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First published online January 1, 2008

Effectiveness and Acceptance of Adaptive Intelligent Speed Adaptation Systems

Abstract

Intelligent speed adaptation (ISA) systems face significant consumer acceptance hurdles that limit the likelihood of widespread adoption, particularly in the United States. However, if these systems are designed as speed management systems rather than speed limiting systems, with adaptability to individual driving behavior, they may be more likely to meet with consumer acceptance. The results of a fixed-based driving simulator experiment that tested the acceptance and effectiveness of a new type of ISA, called an Advanced Vehicular Speed Adaptation System (AVSAS), are reported. The results of the experiment showed that AVSAS resulted in reductions in driver speeds across a range of roadway types. AVSAS is a speed management system that adapts to an individual driver's speed behavior and the current driving situation. AVSAS resulted in an average reduction of 5% of the maximum speeds and 3% of the average speeds of the drivers on four road segments. As expected, AVSAS did not reduce driver speeds as much as the mandatory control ISA system, and the experiment confirmed the results of tests conducted on ISA systems largely in Europe. Conversely, the results revealed that more participants were willing to purchase AVSAS compared with the information or mandatory ISAs. Although these results show the promise of a trade-off between system effectiveness and acceptability that has been missing in mandatory and information ISA research, AVSAS suggests that a range of ISA system design requirements could encourage the adoption of ISA systems in the United States.

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References

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Article first published online: January 1, 2008
Issue published: January 2008

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© 2008 National Academy of Sciences.
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Authors

Affiliations

Stephen Arhin
Center for Intelligent Systems Research, George Washington University, 20101 Academic Way, Ashburn, VA 20147.
Azim Eskandarian
Center for Intelligent Systems Research, George Washington University, 20101 Academic Way, Ashburn, VA 20147.
Jeremy Blum
Department of Computer Science, Pennsylvania State University at Harrisburg, 777 Harrisburg Pike, Middletown, PA 17057.
Pierre Delaigue
Center for Intelligent Systems Research, George Washington University, 20101 Academic Way, Ashburn, VA 20147.
Damoon Soudbakhsh
Center for Intelligent Systems Research, George Washington University, 20101 Academic Way, Ashburn, VA 20147.

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