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Ridesharing systems could cut greenhouse gases, study says

The report, which is especially relevant for transportation and environmental planners, was developed bythe Mineta Transportation Institute.

October 22, 2015
Ridesharing systems could cut greenhouse gases, study says

Lyft

2 min to read


Lyft

Can greenhouse gases be reduced by promoting ride sharing services and battery-electric vehicles? Could they sufficiently reduce vehicle miles traveled (VMT) to make a significant environmental impact? That’s what researchers at the Mineta Transportation Institute (MTI) wanted to know.

Their peer-reviewed report, Synergistic Integration of Transportation Demand Management Strategies (Land Use, Transit, and Auto Pricing) with New Technologies and Services (Battery Electric Vehicles and Dynamic Ridesharing) to Enhance Reductions in VMT and GHG, provides insight about the many possibilities.

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The report, which is especially relevant for transportation and environmental planners, was developed by Principal investigator, Caroline Rodier, PhD, working with Farzad Alemi and Dylan Smith.

“Our findings suggest that dynamic ridesharing, such as Uber and Lyft, could significantly reduce VMT and related greenhouse gas emissions if travelers are
willing to pay with their time and money to use the dynamic ridesharing system,” Rodier said.

She noted that the combination of dynamic ridesharing, along with the transit-oriented
development (TOD) and VMT Fee scenarios, suggests some policy combinations that may be more effective than dynamic ridesharing alone but perhaps more politically palatable.

“For example,” said Rodier, “a moderately used regional dynamic ridesharing with 10 percent increase in VMT fees may produce reductions in VMT on the order of 11 percent compared with a business-as-usual scenario in one horizon year.”

Changes could be greatest in faster growing areas The authors used the San Francisco Bay Area Metropolitan Transportation Commission’s activity-based microsimulation travel demand model for 2010. A business-as-usual (Base Case),
transit-oriented development, and auto pricing (VMT Fee) scenarios are simulated with and without high, medium, and low dynamic ridesharing participation levels and
battery electric vehicles (BEV) driving ranges.

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Results of the BEV simulations suggest that TODs may increase the market for BEVs by less than 1% in the San Francisco Bay Area. In addition, auto pricing policies may increase the market by as much as 7%. However, it is possible that larger changes are feasible over time in faster growing regions where development is currently at low density levels (for example, the Central Valley in California). The VMT Fee scenarios show larger increases in the potential market for BEV by as much as 7%.



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