Africa Transport Planning needs data
Privately operated minibus taxis account for the majority of public transport supply, providing vital connectivity and flexibility but with poor quality or integration. Workers living in townships like Soweto may endure one- to two-hour commutes. And minibus taxi commuters who transfer to another mode spend about 40% of their income on bus fares (Kerr, 2015).
Central to this problem is the invisibility of travelers’ daily experience due to insufficient data. Our project aims to change that. We aim to develop a collaborative, innovative technology to bring people’s access experience into unmistakable focus. Simple, accurate indicators, presented with powerful visualisations alongside resident testimonies, can help engage citizens and public agencies to make data-driven decisions.
Today only 4.7% of Johannesburg’s urban residents have convenient access to rapid transit (ITDP 2017), an especially tenuous lifeline to economic opportunity.
Public agencies typically invest handsomely in large-scale household travel surveys and traffic counts to generate data to support transport plans. Those plans include regional mobility plans and project specific plans for a new metro or BRT, for example. But these traditional data collection efforts cost so much that some cities rarely perform them, if at all! For example, Guadalajara (Mexico) conducted its last household travel survey 13 years ago in 2007. Banjul (Gambia), like many African cities, has no such data at all. Yet with rapid urbanization, cities and development agencies are making massive investments in new metros, BRTs, and roadways.
GoMetro, a South African-based technology company, and Ascendal, a UK-based transit operations and advisory firm have teamed up together to address this problem by launching the African Urban Mobility Observatory in 10 African Cities. Those cities are:
- Addis Ababa (Ethiopia)
- Blantyre (Malawi)
- Dar es Salaam (Tanzania)
- Gaborone (Botswana)
- Johannesburg (South Africa)
- Kigali (Rwanda)
- Kinshasa (DR Congo)
- Lagos (Nigeria)
- Maseru (Lesotho)
- Mwanza (Tanzania)
Mobility Observatory Big Data Application explained
Our solution offers a quicker, more cost efficiency, and more accurate way to generate that same data. By using a suite of Big Data technologies, we can quickly learn about a region’s or community’s travelers, and enrich the data further to generate useful insights. Our data can be directly useful as inputs to traditional four-step travel demand models, which are used to support major investment decisions — with better quality and at a fraction of the cost of traditional household travel surveys.
The GoMetro and Ascendal Mobility Observatory will establish an interactive web data platform, powered by Big Data technologies, to deliver unprecedented data and insights on Soweto residents’ mobility. Users will be able to explore useful indicators of access – such as job accessibility, bus access, affordability, congestion, safey, sexual harassment, OD patterns, and more – by gender, race, income, and neighborhood. The Observatory will make real people’s experience visible through engaging charts, maps, and interactive visualizations.
The Mobility Observatory Indicators and Dataset
|Mobility Indicator||UMA||Digital Survey||Field Survey||APIs||Desk Research|
|1.1. Mode Share||✔✔||✔||✔|
|1.2. Public Transit Access (SDG 11.2):||✔✔||✔|
|1.3. Affordability Index: household monthly income spent in transport, as % of minimum wage for 50 public transit trips||✔||✔✔|
|1.4. Accessibility: % jobs & services people have access to in 60 or 90 min||✔||✔||✔✔|
|2.1. Travel Time: Average in peak hour in mid-week||✔✔||✔||✔|
|2.2. Congestion Index: Ratio free flow over congested speed (peak hour)||✔||✔✔|
|2.3. Vehicle Occupancy: average number of passengers by private vehicle||✔✔|
|2.4. Farebox recovery: % of transit operational costs recovered with fares||✔✔||✔|
|3.1. Public Transit Reliability||✔||✔✔|
|3.2. Public Transit Comfort: Crowdedness||✔||✔✔|
|3.3. Transfers: Avg. # in transit trips||✔✔||✔||✔||✔|
|4.1. Road Mortality Rate: Number of traffic fatalities per 1.000 inhabitants||✔✔|
|4.2. Average age of vehicle fleet||✔||✔✔|
|5.1. Crime Rate: Number of crime incidents in public transit per 1.000 users||✔✔|
|5.2. Safety Perception in Public Transit||✔✔|
|6.1. Sexual Aggression Rate: Number of sexual aggression incidents in public transit per 1.000 users.||✔✔|
|7.1. Distance travelled: Vehicle Km Travelled (VKT) per day per user||✔✔||✔||✔||✔|
|7.2. Transport-related emissions: CO2 Tons from vehicles, related to GDP||✔||✔||✔||✔✔|
|7.3. Transport-related emission cap for 2025||✔✔|
|7.4. Technology: % of clean-energy vehicles of total in public transport||✔||✔✔|
|7.5. Clean-energy vehicles Goals in 2025||✔✔|
|7.6. Regulation: Emissions and noise standards for new vehicles||✔✔|
|7.7. Fuel quality: Particles per million (ppm) of regular diesel fuel||✔✔|
The Innovation Opportunity
A key technology and outreach challenge of this project will be to include residents without access to smartphones. We want to broaden the Observatory’s applicability to poorer cities and communities, especially in Africa, where smartphone penetration may be lower than other regions, and where the need for mobility data is also greatest.
We will develop technology, indicators, and outreach plans for the project. For example, we may use SMS marketing, in partnership with MTN or Vodafone, to engage residents without smartphones, and invite them to take either our web or USSD travel survey. We also will develop sampling targets, by demographic and location, with specific error ranges and confidence levels. We will need to design the surveys and outreach process carefully to ensure statistically valid samples. In addition, we will develop partnerships with local apps, if available, to embed our UMA SDK to observe traveler movements. We may use artificial intelligence to train our UMA SDK for accuracy in a South African context
Next, we will deploy the suite of Big Data solutions. We will generate data and monitor demographics against sampling targets and adjust outreach as needed. Then we will depersonalize and analyze data to measure indicators; and upload the data into our web data platform to generate visualizations. Finally, we will discuss findings from the Observatory with local stakeholders and explore policy and project priorities that may result from the analysis. Here, we will draw upon our team’s transport planning expertise. We will also review lessons learned from the experience to broaden the Observatory’s applicability.
Significant backing from UKAid and DFID
The High Volume Transport Programme (HVT) is delighted to announce that 10 research projects have been commissioned following the recent Open Call for co-created research – and the GoMetro African Mobility Observatory is one of these projects. These projects will produce research that will help increase access to transport services and make transport more inclusive, safer and greener in low-income countries (LICs). These projects are especially crucial at this pivotal time for the transport community, with COVID-19 presenting unprecedented challenges. All 10 will be implemented across countries in Sub-Saharan Africa over the next 14 months to two years. Countries of implementation include Nigeria, Sierra Leone and Ghana in West Africa, Tanzania, Ethiopia and Kenya in East Africa and Zimbabwe, South Africa and Mozambique in southern Africa. This important milestone represents a significant commitment from the HVT Research Fund for projects focussing on the key research priority areas of climate and inclusion identified in Part 1 of the programme.
What makes this project even more exciting and relevant is that UN-Habitat, Wuppertal Institute and UEMI are joining our Consortium to deliver this programme in the cities we have identified as high-priority and high-potential for our technology.
Why this matters
The Observatory, by measuring and publishing key performance indicators, will help planners, researchers, and decision makers engage around priorities. The Observatory will enable better understanding of urban transport and land use. It will foster research, promote engagement and discussion, and enhance public agencies’ capacity to develop and manage transport policies. It will facilitate regional and global cooperation among authorities, professionals, social organizations, and users. And it will catalyze finance and implementation of sustainable mobility projects.