VISSIM and real-world eco-approach and departure comparison

In addition to providing safety and mobility benefits, Connected and
Automated Vehicles (CAVs) have the potential to reduce fuel consumption
and emissions. As new CAV applications are developed, it is valuable to
estimate these potential environmental benefits, typically using vehicle
activity data and emissions models. To date, most researchers in the U.S.
have used the MOVES vehicle emissions model, developed and maintained by
the U.S. Environmental Protection Agency (EPA). However, because MOVES
uses a binning approach, it is likely underestimating the true energy and
emissions savings that occur when CAV applications smooth traffic flow. To
illustrate this problem, we measure and model the fuel consumption and CO2
emissions for a real-world CAV application: Eco-Approach and Departure
(EAD) at signalized intersections. First, a traffic simulation of the
real-world corridor the experiments will be performed on was created.
Next, the hardware needed to perform the real-world experiments was
installed on the real-world corridor. Then, using the traffic simulation
previously mentioned was used to mimic real-world testing of EAD in
different traffic conditions. Finally, real-world EAD tests were performed
on the real-world corridor where fuel consumption and carbon dioxide
emissions was recorded. Real-world measurements are compared to a
MOVES-based estimate, as well as to an estimate provided by the
physical-based Comprehensive Modal Emissions Model (CMEM). Results show
that MOVES consistently underestimates the energy and emissions benefits
of the CAV application, primarily since the bin sizes in MOVES are too
large to catch the nuances of traffic smoothing. On the other hand, CMEM
provided a more accurate energy and emissions estimate, primarily since it
uses analytical functions to model emissions and does not suffer from the
same binning problem.