Posted by aleyan 7 hours ago
PDF download: https://iase-pub.org/ojs/SERJ/article/download/215/119/726
In a similar way that Google Maps shows eco routes, it’d be fun for them to show “safest” routes which avoid areas with common crashes. (Not always possible, but valuable knowledge when it is.)
That's not gonna be something Google would research, of course, due to next to no alignment with their interests.
"A 1974 study by Hall and Dickinson showed that speed differences contributed to crashes, primarily rear end and lane change collisions"
Hall, J. W. and L. V. Dickinson. An Operational Evaluation of Truck Speeds on Interstate Highways, Department of Civil Engineering, University of Maryland, February, 1974.
This research team used Google's first-party location data to identify San Jose's Interstate 880/US 101 interchange as a site with statistically extreme amounts of hard braking by Android Auto users.
But you don't need machine learning to know that... San Jose Mercury News readers voted that exact location as the worst interchange in the entire Bay Area in a 2018 reader poll [1]
It's not a lack of knowledge by Caltrans or Santa Clara County's congestion management agency that is keeping that interchange as-is. Rather, it's the physical constraints of a nearby airport (so no room for flyovers), a nearby river (so probably no tunneling), and surrounding private landowners and train tracks.
Leaving aside the specifics of the 880/101 interchange, the Google blog post suggests that they'll use this worst-case scenario on a limited access freeway to inform their future machine-learning analyses of other roads around the country, including ones where presumably there are also pedestrians and cyclists.
No doubt some state departments of transportation will line up to buy these new "insights" from Google (forgetting that they actually already buy similar products from TomTom, Inrix, StreetLight, et al.) [2]
While I genuinely see the value in data-informed decision making for transportation and urban planning, it's not a lack of data that's causing problems at this particular freeway intersection. This blog post is an underbaked advertisement.
[1] https://www.mercurynews.com/2018/04/13/101-880-ranks-as-bay-...
[2] https://www.tomtom.com/products/traffic-stats/ https://inrix.com/products/ai-traffic/ https://www.streetlightdata.com/traffic-planning/
From the article:
"Our analysis of road segments in California and Virginia revealed that the number of segments with observed HBEs was 18 times greater than those with reported crashes. While crash data is notoriously sparse — requiring years to observe a single event on some local roads — HBEs provide a continuous stream of data, effectively filling the gaps in the safety map."
So we don't have to wait until an accident actually occurs before we can identify unsafe roads and improve them.
I'd love to see them incorporate visual detection of vehicle crash debris as well. There are two intersections in my area that consistently have crash debris like broken window glass and broken plastic parts and license plates from crashes. I know they are dangerous, but I don't know if autonomous vehicles also know that they are dangerous.
Google/Apple probably collect a massively larger amount of data than those other companies, putting those other companies at a risk of losing future revenue.
Between Google and Apple pretty much every car in the US is monitored.
Where Google/Apple's coverage is quite valuable is for near-real-time speeds for atypical events -- say like yesterday's Super Bowl. But that's not what this blog post is about -- this post is about a well-established pattern that can be identified with historical datasets.
All that to say that vendors sell a wide variety of data products to transportation planners, but just because Google is now entering this niche market doesn't mean they'll be "the best" or even realize what their strengths are.
While you're at it, give me an option to avoid unprotected left turns and to avoid making a left turn across a busy road where cross traffic does not stop. (But only during heavy traffic; it's fine when nobody is on the road.) Not only are these more dangerous, they're also more stressful and they also introduce annoying variation into my travel time.