01661744

Component

Connected and automated vehicles (CAV) may deliver energy efficiency and air quality benefits by reducing traffic congestion and facilitating smoother driving behavior. This paper proposes a three-layered modeling framework for assessing the energy and emission impacts of first-generation CAV technologies, such as cooperative adaptive cruise control (CACC). The framework tightly integrates 1) a CAV driving behavior model with 2) a microscopic traffic simulation model to create vehicle trajectory data and then evaluates those trajectories in 3) a fleet-based modal emissions model. In a case study to test this framework, the authors utilized the microscopic model for simulation of intelligent cruise control (MIXIC) to represent vehicles driving with CACC systems in PTV Vissim, traffic microsimulation software, on Interstate 91 (I-91) northbound near Springfield, Massachusetts with real-world traffic speed and volume data. High-resolution (10 hertz), simulated passenger car trajectories were processed into operating modes according to vehicle-specific power, speed, and acceleration and then run through the Motor Vehicle Emission Simulator (MOVES) to quantify the hourly emissions and energy consumption on the I-91network. The authors compared the results of baseline driving using the default Wiedemann 99 car following model in Vissim against a scenario where all vehicles are CACC-enabled and another scenario where the Wiedemann oscillation parameters were set to zero. Their findings suggest that CACC driving will produce notable reductions in fine particulate matter (PM₂.₅) and carbon monoxide (CO) over the baseline but will not have an effect on fuel economy. The Wiedemann scenario without oscillations showed little to no benefit.

This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality.

18-06134

English

18p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Autonomous intelligent cruise control; Car following; Carbon monoxide; Case studies; Connected vehicles; Environmental impact analysis; Exhaust gases; Fuel conservation; Fuel consumption; Intelligent vehicles; Microsimulation; Particulates

Interstate 91 (Massachusetts); Motor Vehicle Emission Simulator (MOVES); VISSIM (Computer model); Wiedemann Car Following Model

Springfield (Massachusetts)

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

Transportation Research Board Annual Meeting 2018 Paper #18-06134

TRIS, TRB, ATRI

Jan 8 2018 11:35AM