When investors envision the ways technology will transform transportation in the not-too-distant future, the big innovations that first come to mind are usually in the realm of self-driving cars and trucks. Some startups are even working on prototypes of autonomous air taxis. What goes overlooked in all the hype surrounding autonomous driving, though, is that the technology already exists for equally impactful advances in another realm, one that will eventually overlap with self-driving systems.
Today, urban areas all over the country are struggling with traffic congestion and delays that hamstring commuting, retail deliveries, ride-hailing services, and public transit alike. This is largely because curbsides have become some of the highest-demand real estate in cities. Drivers pull up to their destinations, observe overcrowded lanes with no accessible curb space, and then pull back into traffic to continue circling until a spot opens.
On-street parking provides more customers for stores and steady revenue for municipalities. But drivers looking for spaces must contend with buses and Uber or Lyft drivers looking for spots to pick up or drop off their passengers. Then you have the increasing popularity of on-demand deliveries taking place alongside traditional shipping services. Add to all this the growing popularity of bike lanes and public scooters, and you have a recipe for chaos.
The current approach to managing all these competing services is essentially not to. In most cities, it’s first come first serve when it comes to parking and deliveries. There’s some planning involved in setting up municipal, on-street spaces, and individual businesses may arrange to have designated spaces for deliveries. But the overall management policies, if there are any, tend to be patchworks based on a history of ad hoc punitive measures or parking code and expired meter violations. Comprehensive planning and organization of these spaces based on business rules is almost nonexistent.
That’s why companies like FedEx and UPS simply accept that their drivers will be ticketed on a regular basis in their efforts to make deliveries on time. Instead of even bothering to negotiate for fleetwide permitting or reserved spaces, which would too often be taken by other drivers regardless of whatever signs are put up to prevent them from doing so, these companies have resigned themselves to settling up with municipalities at the end of every year. The only negotiating they do is for reductions in the fines, which total in the tens of millions of dollars.
What would it take to implement a plan for a more efficient and better organized curbside?
Lots of Ideas but Little Data
In place of the maddening and messy free-for-alls that are taking place along curbsides in cities all over the nation, imagine a system operating with the consistency and precision of a finely crafted timepiece. Buses make stops without having to compete for space. Uber and Lyft drivers are directed to lanes and spaces reserved for drop offs and pickups at designated times of the day—perhaps the same spaces used by the buses at other times. People on bikes and scooters ride along specified lanes without fear of other vehicles swerving into their paths. And businesses can depend on timely deliveries from freight carriers who don’t have to rack up fines for parking violations. Commercial fleets, meanwhile, work with municipalities to strike deals for parking permits in delivery zones instead of paying fines for unavoidable violations.
There are lots of principles at play here. Buses and delivery vehicles operate at least somewhat according to schedules. Railing-sharing services experience more demand at certain times throughout the day. On-street, public parking can be set up in advance to charge drivers varying rates according to how high the demand is in the area. Commercial vehicles could even use a license plate number or other identifier to grant them access to curb space by cross-referencing their ID with a company account.
Cities like San Francisco are already moving toward systems of camera-based enforcement of permitting rules. And the District of Columbia has implemented a paid permit control policy that allows commercial vehicles to load and unload during predetermined time periods while allowing unpermitted drivers one-time access to the loading zones through payments made via mobile apps.
What’s stopping city planners elsewhere in the country from implementing curb management systems like this? First, effectively managing all the (literally) moving parts requires copious data that is, so far, unavailable. Data on vehicle type, time of day, purpose for stopping, duration of stops, weather conditions, and volume of other vehicle types on the road would go into not only the development of an initial management strategy but they would also inform ongoing tweaks and adjustments to account for changes in traffic over time.
Whose Curb Is It Anyway?
The second obstacle to precision curb space management is resistance from the various stakeholders. Try telling a store owner that you’re removing some public parking spots in front of the entrance. As Danielle Harris, director of mobility innovation at Elemental Excelerator, explains, messing with parking spaces “is like taking someone’s first-born child in a lot of ways, because, … with street projects that’s when the pitchforks come out.”
Anytime you’re talking about organizing the use of a public resource, competing individual interests are going to object to any arrangement that strikes them as unfair. Often, they’ll even object if there is no perceptible disadvantage for them simply because they’re concerned about any changes to their existing setup. Bus drivers may not want to share their drop off spaces with Amazon delivery vehicles, even after you’ve assured them they’ll be using that space at different times.
The most effective way to head off this kind of resistance will also rely on data. If you can demonstrate with actual numbers how the new system will benefit everyone with a stake in the project, then you’ll have a much easier time getting buy-in. This can be tricky, though, since some of the benefits will only accrue long-term or come about indirectly. The store owner, for instance, may have fewer parking spaces close to the entrance, but with more Lyft or bus drop-offs, overall foot traffic to the store may still increase. Better flowing traffic in general may even result in more people willing to visit the area. Hard numbers, even if they’re merely projections, will help paint these pictures in a more convincing way.
So, if data is the main missing element, where can curb space managers find it?
Data for Discounts
Many cities are already using sensors to monitor the comings and goings along their curbs. These sensors can tell whether and for how long a space is empty or occupied but getting any details beyond that is difficult. Is the vehicle in the spot a bus or a truck making a delivery? Most sensors won’t be able to distinguish between the two. In-ground sensors also function poorly under snow and ice—and are often damaged by plows.
The best data for managing curbsides comes from video cameras and machine learning programs that recognize a variety of vehicles. The cameras can be mounted near the curb itself—or even in storefronts—and used to create models of how the space is being used. These models can in turn serve as the basis for creating a new system that makes optimal use of the space while keeping traffic flowing as smoothly as possible.
Curbside cameras come with two major issues of their own, though. First, many people simply don’t like having cameras watching their every step. Private business can get away with mounting cameras on their premises because it’s understood they serve security purposes. But cameras on a public street can be counted on to make civil libertarians squirm. The second issue is that the amount of actionable data you can get from stationary cameras along the curb is limited. You could get a much richer idea of what type of vehicles are doing what in a particular area with cameras mounted on other vehicles.
It so happens there’s an emerging trend among commercial fleets to outfit their trucks with cameras and telematics. Fleets are installing these technologies in an effort to combat the skyrocketing cost of insurance, which is putting many transportation companies out of business. The cause of the premium increases has been tied to more aggressive litigation on behalf of plaintiffs’ attorneys in cases involving crashes. Video footage from these incidents can exonerate drivers on the spot, but cameras and telematics are also powerful tools in driver training. Fleets are using these technologies to improve their safety records, which they can in turn parlay into lower insurance premiums.
Now, if several fleets are already collecting copious video data for their safety programs, and if municipalities need that same kind of video data to streamline curb space management, then we have a big opportunity for a mutually beneficial arrangement between fleets and local governments. Just one possible avenue to achieve such a win-win outcome would be to have fleets transmit their telematics data from the road to a database maintained by the municipality. The city can collect the data from multiple vehicles and incorporate it into a highly detailed model of how traffic flows through a particular zone.
In return for access to data from a fleet’s onboard cameras, the city can offer discounted permitting or preferential access to high-demand loading zones. And this would mean giving fleets an added incentive to invest in safety tracking technologies. So, trucks would have an easier time making deliveries, traffic would flow more smoothly through the area, data-based models would be used to create curb space policies that benefit drivers, businesses, bikers, and public transit users alike, and urban travel would become much safer to boot.
Curb space managers in the future will likely rely on data from a variety of sources—the safety systems on trucks being just one of them. Eventually, autonomous vehicles will take over the roads, and the communication from self-driving cars and trucks to technological components of local infrastructure won’t just go in one direction. Vehicles will transmit data both to other vehicles and to systems used for managing traffic as well as other functions such as purchasing goods and services seamlessly. And those systems will transmit data back to them to ensure efficient navigation, safe driving, and optimal convenience for anyone along for the ride.
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