If integrated into adaptive cruise-control systems, a
new algorithm could mitigate the type of freeway backup that seems to
occur for no reason.
At this month’s IEEE Conference on Intelligent Transport Systems, Berthold Horn, a professor in MIT’s Department of Electrical Engineering and Computer Science, presented a new algorithm for alleviating traffic flow instabilities, which he believes could be implemented by a variation of the adaptive cruise-control systems that are an option on many of today’s high-end cars. Details of the paper are as follows Paper MoB1.3:
| Suppressing Traffic Flow Instabilities | |
| Horn, Berthold K.P. | MIT |
|
Keywords: Driver Assistance Systems, Road Traffic Control, Multi-autonomous Vehicle Studies, Models, Techniques and Simulations
Abstract: While many models
of traffic flow predict the instabilities commonly
observed--—particularly at higher traffic densities—--there are few
suggestions for suppressing them. A novel method is disclosed here for
suppressing the instabilities, thereby reducing gas consumption,
accidents, wear and tear on vehicles and roadways as well as travel
times while increasing traffic throughput.
The method uses information about the following vehicle as well as the leading vehicle. Using information from both sources allows the gain of feedback to be reduced below one, thus eliminating the instability characteristic of "car following." The needed inputs to the control system can be provided by machine vision (or radar or lidar. Previous proposals for smoothing traffic flow instabilities do not use information about the vehicles behind—--"car following" cruise control methods focus only on the vehicles ahead. The method is based on information flow both downstream and upstream, in distinction to traditional approaches where information flows only upstream. | |
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