch, a historic university town located approximately 50 kilometres east of Cape Town, South Africa, using probe data. It is known that Stellenbosch experiences traffic congestion, but the scientific extent of this congestion has not been fully determined, as the present volume counts alone are not a sufficient form of assessment. Its residents complain about congestion suffered in town and express frustration. This, along with the fourth annual TomTom South African Traffic Index publication, which revealed that Cape Town (with a congestion index of 27%) is the most congested city in South Africa, instigated this study. Literature bares that the level of service concept (LOS) defined in the Highway Capacity Manual (HCM) has been widely used as a basis for congestion measures, although travel-time-based measures are suggested to satisfy the need for congestion information best. Travel time is well understood by both the general public and professional community, but the collection of travel time, travel speed, travel rate and travel delay data is historically deemed somewhat more complex and onerous than traffic volume counting procedures, and together with limited financial resources has restrained its application. The methodology applied in this study comprises the utilisation of TomTom Traffic Stats Portal that contains historic travel-time-based data from TomTom in-vehicle navigation systems and supporting devices. The platform and associated configuration is state-of-the-art and brings new light to travel-time-based congestion measures. The data was statistically analysed over various date and time periods, and standard congestion index concepts were applied. Congestion measures were considered along the major arterials leading into and out of Stellenbosch, as well as on part of its central road network. This paper shows that Stellenbosch evidently faces increased levels of congestion. Travel times on the inbound arterials are on the rise, and in-town traffic is becoming unsustainable.
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