Capacity analysis and optimisation of traffic flow at major intersections within the East London Central Business District using quantum flow theory: A case study of Oxford Street

Abstract

Traffic congestion represents a persistent challenge to the long-term viability of urban transportation systems, affecting numerous cities within and outside South Africa (SA). Projections indicate a worsening trend, posing a significant threat to urban life quality. Congestion detrimentally impacts traffic speed, leading to heightened journey durations, increased fuel consumption, elevated operational expenses, and exacerbated environmental pollution when contrasted with unimpeded traffic flow. Over recent decades, the escalation of private vehicle ownership across the East London (EL) metropolis has exacerbated traffic congestion, notably within the East London Central Business District (EL-CBD), specifically along Oxford Street. This study endeavours to undertake a capacity analysis and traffic flow optimisation utilising and applying a model grounded in quantum flow theory, aiming to alleviate traffic congestion within the EL-CBD, focusing on Oxford Street. The study aims to develop an optimised route assignment network design and an Integrated Transportation Plan (ITP) as part of a comprehensive strategy to enhance traffic flow efficiency at the three primary intersections within the EL-CBD. The study collects and analyses data in two phases using a quantitative research methodology. The initial phase entails disseminating and completing a structured questionnaire by 384 respondents. Subsequently, the second phase entails a comprehensive traffic survey conducted for 16 hours daily across seven consecutive days at each intersection to ascertain traffic flow patterns. The investigation reveals that Oxford Street experiences uncontrolled traffic congestion, particularly during peak hours from 6:00 to 10:00 in the mornings and 14:00 to 18:00 in the afternoons throughout the week. The study attributes this congestion primarily to elevated traffic volumes from increased private vehicle ownership, reckless driving behaviours, and limited parking availability. Identifying and quantifying congestion hotspots has emerged as imperative for decision-makers to devise effective mitigation strategies to enhance the sustainability of the broader transportation network. The paper outlines available measures, comparing and detailing their implementation on historical traffic datasets spanning daily and weekly. Enhanced public transportation systems, incentivised carpooling initiatives, localised bus services, and judicious parking management are promising strategies for mitigating traffic congestion within the EL-CBD.