Mobile source emissions inventory data from heavy-duty on-road vehicles are traditionally obtained using three methods: engine dynamometer, chassis dynamometer, or in-use vehicle driving. Engine dynamometer testing provides for the greatest control and highest accuracy but requires the most time and can be cost prohibitive when obtaining emissions from many in-use engines. In-use emissions collection is a relatively inexpensive and rapid method of obtaining real-world data, but this method is relatively new and is not regulated by any Federal or international regulations as of yet and accuracy of the data from these devices has not been established. Chassis dynamometer-based testing provides for the means of obtaining a large sample of data from in-use vehicles in a controlled environment. However, existing chassis dynamometer cycles assume a level road surface with no grade. In a chassis dynamometer test cycle, a simple line trace is used to represent the desired vehicle speed on a video monitor for the driver to follow. A second line trace is overlaid on the first to indicate the actual vehicle speed on the dynamometer and the drive adjusts the vehicle speed to match the scheduled speed as closely as he is able. Experienced chassis dynamometer test drivers are able to look at the desired speed and anticipate the required gearshifts during the testing. However, to account for road grade in a chassis dynamometer test schedule, the driver of the vehicle will require additional cues. Also, drivers may not drive a vehicle while following a trace in the same way that they drive on the road. To implement grade and inject a sense of the real world in a chassis dynamometer test cycle, a virtual reality interface has been developed to employ images of a roadway with feedback between the driver’s performance and the image. As a first step to implementing grade, a level road surface using a virtual reality interface was emulated using an in-house developed software package to present images of roadways, including traffic control signals and constraints due to traffic congestion. In the virtual reality execution, the driver perceives the position of the vehicle relative to traffic signals and other traffic cues. An initial investigation into the effect of road grade using the conventional line trace method is shown and then use of the virtual reality approach is compared with the conventional line trace. The results from the study shows that an experienced driver can use the virtual reality interface with similar emission results as the conventional line trace method.

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