What if we could imagine a city in which there were no traffic bottlenecks or jams? What if we could sail through tolls and park using an app? Could high-speed rail replace cars as our main means of transport commuting to and from work? Would travel apps with our faces, government IDs, and medical records launch us past the long security lines at the airport?
We already use computers to help us navigate our destinations, buy plane or train tickets, and in some cities, park using only our location and a credit card. Already a part of our day-to-day for many, computer vision is moving us along at a rapid rate.
Smart cities are changing the way we move
Computer Vision is being used in a variety of ways and is modernizing our transportation infrastructure for a start. Using advanced technology, computers are learning to ‘see and hear’ and make informed decisions much as humans might to make our world more efficient and safer.
Below are just a few places Computer Vision is already in play in our communities
- Traffic patterns
- Traffic signals – connected cameras watch for pedestrians as they monitor traffic flow. These connected cameras also help to optimize flow and reduce congestion.
- Street lamps – imagine saving electricity by dimming street lamp switches then turning them back on if movement is detected.
- Tolls – camera captures of your license plate billed to where it's registered and EZ Pass lanes – one pass to move across highways without slowing, stopping, or having to handle cash or coin.
- GPS warnings – red for stopped traffic, yellow for slowed traffic
- Parking apps - in cities with significant parking issues such as limited space. Imagine using a location-based service parsed into zones and your credit card to not only find a parking spot more easily, but to guarantee your car won’t be towed or mishandled.
- Clear ID - when traveling both domestically and internationally
- High-speed rail - in some cities and talks under way for more. Commuter trains are moving beyond New York and Chicago to other cities such as Atlanta, Detroit, and Dallas just to name a few.
These are just a few ways cities are being modernized for individuals. But what about on a grander scale? With the increase of online orders and demand for delivery in the last year or two, it’s estimated that over 1 million packages were delivered in New York each day. Extrapolate that to the other 49 states and the amount of traffic on the road that is strictly for deliveries soon overtakes that of individual commuters.
Computer Vision is Solving for Delivery Congestion
For many downtowns, parking can be a bear. Especially if you have a delivery van or truck. Where do you park to make your deliveries? Remember, you’re on a deadline. All. The. Time.
What if a car is parked in your loading zone? What if there’s too much traffic to park? What had once plagued urban roadways was now a bone of contention to deliver products in a timely manner. On the more negative side of these frustrations, parking revenue was virtually eliminated as the larger companies absorbed the costs into their cost of doing business. No one was getting anywhere fast.
Enter Computer Vision technology. Once the reason behind the problem was understood, cities could begin to plan for a solution. This technology could be used to help city planners understand curbside activity so they could tailor their plans based on their cities’ needs. With the proper data to make more informed decisions, cities can plan locations for passenger parking, ride-hailing lots, and delivery only zones to make more efficient use of people’s parking needs.
Next Steps Toward a Modernized Infrastructure
Curb management is just one of the options that America is working on to modernize its infrastructure. Making traffic patterns and flow more efficient is another. Imagine a plan in which pedestrians, drivers, cyclists, commuters, and delivery fleets can safely share the road while also investing in clean energy solutions. Adding in infrastructure plans to also help combat climate change makes it a win-win for everyone.
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