Knowledge Resources

This paper evaluated the potential impacts of an eco-driving system designed to help drivers smooth speed profiles and improve traffic flow by reducing unnecessary acceleration and braking events in heavy traffic. The system provided individual drivers with real-time dynamic speed recommendations based on current link travel time data and weather information collected at local transportation management centers (TMC). To evaluate system impacts a simulation study and real-world vehicle experiment were conducted.

Simulation Study

The PARAMICS microscopic traffic simulation tool was applied to the Comprehensive Modal Emissions Model (CMEM) to examine vehicle performance under a variety of traffic conditions. Using an eco-driving technology penetration rate of 20 percent, velocity trajectories of eco-driving and non-eco-driving vehicles were modeled on a straightforward section of freeway having varied levels of service (LOS). Vehicle population data from Southern California were used to calibrate the model.

The following energy/emission statistics were calculated for an example vehicle traveling "with" and "without" eco-driving assistance on a congested segment of freeway stabilized at an average speed of 40 km/h.

Velocity trajectory	Non-eco-driving	Eco-driving	Difference
Max (km/h)	80.5	48.9	- 31.7
Min (km/h)	10.3	22.7	12.4
Average (km/h)	43.3	40.2	- 3.05
Std. dev. (km/h)	12.7	3.2	- 9.5
Skewness (km/h)	0.64	- 2.9	- 3.5
CO2 (g)	1605.13	1044.81	- 34.90%
Fuel consumption (g)	531.23	333.29	- 37.30%
Travel time (min)	8.9	9.6	7.70%

Although eco-driving traffic speed stabilization can contribute to significant fuel savings and emissions reductions during congestion conditions, the author noted the system would have very little impact during free flow conditions.

Field Study

In addition to the simulation study, limited real-world experimentation was conducted. Real-time freeway traffic data (speed, density, flow) acquired from embedded loop detectors as part of the California Freeway Performance Measurement System (PeMS) were used to calculate average vehicle speeds on major freeways in the study area. Traffic speed data were then processed at a local TMC, and optimal speed values were calculated for individual links on the roadway network every 30 seconds. Using a wireless service provider, optimal speed values were transmitted to an in-vehicle display and drivers were able to limit vehicle speeds to those recommended by the system servers. As a "control" a second vehicle was operated in the same traffic except the recommended speed information was not provided. The velocity trajectories of test vehicles were compared to assess the impacts of eco-driving versus non-eco-driving. The data suggest that eco-driving can reduce energy and emissions with little increase in travel time.

Velocity trajectory	Non-eco-driving	Eco-driving	Difference
Max (km/h)	117.9	93.6	- 24.3
Min (km/h)	0	0	0
Average (km/h)	33.9	32.1	- 1.9
Std. dev. (km/h)	21.2	17.5	- 4.0
Skewness (km/h)	1.7	1.6	- 0.16
CO2 (g)	5439	4781	- 12%
Fuel (g)	1766	1534	- 13%
Travel time (min)	38.9	41.2	6%

FINDINGS

Overall, the study found that eco-driving with dynamic speed recommendations can reduce fuel consumption by 10 to 20 percent and lower carbon dioxide emissions without drastically increasing freeway travel times . The author noted that the benefits are dependent on level of service. Under free flow conditions benefits would be minimal, however, under severe congestion benefits would be considerable.