# Using Waze to Evaluate Traffic Costs

## 21/11/2016 by pablo.cerdeira@gmail.com

How to choose where to fight traffic jams and how much to spend in each area considering our citizens’ behavior?

In this example, we used Waze data generated by the people to measure the traffic impact for each area in the City of Rio de Janeiro.

According to two different analyses by FIRJAN and FGV, Rio loses among 8% and 10% of its GDP every year as a consequence of the traffic. Considering Rio’s GDP in 2012 (around R$220 billion), it would represent loses between R$ 18 billion and R$22 billion per year. Although relevant, those analyses didn’t provide two essential information: a. Where the traffic problems occur, and b. The number of people affected by it. To make the analyses by FIRJAN and FGV useful, we used Waze data to answer those two previous questions. ## 2. Traffic location With the data provided by Waze, we were able to: (i) measure the average speed for each road segment per hour, (ii) compare the average speed during morning and night peaks with the free flow speed (measured between 2 AM and 4 AM), (iii) count the total amount of traffic jam alerts reported by the citizens through Waze app during the morning and night traffic peaks. It allowed us to identify the 30 worst traffic spots regarding the average speed and the number of people affected by it (extrapolating the number of individual sending traffic jam alerts). These 30 most important traffic spots accounted for 26.4% of the total traffic of the City. So, with this information, we were able to distribute the total traffic loss (9% of Rio’s GDP, the average of 8% and 10% according to FIRJAN and FGV) per each traffic area. It allowed us to add a price tag for each traffic spot. ## 3. People affected by the traffic Using the number of individuals reporting traffic problems, we were able to calculate de density of citizens affected per area. This information was crucial to us to understand not only the cost of the traffic but also to choose where to focus our attention considering the number of beneficiaries. ## 4. Measuring ROIs The cost of each traffic spot and the number of affected people also allowed us to evaluate the Return On Investment - ROI for the planned solutions for every traffic area. In the example in the presentation below we show an ROI evaluation for the Bicalho Avenue. We were losing around R$ 840 million per year in this area. The proposed solution, the BRT Transbrasil, would cost R\$ 1.3 billion. So, if the BRT Transbrasil reduced the traffic in the Bicalho area per 50%, it would “generate profit” in less than 4 years.

The presentation below brings some examples and images of the model developed by us, in the PENSA Team.

Pablo Cerdeira is the Head of the Center of Technology and Society - CTS/FGV and the former Rio de Janeiro's Chief Data Office