This is the second of a two-blog series about optimizing curb space for loading zones. Part 1, here, focuses on the first steps transportation authorities can use to better manage loading zones. Part 2, below, digs deeper into the factors involved in pricing loading zone curb space.
Whether it’s called value pricing, performance pricing, dynamic pricing, or variable pricing, managing demand for loading zones and other curbside space won’t work by using a “finger in the air” approach.
It’s a complex process, one that requires advanced analytic expertise, involving data scientists who use algorithms and machine learning to optimize pricing to meet municipal demands. Implementing demand-based, progressive pricing generates multiple new opportunities to improve curbside lane efficiency at meters and in loading zones.
The use of demand pricing can help influence travel decisions, such as:
- Whether to drive – for city leaders who choose to promote alternative modes including mass transit, bicycles, or other transport modes.
- When to drive – to help shift trips to times when demand may not be as high.
- Where to park – to encourage walking a few blocks, to reduce time spent traveling or searching for a parking spot.
Properly priced loading zones will help ensure curbside availability, while also allowing cities to monetize available curb space.
Additional opportunities to further improve curbside loading zone efficiencies include:
Automate invoicing. Given both the volume and variability of deliveries made throughout the day, automating the billing for loading zone stays will help reduce illegal parking and provide an efficient alternative to requiring drivers to pay for each individual stay. Fleet registries can allow for large and small companies alike to update license plate information and receive a single invoice, calculated based on the loading zone rates and length of time parked. Further, the registry will ensure that delivery companies and other operators are not cited erroneously.
Integrate enforcement. In addition to making it easier for delivery operators and Transportation Network Companies (TNC) to comply, computer vision can capture data needed to document both compliance and non-compliance, communicating the latter efficiently and accurately to officers to cite illegally parked vehicles based on their proximity to a loading zone. Cities may even be able to send citations by mail, which would allow officers to focus on compliance with other regulations that have a greater impact on public safety.
Evolve with technology. Several years ago, sensors offered the best means of collecting space-by-space utilization data. ‘Asset lite’ models improved the return on investment of these devices. Now, computer vision offers cheaper and more flexible alternatives for data gathering. Soon, cameras will likely be supplanted by telematics and real-time vehicle positioning data. Today’s intelligent curb lane management solutions must allow for the inclusion of tomorrow’s transformative technologies.
The bottom line is that municipal leaders have more tools than ever before at their disposal to sustainably understand and improve curb use for loading zones, parking and other uses. When properly integrated, cities can deploy computer vision, demand and progressive pricing, or algorithms to optimize loading zones to help them improve the efficiency of available curb lane space, as well as the processes used to manage them.
Ultimately, when loading zones are properly managed, drivers find parking quicker, there’s less congestion, a lower likelihood of injury or harm to pedestrians and bicyclists, along with fewer altercations. And data suggests motorists are drawn to areas where they’re likely to find a parking space. City leaders should examine demand pricing for load zones and available curb space. As deployed in L.A., and in Washington D.C., curbside management that leverages advanced analytics to evaluate city parking systems and make pricing recommendations can help cities achieve their coveted congestion mitigation, public safety, accessibility and efficiency goals.
About the AuthorMore Content by Lauren Weintraut