Some cities are turning to digital monitoring to replace traditional processes, enabling more frequent and accurate assessment of infrastructure quality.
This story was originally published by Data-Smart City Solutions.
America’s roads need help. In a 2013 report on the state of U.S. infrastructure, the American Society of Civil Engineers gave road infrastructure a ‘D’ grade. According to the report, 32 percent of America’s major roadways are deficient, with particular concentrations of disrepair in urban areas: while only 15 percent of vehicle miles traveled on rural interstate highways are over pavement considered deficient, the number jumps to 47 percent in urban areas. These poorly maintained roads cause vehicle damage and waste gasoline, costing the average American driver $324 each year.
Cities are looking for ways to direct their street improvement resources more effectively, given the limited personnel to monitor streets and anemic funding for repairs. For instance, city of Boston employees currently conduct a visual survey of each street in the city every three years, a method that is expensive, time-consuming, and leaves streets unmonitored for years at a time. To improve upon this system, some cities are turning to digital monitoring to replace traditional techniques, enabling more frequent and accurate assessment of infrastructure quality. These digital methods primarily fall into one of two categories: vehicle-based monitoring systems, which collect data via an array of sensors attached to a vehicle (usually owned or contracted by the city), and smartphone-based monitoring systems, which leverage built-in smartphone functionality to gather road data.
Vehicle-based monitoring systems outfit vehicles with a variety of sensors to continually track the path they travel and provide a profile of the street conditions encountered, creating more consistent and objective data than is collected in traditional road surveys.
Spun off from a research initiative at Northeastern University, StreetScan is one such system, providing a suite of monitoring tools and analytic software designed to empower cities to gather road data cheaply and efficiently. Using GPS, radar, microphones, cameras, tire pressure sensors, and an accelerometer, StreetScan collects a wealth of data about street condition, material, and points of concern without requiring the city to purchase the equipment itself (which can cost hundreds of thousands of dollars)–an appealing proposition in an era of limited capital budgets.
Cincinnati adopted the vehicle-based approach to street condition monitoring in 2015. With a reduction in federal and state transportation funding following the 2008 recession, Cincinnati needed to look for ways to target its limited funding to address the streets in the worst condition. City officials partnered with local firm INFRAME to compile a comprehensive picture of their street conditions using a PaCE (Pavement Condition Evaluator) van equipped with cameras, lasers, and other monitors – similar to the StreetScan setup – which identifies road surface issues and provides georeferenced images with a one millimeter resolution for the city to use to direct its efforts. Using funding from their flexible Capital Acceleration Plan, the city hopes to improve consistency in their process, build a safer road network, and to save money in the long run by proactively addressing road needs.
Other cities and researchers have experimented with monitoring street quality using the built-in GPS, camera, and accelerometer functionality of smartphones. These monitoring systems are ideally placed on city vehicles that already travel the city daily (such as public works trucks), or used to assess street quality through crowdsourcing, much like Waze’s traffic monitoring.
In a 2015 pilot, Carnegie Mellon researcher Christoph Mertz partnered with the city’s Public Works Department to install smartphone cameras in city vehicles to capture images of the streets in Pittsburgh. Paired with GPS data and fed through a computer algorithm, these images are classified according to the types of road surfaces and the damages pictured, something the city hopes will help them identify sections of street that need the most urgent attention. Still in testing and development, Mertz’s approach might appeal to cities hoping to get a foot in the door of street quality analytics by pursuing an affordable option that can be used continuously. Similarly, Canadian startup TotalPave provides cities with a smartphone app that records overall road quality (measured via the phone’s accelerometer) and manually tracks individual issues, such as potholes. Comprehensive data and analysis tools are then available through a cloud-based web portal. TotalPave, which costs cities little more than a smartphone and was the recipient of $100,000 in a venture capital competition in 2013, aims to start with a portfolio of 38 cities and expand from there, eventually targeting more than 13,000 North American cities, all for a fraction of the cost of renting or buying a monitoring van.
When used in vehicles on daily routes around a city, apps like these can collect a wealth of data while requiring minimal time or effort from city employees and can eliminate many single-purpose street survey efforts. However, the idea of crowdsourcing street quality data from citizens holds the potential to create an even larger, richer dataset.
Boston – in recent years, a frequent early adopter of civic technologies – launched Street Bump in 2012. Pioneered by the city’s innovation office, New Urban Mechanics, this free app (iPhone only) is Boston’s take on smartphone-based street monitoring and is open-source, so other cities can use and improve it. By aggregating the experiences of hundreds or thousands of drivers who traverse the streets of a city, technologists and city officials hope to uncover insights about road quality which would otherwise require intense labor from city workers. With dozens of phones reporting poor conditions on a road each day, these once-hidden problems become readily visible to city officials and can be prioritized for repair.
Looking forward, it seems likely that more cities will find value in automating their road quality monitoring, using either high-tech vehicles or the collective insights of the thousands of drivers who travel their streets each day.
If recent news from the tech world is any indicator, the future will include a bit of both. Last year, Google–parent of the Android smartphone operating system and aspiring pioneer of driverless cars–filed a patent for a system employing GPS and an accelerometer to monitor road conditions. The patent discusses both vehicle-mounted and smartphone components, but given its source, we might expect to see it incorporated into self-driving cars of the future.
In the future, we are likely to see digital techniques continue to replace visual surveys by city employees for reasons of accuracy, efficiency, and cost. Cities that can afford it may opt for the detail of vehicle-based systems, while smaller cities or those strapped for cash will likely elect to take the cost-effective path of smartphone-based systems. And if efforts like Street Bump and Google are successful, crowd-sourced road information may eventually make dedicated city road monitoring efforts obsolete.