The battle for curb space

Many know the frustration of exiting the airport after a long flight, ordering an Uber or Lyft, and waiting too long for a vehicle that is just a short distance away. This type of congestion is often not caused by typical traffic hold-ups, but rather rideshares and private drivers competing over limited curb space to pull over and pick up passengers.

Due to the expansion of new mobility technologies like ridesharing, grocery delivery, shared bike or scooter stations, and micro mobility systems, this problem is increasingly prevalent in cities across the country. On-street parking, curb-side passenger pickup and drop-off, and loading for commercial trucks transform a normal city curb into valuable public infrastructure over which cars, trucks, delivery vehicles, facilities, and pedestrians compete.

In a paper published in Transportation Science, researchers from the Department of Civil and Environmental Engineering at Carnegie Mellon University developed a model to simulate how curbs are being used in real time within a large transportation network.

“Curb space could be a limited public resource in urban areas,” said Sean Qian, professor of civil and environmental engineering and director of the Mobility Data Analytics Center. “Using it commercially by companies like Uber, Doordash, and Amazon delivery has substantial negative social externalities that have been historically overlooked.”

Using curbs commercially has substantial negative social externalities that have been historically overlooked.

Sean Qian, Professor, Civil and Environmental Engineering

The framework takes into account not just where and when different vehicles and services are using curb space, but also how these different uses interact with each other. For example, how does an Uber picking up passengers affect a delivery truck searching for a spot to unload? And, zooming out, how do these activities influence roadway congestion and the choices others make on a different road across town?

Using real-world data, the team was able to identify patterns in usage and behavior to develop a ‘status-quo’ model and predict how travelers would react to changes in curb configuration, pricing, or space availability. This capability is especially useful to city planners looking to assess and implement new policies, like regulating and pricing spaces to ridesharing services or strategies to reduce vehicle emissions.

“We have a large team that includes technology startups, traffic engineers, and urban planners from cities across the country,” said Jiachao Liu, a Ph.D. candidate in civil and environmental engineering. “Based on our framework, we can inform them of the potential impacts of certain policies and how different users might react.”

Eventually, the research team hopes to improve how they calculate travel times to more accurately predict how curb usage could affect traffic delays, and consequently recommend optimal pricing strategies and space limitations to commercial curb use. Qian also hopes to incorporate data from additional travel modes in future studies, including public transportation, electric vehicles, and shared mobility services to paint a more comprehensive picture of the mobility network. 

“With better technologies and curbside management strategies, there could be a win-win for cities and service operators,” said Qian. “I believe that traffic and curb usage can be efficient, reduce emissions, and improve service quality with the right approach.”