We invite you to imagine a future where LA's streets are maintained not because someone yells into a phone or when someone needs to reports a pothole via an app but rather that the city is able to see which street is degrading faster than others and allocate maintenance and repair resources proactively.
Imagine a future where the bike commute to your co-working space is defect free.
Imagine a future where autonomous vehicles are able to visit every street in the city and deliver services to inner-neighborhoods because of the maintenance good quality pavement markings.
Today, our streets, our single largest civic asset, are maintained by heroic public workers who ensure we have comfortable rides. What if this heroic effort was supported by data, intelligently, to allow those public workers do more with less redundancy and make better, more equitable decisions about our streets?
Street QUality IDentification (aka SQUID) is a new way of measuring the ground truth about LA's and California's street conditions.
SQUID combines street imagery with ride quality data to create a new generation of the antiquated Pavement Condition Index (PCI), a standard first developed by Army Corps of Engineers in the 70s. The PCI relies on analog, labor intensive, and error-prone methods and has changed little in 40 years. PCI scores are used to decide how billions of dollars of public money are spent for street maintenance.
We can do better.
Consider that just 1% of LA BSS's annual budget could fund a dedicated team of public technologists for 5 years committed to ensuring that local street maintenance is performed efficiently using ground truth data, in an open and transparent manner. Moreover, this would also prepare the city for inevitable autonomous futures.
On April 3, 1988, the LA Times Magazine published a 25-year look ahead envisioning what Los Angeles would look like in 2013. Its cover; shiny streets with futuristic, possibly autonomous cars transporting Angelenos to home, work, or play. 4 years into that optimistic future, we are only just seeing the shiny cars but sustainably maintaining smooth city streets still seems like a distant future.
SQUID is an opportunity to pioneer a new way for Los Angeles and California at-large think big and think local in the same stride. The recently passed SB1: Road Repair and Accountability Act of 2017 allocates $15 Billion to local street maintenance over the next decade potentially paving the way forward to preserve the bottom line for many Californian cities.
SQUID is a bottom-up approach to ensure that the top-down is allocated fairly. It is a standard built using open technologies such as Open Street Cam, a mobile app that collects and transmits street imagery in real-time. As data about all streets is collected, ARGO's public data infrastructure is deployed to integrate with existing city road inventory to allow BSS managers make proactive maintenance decisions and allocate repair and maintenance resources more efficiently all while ensuring accountability.
The SQUID program works to also ensure that street analytics is made accessible and workable by anyone through a street data heroes workshop process that will introduce foundational concepts in how to collect, analyze and tell stories using Los Angeles street data.
SQUID deployed in Syracuse in April 2016. Collected 520 miles ~ 110,000 images of Syracuse street conditions in 10 days.