  This paper introduces a novel approach that seeks a middle ground for traffic
control in multi-lane congestion, where prevailing traffic speeds are too fast,
and speed recommendations designed to dampen traffic waves are too slow.
Advanced controllers that modify the speed of an automated car for
wave-dampening, eco-driving, or other goals, typically are designed with
forward collision safety in mind. Our approach goes further, by considering how
dangerous it can be for a controller to drive so slowly relative to prevailing
traffic that it creates a significant issue for safety and comfort. This paper
explores open-road scenarios where large gaps between prevailing speeds and
desired speeds can exist, specifically when infrastructure-based variable speed
limit systems are not strictly followed at all times by other drivers. Our
designed, implemented, and deployed algorithm is able to follow variable speed
limits when others also follow it, avoid collisions with vehicles ahead, and
adapt to prevailing traffic when other motorists are traveling well above the
posted speeds. The key is to reject unsafe speed recommendations from
infrastructure-based traffic smoothing systems, based on real-time local
traffic conditions observed by the vehicle under control. This solution is
implemented and deployed on two control vehicles in heavy multi-lane highway
congestion. The results include analysis from system design, and field tests
that validate the system's performance using an existing Variable Speed Limit
system as the external source for speed recommendations, and the on-board
sensors of a stock Toyota Rav4 for inputs that estimate the prevailing speed of
traffic around the vehicle under control.
