01698022

Component

Connected and autonomous vehicle (CAV) technology has become one of the focused research topics to reduce automobile energy consumption and emissions. Many CAV applications have been developed that use a computer rather than a human to determine the vehicle’s trajectory. This brings new challenges to evaluate their fuel economy as different CAV controllers will drive the vehicle differently and many traffic factors might affect the fuel economy such as penetration rates, congestion levels, etc. The current fuel economy testing procedure cannot be directly applied since it evaluates all vehicles with the same standard driving cycles and different traffic factors are not considered. This work studies the effects of different traffic factors on the fuel economy of a CAV and uses eco-corporative adaptive cruise control (Eco-CACC) as a representative CAV application. Two scenarios are investigated: a driving cycle based scenario with no lane changes and a complex traffic network scenario with lane changes. The results provide a systematic analysis of variations of CAV fuel benefits due to different penetration rates of communication, penetration rates of automation, and locations of the CVs and CAVs. It shows that in a platoon of mixed human-driven vehicles and Eco-CACC controlled CAVs, the target CAV can gain significant benefits as long as there is another preceding CAV in front. It also demonstrates that the human-driven vehicles can gain about 10% fuel benefit when following an Eco-CACC controlled CAV. In addition, the traffic flow of the platoon is smoothed and shockwaves are mitigated.

This paper was sponsored by TRB committee ADC70 Standing Committee on Transportation Energy.

19-05828

English

16p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References

Autonomous intelligent cruise control; Autonomous vehicles; Connected vehicles; Fuel consumption; Lane changing; Traffic flow; Traffic platooning; Vehicle mix

Driving cycles

Data and Information Technology; Energy; Highways; Operations and Traffic Management; Vehicles and Equipment

Transportation Research Board Annual Meeting 2019 Paper #19-05828

TRIS, TRB, ATRI

Dec 7 2018 9:44AM