Modelling the impact of priority infrastructure on the performance of the minibus taxi services in Southern Africa

Abstract

The minibus taxi industry has grown from a modest provider of public transportation to the largest supplier to the urban public. Attempts have been made by government to regulate, integrate, and upgrade this sector but such efforts have been met with varying levels of success. Taxi drivers face immense pressure from passengers and the taxi industry to increase their performance which leads to hostile driving behaviour and often fatal accidents on the road. Transit priority measures, which are techniques used to reduce delays for buses or other forms of public transport on congested roads, have been used to advance the quality of service of buses and BRT vehicles but have not been extended to include the paratransit industry. The purpose of the study is to quantify the economic impact that these forms of infrastructure would have on minibus taxi operators, passengers, and other road users. The various forms of infrastructure were modelled to represent conditions in various parts of the city where frequent stops to load and offload passengers take place. Four alternative service options to the traditional curb-side stop were identified which included a queue-jumping lane, a queue-bypass lane, a single lane pre-signal strategy, and a dedicated minibus taxi lane. Five analytical models were developed, based on macroscopic traffic flow theory, using Excel, to gain a strategic understanding of how the benefits and costs of the infrastructure vary with different traffic conditions. It was observed that all the infrastructure alternatives result in a decrease in travel time, user cost, operating cost, and the total cost per trip for the minibus taxis. Pertaining to the car drivers, a decrease in travel time and total cost was observed because of the reduced delay due to taxi stops no longer impeding traffic. Environmentally, a reduction in harmful gas emissions was noted, particularly in the case of the minibus taxis. The single lane pre-signal strategy and the queue-jumping lane fared the best out of the five options with the lowest travel times and overall cost per hour, resulting in a decrease in total hourly cost of 56%, which consists of construction cost, user cost, and operating cost. A low-cost, commercially available drone was used to monitor the traffic behaviour of minibus taxis on a selected road segment in Pretoria in order to determine the applicability and suitability of the various infrastructure forms. It was observed that the drivers often try to cut corners and skip traffic to save time during peak traffic scenarios. In two cases driving patterns like the case modeled for the queue-jumping lane were displayed cutting time off the drivers’ trip. It was also observed that there is a shortage of infrastructure for minibus taxi operators to pick up and drop off passengers often resulting in them making informal stops that cause congestion. The time passengers save on their often-long travel distances would go a long way to redress the transportation injustices of the past. The monthly savings of over R32 000,00 per taxi driver in operating cost would serve as a subsidy to a public transportation industry currently operating unaided. It was concluded that implementing such significant changes in the public transport industry in South Africa would be equivalent to providing minibus taxi operators with much needed financial support.