RE-ENGINEERING OF TRAFFIC SYSTEMS IN THE CENTRAL BUSINESS DISTRICT (CBD) OF A SOUTH AFRICAN CITY: THE CASE OF KIMBERLEY CITY

Abstract

Most cities of the world face the challenges of dealing with traffic congestion and its undesirable consequences. In South Africa many large and medium sized cities– and specifically the central business district (CBD) thereof – are experiencing traffic congestion and are severely affected by it. One such city which warranted this investigation, is Kimberley in the Northern Cape Province. Because of its unique physical and spatial attributes; its road network; economic characteristics and the requirement of the mobility of heavy vehicles in addition to the normal city traffic, Kimberley experiences typical traffic congestion challenges in its CBD area, particularly during peak hours. Thus, using the city Kimberley as a case study, an investigation was conducted to comprehend the traffic congestion scenario on the roads in and around Kimberley’s CBD area with the aim to evolve plausible re-engineering interventions that could alleviate the traffic congestion challenges experienced by the city. The conduction of the study involved the critical review of relevant literature, understanding of the control variables influencing traffic congestion and applying relevant empirical models to assess traffic congestion and evolve policy/strategic measures to alleviate the challenge. A survey research methodology was used for the collection of data, followed by statistical analyses of the data and the application of empirical models to assess the level of traffic congestion on the roads of the study area. Simulated scenarios based on different re-engineering interventions were then evolved, which assisted in engendering policies and strategic interventions that could reduce traffic congestion and improve smooth traffic flow in and around the Kimberley CBD area. In this regards, the following major factors usually causing traffic congestion in and around CBD areas were investigated. They are traffic volume; type and composition of vehicles; specifically plying of heavy vehicles (large trucks); on-road parking facilities; type of junctions; traffic speed; inadequate number of lanes; inadequate turning radii; insufficient lane width/ road width (capacity); inadequate availability of space near junctions; availability of commercial function; availability of traffic nodes such as bus and taxi stops; and availability of civic/administrative functions close to the roads. The study indicated an appreciable level of traffic congestion on some of the roads in the Kimberley CBD area –specifically during peak hours– which needs strategic intervention. The results of the application of empirical models such as Segment delay (Ds), Travel time index (TTI), Q index, Level of Service (LOS) and Queue length suggest that two of the major roads, namely Long Street and Transvaal Road (impacted by Pniel Road), are experiencing high levels of congestion during both normal and peak hours. Similarly, some of the other roads such as Bishop Road, Carter Road and Barkley Road (impacting Transvaal Road) and Schmidtsdrift Road are a cause of concern during peak hours. Future scenario analyses indicated that these roads – i.e. Long Street, Transvaal Road (Phakamile Mabija Road), Bishop`s Road, Carter Road and Barkley Road – will become severely congested. Besides, junctions connecting Long Street and Bultfontein Road (J1); Bishop-/Lyndhurst Street and Bultfontein Road/Delham Street (J2); Transvaal Road and Cecil Sussman Street (J3); and Transvaal Road and Old Main Street (J5); experience high queuing lengths during peak hours and are seemingly under pressure with regard to congestion. However, the following re-engineering interventions this study envisages for the year projected year 2025 should reduce congestion on the roads in and around the CBD area of the city: appropriate traffic diversion from the congested roads to relatively less congested roads during both normal and peak traffic hours; segregation of heavy vehicles and the diversion of the appropriate proportion of normal cars during peak hours; optimal use of less congested roads for carrying diverted traffic; prevention of use of on street parking facilities during peak hours; and modification of signalling cycle time at major junctions during the peak hours. It has been determined that by adopting a policy of diverting a minimum percentage traffic from Long Street (20.77%), Transvaal Road (28.80%), Bishop Road (15.11%), Barkley Street (12.73%), Barkley section 2 (9.0%), Carter Road (14.10%) and Cecil Sussman Road (20.77%) and assigning all this traffic in the following proportions to Memorial Road (12.23%), Du Toitspan Road (20.77%), Lyndhurst Street (20.77%) and Main Street (25.80%), would appreciably reduce the traffic congestion in the congested roads without increasing the level of traffic congestion on the relatively free roads. Similarly, by adopting a policy, of diverting a minimum percentage of traffic from Long Street (33.71%), Transvaal Road (40.05%), and Bishop Street (17.79%) during peak periods in projected years and assigning this traffic in the following proportions to Memorial Road (25.0%), Barkley Road impacted by Pniel Street (25.0%), Du Toitspan Street (28.43%), Lyndhurst Street (28.43%) and Main Street (28.43%), will not significantly increase the level of traffic congestion on these roads whilst enabling the reduction of traffic congestion on the roads under pressure of traffic. Furthermore, simulated scenarios of traffic diversion based on travel time ratio and change in speed, show that with a reasonable level of diversion of traffic from congested roads to less congested roads, speed can be increased and travel time can be reduced on the roads in the CBD area of the city, thus allowing roads to be optimally utilised. These results also established the following two hypotheses on which this investigation has been based: 1) Segregation of traffic (modal split) will appreciably reduce traffic congestion in terms of improved LOS, less travel time and reduced delay on the roads in the CBD; and 2) Optimal traffic assignment (diversion to alternative roads) will significantly reduce traffic congestion in terms of improved LOS, less travel time and reduced delay on the roads of CBD. It can thus be concluded that re-engineering solutions such as traffic diversion from the congested roads to the under-utilised or least congested roads with appropriate traffic assignment and modal split (segregation of vehicles) could assist in easing the traffic congestion, increasing speed and reducing travel time, resulting in optimal utilisation of all the roads in the CBD area of the city.