CASE STUDY: DEVELOPING TANZANIA’S TRANSPORT INFRASTRUCTURE MANAGEMENT SYSTEM (TIMS)

Abstract

This case study profiles the steps taken to develop a process for developing a transportation information management system protype. The case study was initiated in response to a pattern of growth whereas, Tanzania is increasingly becoming a mobile society that suffers severely from traffic congestion, delay and mobile source pollution. Meeting the challenges of greater mobility, accessibility, land use development, economic growth and revenue constraints requires that transport investment and maintenance strategies be optimized. In this case study we define transportation information management system (TIMS), in the context of the Tanzania 2014 transportation network. In doing so an argument is made for developing a base line digital transport network analysis, as a starting point. In doing so, we identify a suite of decision-making tools and a stable of performance variables. As well, this case study presents a draft: work plan which emerged during this effort. Developing effective congestion relief strategies requires going beyond the collection of geotechnical like shoulder width, guardrails, vegetation, road length and width, culverts, volume, drainage, terrain, rail crossing, number of lanes, bridges locations, and type of terrain. A comprehensive analysis of congestion requires a fully loaded transportation database with the following characteristics: regional, trunk line, and local roads; travel, time, ADT, population, employment, landuse, and income data at the regional and ward level and; transit line and multi modal infrastructure data. To test multiple congestion mitigation strategies advanced analysis tools are helpful to analyze the impact that network connectivity, pedestrian flows, population growth, travel demand, landuse, and community have accessibility. Equally important is the need have a skilled professional, and technical workforce that has not only the theoretical knowledge but also the technical training to use buffer, proximity, travel demand and simulation tools to assess the impacts of population concentrations, vehicle travel and goods movement.