2B.1 New Test Results: Automated Vehicles during Adverse Weather

Monday, 13 January 2020: 10:30 AM
209 (Boston Convention and Exhibition Center)
Brenda Boyce, Booz Allen Hamilton, Alexander, AR; and D. Johnson and R. Alfelor

Weather (atmospheric conditions) and road weather (pavement conditions) can adversely affect vehicle and driver behavior. With the advent of automated vehicles (AVs), the Federal Highway Administration Road Weather Management Program has begun research and testing to identify how vehicles and drivers will detect and react to adverse weather and road weather conditions. AVs have sensors and perception systems to detect objects and events in their vicinity. Using this information, they control the steering or speed or both to move the vehicle along its selected path. Their ability to properly perceive the situation and execute a maneuver can be affected by atmospheric and road weather.

Perception of an environment for automated driving requires two main sets of information: the type of objects around the vehicle and the position and velocity of those objects. A wide variety of different means are available to achieve this objective, but most commonly control is achieved using a combination of cameras and radar sensors. Most vehicles on the market use cameras in conjunction with machine vision algorithms to identify objects and marking on the roadway. Some use multiple cameras to add depth perception, through stereo vision. Radar detects objects by measuring the return of electromagnetic radiation, which for automotive applications is generally 77 GHz. By recording both time of flight and frequency shift due to the Doppler Effect, distance to the object and relative velocity are measured. Each type of sensor is known to have different strengths and weakness in how it perceives the environment. The adverse weather testing was designed to help to exemplify these differences.

Three vehicle models in 2018 and two vehicle models commercially available in the United States were used for these tests. All three had machine vision (one or more video cameras), and two had a radar. The AVs selected for these tests strictly rely upon on-board technologies, video and radar. Future vehicles may be connected, using dedicated short-range communication (DSRC) or 5G cellular communication to communicate with other vehicles, pedestrians, and infrastructure. Connected Automated Vehicles (CAVs) have the ability to optimize network capacity, reduce congestion, increase safety, and have environmental benefits. Connected vehicle technology and the associated vehicle-to-vehicle apps was not part of these tests.

The tests conducted were developed with the intent to challenge perception systems across a variety of simulated adverse weather conditions in a controlled outdoor laboratory setting. Production vehicles with different perception systems were driven through a planned variety of road and road weather conditions to permit an assessment of how well the automation features of each AV performed. The results from these tests provide data to FHWA and to other stakeholders on how selected perception systems perform in a limited set of adverse weather conditions.

The presentation will describe the tests and results that were obtained during the testing in March 2018 and February 2019 along with some videos.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner