Making Cities More Walkable with Better Data and Technology

A city’s walkability contributes to improved health outcomes for residents, lower crime rates and increased civic engagement. Governments can use data and artificial intelligence to improve their streets for pedestrians.

by / April/May 2020

Walkable neighborhoods have long been prized among urban designers. Walkability is linked to benefits including higher property values, less crime and better health among residents. For example, one recent study found that older adults living in easy-to-walk communities not only had better physical health, but also higher cognitive functions. Another study found that walkable neighborhoods are associated with more arts organizations and higher levels of civic engagement.

There are many ways cities can become more walkable. Jeff Speck, a city planner who has written two books on the subject, Walkable City: How Downtown Can Save America One Step at a Time and Walkable City Rules: 101 Steps to Making Better Places, has identified countless ways to improve the walkability of cities such as providing mixed use development, consolidating parking, providing good transit and biking options, and even planting more trees. But in addition to improving the physical features that make cities more walkable, some cities are using technology to address this problem.

One attempt has come from the development of a “Walk Score,” a numerical value on a 0 to 100 scale that reveals how easy (or hard) it is to walk to key amenities like grocery stores, restaurants and pharmacies from any given address. This metric helps city planners, builders and residents better understand the extent to which different places are pedestrian friendly.

Cities are also using data to improve navigation for pedestrians. While there are many online map services, most are designed primarily for vehicles. And while some, such as Google Maps, offer walking directions, they are usually optimized to find the shortest route between two points, which may take walkers across congested roads or through crowded sidewalks — or even no sidewalks — even when there are alternatives.

Part of the problem is that there is little available data about pedestrian footways. Most maps treat sidewalks as ancillary data about streets, simply noting whether a sidewalk exists but providing little other useful information. To address this problem, OpenSidewalks, a project developed by a team of researchers at the University of Washington, has created a data schema for representing much more detailed information about sidewalks, allowing cities to detail the presence of marked street crossings, crossing islands and curb cutouts.

To put this information in the hands of users, the researchers launched AccessMap, a website where Seattle residents can get personalized route recommendations based on their individual mobility needs. For example, the site will provide different recommendations for an individual using a wheelchair, a powered scooter or a cane, helping users avoid steep hills or uneven sidewalks.

Others are working on projects to allow users to optimize routes based on other factors. For example, a researcher at the Alan Turing Institute is modeling air pollution so they can recommend routes that maximize an individual’s exposure to clean air, which can be especially useful to people with asthma. Another researcher is using crowdsourcing and computer vision to identify the prettiest streets, so that people can choose to take the most scenic route. All of these features require more data and better algorithms. To that end, cities should be looking for more opportunities to add new data layers to local maps, including through crowdsourced efforts and partnerships with wearables.

Finally, some cities are embedding smart city solutions in the pavement to make their communities more pedestrian friendly. The most basic examples of this are smart outdoor LED lighting systems that only turn on when people are in the vicinity. Others are more advanced. One working prototype in London uses cameras and a neural network to identify pedestrians, cyclists and vehicles, predict their paths, and use computer-controlled lights to alert people of potential hazards, such as a child walking between parked cars. For example, the lights can form an on-demand crosswalk that adapts to the size of the crowd or adjusts the distance between pedestrians and vehicles when roads are wet.

Most cities have a lot of work to do to become more walkable, and technology can be part of the solution. 

Daniel Castro Contributing Writer

Daniel Castro is the vice president of the Information Technology and Innovation Foundation (ITIF) and director of the Center for Data Innovation. Before joining ITIF, he worked at the Government Accountability Office where he audited IT security and management controls.
 

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