Priority index for road maintenance interventions of greater Kampala metropolitan area based on rout choice.

Abstract

Road infrastructure requires timely maintenance interventions to serve through its design life. Literature indicates that natural and artificial phenomena like adverse weather negatively impact roads resulting into permanent deformation and as such, institutions around the world deploy different maintenance methodologies to improve resilience using different forms of priority indices like AHP and Fuzzy Logic technique. The study discusses the limitations of AHP and Fuzzy Logic technique while proposing the use of CCTV camera data to generate a priority index based on user route choices. Using simple random sampling technique, roads within GKMA with different traffic counts within a period of seven months were selected and a route choice model was used to predict user route preferences. Pavement visual condition analysis was also undertaken. Results revealed that roads with higher vehicular traffic volume exhibit more extreme level of damage, consequently increase travel time and affect travel speeds. The projected growth of traffic demand by 29.52% highlights the escalating challenges faced by the transportation network in the GKMA. This growth underscores the necessity for proactive planning and infrastructure development to accommodate the increasing demand while considering the revealed preferences of commuters. The results provided valuable insights for policymakers and urban planners by revealing the trade-offs individuals make when choosing routes, the factors that induce indifference, and the homogeneity of preferences within the studied population. The study provides evidence that a maintenance specific priority index that is based on route choice will aid policy makers and engineers to make decisions on criteria selection for road maintenance and also predict future traffic volumes on roads to guide transport system improvements and traffic police deployment decisions on point of traffic congestion. Route choice analysis gives valuable insights on decision making patterns and preferences of users in aggregate context. This is important in making decisions on allocation of resources to maintain the transport network operating at high serviceability