Predicting the road ahead: Hua Cai uses prospective modeling to attain sustainable urban transit

Growing up in China, Hua Cai was intrigued by the algae blooms that formed in a nearby lake as a result of industrial pollution.

“That was how I first became interested in environmental problems and why I chose to study environmental engineering,” says Cai.

After receiving an M.S. in environmental engineering from the Pennsylvania State University, Cai became a laboratory manager and environmental engineer at CDM Smith.

Making your own menu

“As an environmental engineer, I realized that fixing a problem after it’s already happened is too late,” says Cai. “This is one of many factors that led me to pursue my Ph.D. in sustainable systems modeling.”

She explains, “When we create a new system, there are a lot of options during the adoption phase, and very little data about what works best. As we gradually adopt a system and build it into our infrastructure, eventually we are locked in. We have a lot of data, but very little flexibility in terms of what we can do to meet new challenges. My focus is that earlier phase. How can we build models to identify what's going to happen in different scenarios? Then we can inform the system development and make better decisions now that avoid negative or unintended consequences later.”

After completing her Ph.D. at the University of Michigan, (jointly conferred in Environmental Engineering, Natural Resources and Environment), Dr. Cai joined the Purdue College of Engineering in 2015.

“One thing I learned during my Ph.D. is that you don’t have to order from the menu. If you have a vision, there are resources that you can find to support the work that you really want to do.”

Dr. Cai has found a great deal of support for her vision at Purdue, where her research has focused on urban sustainability using prospective modeling. She is appointed jointly as an associate professor in Environmental and Ecological Engineering and Industrial Engineering, affiliated with the Purdue Climate Change Research Center (PCCRC) and Ecological Sciences & Engineering (ESE) interdisciplinary program, and she leads the Urban Sustainability Modeling and Analysis Research Team (uSMART).

“I’ve specifically been focusing on the transportation sector, because more than 90% of the energy the transportation sector uses is from petroleum and it contributes 25-30% of the total emissions,” says Cai.

Deciding for a world that doesn’t yet exist

Right now, over half of the global population lives in urban areas; by 2050, this figure is expected to rise to 68%. This burgeoning population is a vital consideration for urban transportation systems, since investments and decision-making are not based on current transportation use, but predicted use 20-30 years into the future.

“We need to ensure that we are on a sustainable path now, developing new technologies and systems to meet those future needs,” says Cai.  

There are currently three major trends changing urban transportation systems: shared mobility (scooters, bikes, cars); electric vehicles; and autonomous driving.

“When we look at the environmental impacts of a system, we have to use a lifecycle perspective,” Cai explains. “Without tailpipe emissions, an electric vehicle is not emissions free because it takes energy and materials to make them and create the batteries. The sources of the electricity also plays a critical role, and we also need to build proper charging infrastructure to support charging electric vehicles using cleaner electricity.”

"These emerging trends also aren’t happening in isolation,” adds Cai. “They are happening at the same time, and may prevent or stimulate one another. They are also becoming part of an existing transportation infrastructure. Are they complementing or competing with existing transit? Modeling allows us to explore a number of different developmental pathways to help understand the larger environmental impact.”

Complementing or competing?

Professor Cai is currently conducting research in partnership with the Indiana Department of Transportation (INDOT). To make informed infrastructure investments and policy decisions, INDOT must anticipate potential future changes in the way Hoosiers live and work and how businesses transport goods.

In a recently completed project with INDOT, Dr. Cai and Dr. Konstantina Gkritza developed a simulation model to analyze the impacts of two transformative technologies---shared micro-mobility (bike-sharing, shared e-scooters) and ride-hailing systems (such as Uber and Lyft)—on vehicle ownership and VMT (vehicle miles traveled).

Their findings included:

  • These transformative technologies have not significantly affected car usage in Indiana cities, but they have decreased transit use. In other words, shared micro-mobility is replacing public transit rather than complementing it.
  • While some citizens may shift to transformative technology for recreational trips, they are a more challenging choice for long commuting trips.
  • While shared micro-mobility may slightly reduce VMT (vehicle miles traveled) by 2%, ride-hailing could increase VMT by 30%. This is because drivers of ride-hailing vehicles often travel numerous miles without passengers in order to reach a client or balance supply and demand between particular areas.

Ultimately, cities must promote better integration between transformative transportation systems and existing infrastructure to improve urban mobility and sustainability. 

“Our future transportation systems depend on how we utilize these opportunities now,” says Cai.

The road ahead

The above study also provided insights on how the pandemic influenced transit habits. Working remotely, shopping online, and increased deliveries caused shifts in travel demand and behavior. When these shifts are added to the adoption of new transportation technologies, it’s clear that there are numerous potential scenarios for how Indiana’s freight and micro-mobility movements may change in the coming decades.

In order to address this uncertainty, Cai and Gkritza are participating in another INDOT project aimed at developing medium- and long-term future forecasts of transportation demand, mode choice, and travel behavior shifts for people and freight, including micro-freight (such as delivering a single meal or grocery order).

In addition to research, Dr. Cai currently teaches graduate courses in emerging transportation systems modeling, including “Urban Mobility Optimization” and “Transportation, Energy, and Sustainability.”

“The great thing about having capable students is that they challenge you every day.” Hua Cai smiles.

“I often ask myself what I’ve done to deserve so many colleagues, students, and funding agencies supporting my work.”



Writer: Jessica Mehr
Source: Hua Cai
Date: May 2022