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NEWS
Researchers Seek To Lessen Environmental Impact With Green Fleet Technology
August 3, 2017

According to information from Pennsylvania State University (Penn State), new research is underway that addresses the impact delivery trucks have on the environment by providing green solutions that keep costs down without sacrificing efficiency.

Reducing the impact large-vehicle emissions have on the environment is a real challenge due to industry delivery demands, explained Vittal Prabhu, a professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering.


Professor Vittal Prabhu is coming up with innovative new ways to cut down the effect fleet vehicles have on the environment while keeping costs down and maintaining timely deliveries. Credit: Min Xian.

“The size of fleets has increased, the transportation networks have become more complex and, perhaps most importantly, there is an increased demand for timely deliveries in tighter time frames,” he said. “Therefore, it is increasingly important to come up with innovative new ways to cut down the effect these vehicles have on the environment while keeping costs down and maintaining timely deliveries.”

Prof. Prabhu is the co-author on two recently published papers, “Just-in-time delivery for green fleets: A feedback control approach” published in the journal Transportation Research Part D: Transport and Environment in 2016, and “Smart logistics: distributed control of green crowd-sourced parcel services,” published in the International Journal of Production Research, that address these complex issues and present some promising solutions for the delivery industry.

As reported in the Transportation Research journal paper, Prof. Prabhu and Seokgi Lee, a Penn State alumnus and now an assistant professor at the University of Miami, developed a new algorithm — called Greening via Energy and Emissions in Transportation (GEET) — to more effectively route fleet vehicles in order to reduce environmental effects.

“GEET determines the optimal departure time and vehicle cruising speeds that can be varied throughout the trip based on anticipated vehicle performance and delivery times,” said Prof. Prabhu. “This is the feedback part of the ‘feedback control approach’ to the problem.”

Through this new algorithm, the researchers saw, on average, a 12-16 percent reduction in fuel consumption and were able to implement this improvement within delivery systems in a short amount of time.

As reported in the International Journal of Production Research paper, Profs. Lee and Prabhu worked in collaboration with Yuncheol Kang, another Penn State alumnus and now an assistant professor at Hongik University in Seoul, Korea, on a study that focused on crowd-sourced parcel services. In crowd-sourced parcel services, an individual can download an app to find packages that need to be delivered within their own neighborhood. This form of delivery is often faster than a single delivery truck; and with the growing popularity of on-demand transportation companies, such as Uber and Lyft, the cost for these personal deliveries is dropping.

Individuals with the app see the payout for transporting a package and can decide to accept or decline the job. For this reason, this type of delivery system is difficult to model because of the many unknown factors. The supply and location of drivers, along with changes in demand for people to ship packages, is largely variable.

According to Prof. Prabhu, “This kind of system causes a lot of wasteful driving, which causes both economic and environmental burdens.”

The researchers’ algorithm attempts to pair drivers and packages to certain routes in order to reduce the overall effect of unnecessary mileage and carbon emissions.

When tested using computer simulations on a hypothetical crowd-sourced parcel company, this new method increased the company’s revenue by 6.4 percent by reducing fuel and emission costs by 2.5 percent.

“This is hopefully just the beginning,” said Prof. Prabhu. “We will continue to look at the issues within fleet operations and determine what other efficiencies can be applied in order to cut down on emissions while maintaining customer satisfaction.”


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