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Iowa State University--Becoming the Best

Estimating Energy Efficiency of Connected and Autonomous Vehicles in a Mixed Fleet


Principal investigators:

Project status

In progress

Start date: 03/01/17
End date: 02/28/18



About the research


The long-term vision for this research is to optimize the operations of transportation networks that are partially made up of connected and autonomous vehicles (CAVs), to achieve energy efficiency while assuring safety and on-time arrival.

This project will estimate travel time and fuel economy of a traffic stream consisting of CAVs and manual vehicles. Microscopic traffic flow models will be used to simulate the vehicle dynamics, considering the interaction between CAVs and manual vehicles. Energy consumption will be estimated based on the simulated velocity and acceleration of each vehicle, considering conventional gasoline vehicles, hybrid vehicles, and plug-in electric vehicles. We will compare and select the appropriate fuel consumption models to estimate the energy consumption and emissions of conventional and alternative fuel vehicles. The energy consumption models will be incorporated trwith the microscopic traffic flow models.

The potential applications of the proposed research are to design variable speed limits and personal speed advisory information for the future fleet with a mix of manual vehicles and CAVs and to evaluate the time and energy efficiency of various control strategies and alternative fuel powertrain technologies.