The future of mobility is data driven. Every plan, investment, policy change, and infrastructure design will be grounded in data and evidence for decision-making. Data allows for a higher level of objectivity, precision, predictability, and consistency in decision-making. Today, the increasing digitalization of transport systems generates vast troves of data from diverse supply sources (on-vehicle sensors, roadside sensors, and cameras, smartphones) and demand-side sources (employment location, banking). Governments, researchers, and planners can harvest this data to generate much-needed insights into policies and investments’ outcomes.
In the past three years, the international transport community, with global initiatives like Sustainable Mobility for All (SuM4All), has made massive investments in data collection and compilation of knowledge on policies tested across the world to achieve sustainable mobility. Imagine what difference it will make for the sector if this catalog of policies was associated with some measurement of outcome and impact — such as carbon emissions, traffic fatalities, travel times, and economic activity?
While this may be difficult to imagine today, the vast amount of new data generated from public and private sources, along with the progress with Artificial Intelligence, makes this ambition more realistic for the future. The World Bank’s Impact Evaluations (IEs) Connect for impact program has been trailblazing this approach, using World Bank’s transport projects to build data ecosystems and inform policy choices.
The challenge of data is immense in transport. According to the report, Sustainable Mobility: Policy Making for Data Sharing, “an estimated 35 percent of the world’s largest cities and 92 percent of the largest low and middle-income cities do not have complete transportation maps. The overall level of digitalization of transportation in developing countries remains relatively low.”
Launched on March 9, 2021, the report is the first of the five papers of the “GRA in Action” series by SuM4All.
The report also discusses the opportunities and the benefits of data sharing:
- The increase of smartphone penetration and falling costs of data storage and communication infrastructure offers new opportunities. In developing countries, data from smartphones is used to map formal and informal transport services in real-time. This data could generate information to help users of transit plan multi-model journeys and create valuable insights for city planners on transport access, transit network analysis, ridership, and revenue estimates.
- The DigitalTransport4Africa and Datum efforts showcase data-sharing benefits by collecting, mapping, and integrating data from multiple transportation sources in fragmented mobility markets in countries around Africa and Latin America. Public planners and private transportation providers are also using data from Master Mobility Plans, such as household surveys, travel diaries, traffic counts in several points, and other GIS layers to understand cities’ mobility needs and address existing transportation systems gaps through new apps.
Let us look at two examples of how IE Connect has used technology and data for real impact on the ground.
- The program’s SmarTTrans team in Kenya developed machine-learning algorithms to extract data from crowdsourcing reports and other sources. It revealed 200 locations (blackspots), representing 52 percent of crashes and 55 percent of Nairobi city deaths. The program is an example of using AI to prioritize investments in 1 percent of the road network to improve urban management and will be used in shaping the road safety component of Horn of Africa’s $1 billion projects funded by the World Bank;
- In Rwanda, the program focused on evaluating the impact of rural road upgrading on market integration and household welfare. The impact evaluation focused on market prices, land prices, household consumption, and production as the key outcome variables. Results showed that households in the most remote (most impoverished) areas experienced enormous benefits from road rehabilitation; some saw a nearly 20 percent increase in income. The study has led to the commitment of more funds to rural road infrastructure development in Rwanda. The government has also adopted the data systems developed on rural roads. It will also help monitor the impact on roads constructed in Rwanda.
We are just at the beginning of a great revolution in the transportation sector. Data combined with artificial intelligence is well leveraged could generate new insights for operating transportation systems, plan for future needs, and incentivize customer behavioral changes. Of course, addressing privacy, cybersecurity, competition, and other issues will help unleash the full potential of new data sources. The benefits outweigh the risks.
Click here to learn more about the Impact Evaluation Program. For more information about the Sustainable Mobility: Policy Making for Data Sharing, please visit www.sum4all.org