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A photo of Lima
With an estimated population of around 10 million, Lima is one of the biggest cities in Latin America.

Like many urban centers in Latin America and around the world, modern Lima was built for cars. Decades ago, designing cities around cars was considered forward-looking; residents on the outskirts could more easily access jobs and shopping downtown, which in turn drew many Peruvians to migrate to the city. But as Lima’s population and rates of car ownership ballooned, so did the downsides of this car-centric approach.

By 2022, Lima was ranked the fourth most congested metro area in the world. According to World Bank analysis, only about 18 percent of all jobs in the Metropolitan Area can be accessed within 45 minutes of travel by public transport or non-motorized transport, and less than 1 in 10 Lima residents report feeling satisfied with public transport quality. The World Bank has estimated that Lima’s transport woes are costing the entire country of Peru the equivalent of 1.8 percent of its GDP each year. 

To improve the lives of everyday Limeños and boost Peru’s economy, the World Bank is preparing an ambitious 10-year investment program, led by the Peruvian government and Lima’s transportation agencies, that will rethink and revamp Lima’s transport network from the ground up.  The goals of the program are manifold: improving traffic flow, enhancing road safety, lowering carbon emissions, promoting a shift toward walking, cycling, and public transport, and redesigning neighborhoods to boost walkability.

Since it is relatively uncommon for a transport investment to have such a broad scope and scale, it is crucial that it is properly informed by reliable, robust data analysis. For this reason, a grant from the Global Facility to Decarbonize Transport (GFDT) is funding innovative data crunching work that will allow project planners to determine which roads, intersections, and other transport infrastructure to overhaul for the biggest effect. 

Among the datasets being analyzed are air quality sensor data to estimate the rate at which air pollution might improve with reduced congestion, and traffic crash data to determine the intersections and road stretches in greatest need of new safety measures. The overarching aim of the preparatory data analysis is to squeeze the maximum value from every invested dollar when it’s time for shovels to hit the ground.

One of the primary objectives of the upcoming World Bank-financed investment program is to improve traffic flow to save commuters time. Reducing congestion will provide almost two-thirds of the estimated economic benefits of the first phase of the program, and will allow Lima to more fully reap the benefits that come from high density. 

To help ease traffic bottlenecks, the data analysis team is helping Lima’s transport agency improve models that simulate traffic flow based on parameters such as traffic light timing and the volume of vehicles. High quality microsimulation models are crucial as they can allow planners to test scenarios like how giving priority to buses at a particular intersection would affect waiting times for other vehicles. The improved models will directly feed into the investment program’s plan to optimize and coordinate traffic lights at nearly 500 intersections. 

Another key objective of the investment is improving road safety at approximately 300 high-risk intersections, as well as better enforcing speed limits and other traffic rules at roughly 40 major intersections. Improving road safety not only saves lives of both vehicle occupants and vulnerable road users such as cyclists and pedestrians; it also encourages people to shift to people-powered movement such as walking and biking, which comes with climate and health benefits.

A photo of cyclists in Lima
A dedicated bike line in Lima’s Puente Villena neighborhood. (Image credit: Myriam B/Shutterstock.com)

To help with the former, the data analytics team intends to establish baseline data on factors such as property values and local economic activity so that the benefits of converting congested neighborhoods into low-traffic zones can be quantified. 

And to prepare for the bike lane work, the data team is, among other things, conducting a gender analysis to study how the addition of new bike lanes would improve transport options for women. The experience of other cities and the initial data analysis shows that women typically need to feel safe and secure to cycle, and so are more likely to bike in parts of the city that have dedicated cycling infrastructure.

Lima’s vision of a low-carbon transport system—that is, one which prioritizes walking, biking, and mass transit over the personal automobile—marks a reversal from its previous car-centric approach.  If the large-scale investment program—informed by robust data analytics—is as effective and impactful as planned, it would not only improve life for everyday Limeños; it could also serve as a model for other cities around the world seeking to undergo similar transportation transformations. In fact, a handful of intermediate cities in Peru are already considering following Lima’s example.