What is Giving Compass?
We connect donors to learning resources and ways to support community-led solutions. Learn more about us.
Giving Compass' Take:
• Smart Cities Dive discusses transportation issues in this country and how data often falls short in addressing them, mainly because the numbers don't take into account individual needs enough.
• The urge here is to create a more holistic approach to transportation policy, especially as technology continues to disrupt the industry. How can we get people to ditch their cars for good, helping the environment and reducing traffic problems?
• It would be good for our health, too. Here's the connection between car pollution and diabetes.
Over the last few months our smart cities team has had dozens of deep dive conversations with principals at various departments of transportation, innovation offices and planning agencies across the United States. While these agencies have access to more data than ever before, the cities and municipalities don’t have a true understanding how their residents move through the transportation system and whether or not the core needs of the city and/or municipality are being served by their current system.
This evolving dynamic mirrors our dynamic journey here at Arity and as we continue to dive deep into this massive topic we are learning that the potential solutions to this challenge are not easy — and its going require all of us to tackle several different problems at once, here are three that we have observed.
As we heard many times, transportation planners are drowning in data — but the data that is most readily available are often volumes and counts of traffic or ridership. However, this specific type of data does not help transportation planners who are grappling with a fundamentally different set of questions: How can transportation network companies (TNCs) complement first/last mile service for public transit? Will autonomous vehicles cause or alleviate congestion? How do we ensure equitable access to mobility services?
To understand these complex questions, mode-centric data falls short. Because there is no concept of the user or customer in these datasets, it is difficult to understand how residents link multiple modes together to reach their destination, without relying on inference.
Read the full article about the challenges of user-centered transportation by David D'Silva at smartcitiesdive.com.