A Cost Function-Oriented Quantitative Evaluation Method for Unmanned Ground Vehicles

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Abstract:

Task driven approach is widely used as an evaluation method for intelligent vehicle, however this approach may lead to many teams using the conservative approach to complete the task. Although the competition task can be completed, it has deviated from the goal of technological development actually. A cost function-oriented quantitative evaluation method is proposed in this study. The time to complete each task and the quality of each indicator are considered in the evaluation method. The cost function-oriented quantitative evaluation method guides the intelligent vehicle’s development in the "low-cost index" (i.e. high technology) direction. The evaluation results in the 2010 Future Challenge: Intelligent Vehicles and Beyond (FC’ 2010) competition showed that the proposed method can quantitatively evaluate the overall technical performance and individual technical performance of unmanned vehicles.

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Periodical:

Advanced Materials Research (Volumes 301-303)

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701-706

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July 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Information on: http: /www. darpa. mil/grandchallenge04.

Google Scholar

[2] Information on: http: /www. darpa. mil/grandchallenge05.

Google Scholar

[3] Information on: http: /www. darpa. mil/grandchallenge/index. asp.

Google Scholar

[4] Information on: http: /www. sapro. com. au/smartdemo/smartdemo2005. htm.

Google Scholar

[5] Information on: http: /www. elrob. org/melrob/melrob2006/about-m-elrob-2006. html.

Google Scholar

[6] Information on: http: /www. elrob. org/celrob/celrob2007/about-c-elrob-2007. html.

Google Scholar

[7] Information on: http: /www. elrob. org/melrob/melrob2008. html.

Google Scholar

[8] Information on: http: /www. elrob. org/celrob/celrob2009. html.

Google Scholar

[9] Information on: http: /www. elrob. org/melrob/melrob2010. html.

Google Scholar

[10] Information on. Available : http: /www. elrob. org/celrob/celrob2011. html.

Google Scholar

[11] Prof. Ing. Gino Ferretti. (2010, July 20). [Online]. Available: http: /viac. vislab. it.

Google Scholar

[12] Information on: http: /ccvai. xjtu. edu. cn/news. do?method=getdetails&id=33.

Google Scholar

[13] Junqing Wei, Dolan, J.M. A robust autonomous freeway driving algorithm" 2009 IEEE Intelligent Vehicles Symposium , Page(s): 1015 – 1020, Xi, an, Shaanxi, China , June 3-5, (2009).

DOI: 10.1109/ivs.2009.5164420

Google Scholar

[14] Junqing Wei, John M. Dolan and Bakhtiar Litkouhi. A Prediction- and Cost function-Based Algorithm for Robust Autonomous Freeway Driving, 2010 IEEE Intelligent Vehicles Symposium, University of California, San.

DOI: 10.1109/ivs.2010.5547988

Google Scholar

[15] Guangming Xiong, Xijun Zhao, Haiou Liu, et al. Research on the Quantitative Evaluation System for Unmanned Ground Vehicles, 2010 IEEE Intelligent Vehicles Symposium, Page(s): 523-527, University of California, San Diego, CA, USA June 21-24, (2010).

DOI: 10.1109/ivs.2010.5548144

Google Scholar

[16] T.I. Saaty, The Analytic Hierarchy Process. McGraw Hill Inc. (1980).

Google Scholar

[17] Information on: http: /ccvai. xjtu. edu. cn/news. do?method=getdetails&id=40.

Google Scholar

[18] Eric Krotkov, Scott Fish, Larry Jackel Bill McBride, Mike Perschbacher, Jim Pippine. The DARPA PerceptOR evaluation experiments, Auton Robot (2007) 22: 19–35.

DOI: 10.1007/s10514-006-9000-0

Google Scholar