Scipediacontent: Scipediacontent moved page Draft Content 448617666 to Desaraju et al 2011a

2021-01-28T18:56:24Z

Scipediacontent moved page Draft Content 448617666 to Desaraju et al 2011a

Scipediacontent: Created page with " == Abstract == The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. Improving safety at intersections has also been ident..."

2021-01-28T18:56:20Z

Created page with " == Abstract == The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. Improving safety at intersections has also been ident..."

New page

== Abstract ==

The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. Improving safety at intersections has also been identified as high priority due to the large number of intersection related fatalities. This paper focuses on developing algorithms for estimating driver behavior at road intersections. It introduces two classes of algorithms that can classify drivers as compliant or violating. They are based on 1) Support Vector Machines (SVM) and 2) Hidden Markov Models (HMM), two very popular machine learning approaches that have been used extensively for classification in multiple disciplines. The algorithms are successfully validated using naturalistic intersection data collected in Christiansburg, VA, through the US Department of Transportation Cooperative Intersection Collision Avoidance System for Violations (CICAS-V) initiative.

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1109/ivs.2011.5940569 http://dx.doi.org/10.1109/ivs.2011.5940569] under the license https://creativecommons.org/licenses/by-nc-sa

* [https://dspace.mit.edu/bitstream/1721.1/65892/1/How_Behavior%20Classification_DF.pdf https://dspace.mit.edu/bitstream/1721.1/65892/1/How_Behavior%20Classification_DF.pdf]

* [http://xplorestaging.ieee.org/ielx5/5930385/5940387/05940569.pdf?arnumber=5940569 http://xplorestaging.ieee.org/ielx5/5930385/5940387/05940569.pdf?arnumber=5940569],
: [http://dx.doi.org/10.1109/ivs.2011.5940569 http://dx.doi.org/10.1109/ivs.2011.5940569] under the license cc-by-nc-sa

* [https://dblp.uni-trier.de/db/conf/ivs/ivs2011.html#AoudeDSH11 https://dblp.uni-trier.de/db/conf/ivs/ivs2011.html#AoudeDSH11],
: [http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005940569 http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005940569],
: [http://dx.doi.org/10.1109/IVS.2011.5940569 http://dx.doi.org/10.1109/IVS.2011.5940569],
: [https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5940569 https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5940569],
: [https://academic.microsoft.com/#/detail/2131762276 https://academic.microsoft.com/#/detail/2131762276]

← Older revision	Revision as of 18:56, 28 January 2021
(No difference)

Desaraju et al 2011a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 448617666 to Desaraju et al 2011a

Scipediacontent: Created page with " == Abstract == The ability to classify driver behavior lays the foundation for more advanced driver assistance systems. Improving safety at intersections has also been ident..."