0
Research Papers

Compensating for Operational Uncertainty in Man–Machine Systems: A Case Study on Intelligent Vehicle Parking Assist System

[+] Author and Article Information
Dale Su

Department of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan

Kuei-Yuan Chan

Department of Mechanical Engineering, National Taiwan University, Taipei 10617, Taiwan e-mail: chanky@ntu.edu.tw

1Corresponding author.

Manuscript received June 12, 2014; final manuscript received January 28, 2015; published online July 1, 2015. Assoc. Editor: Alba Sofi.

ASME J. Risk Uncertainty Part B 1(3), 031008 (Jul 01, 2015) (13 pages) Paper No: RISK-14-1027; doi: 10.1115/1.4030438 History: Received June 12, 2014; Accepted April 27, 2015; Online July 01, 2015

The successful operation of man–machine systems requires consistent human operation and reliable machine performance. Machine reliability has received numerous improvements, whereas human-related operational uncertainty is an area of increasing research interest. Most studies and formal documentation only provide suggestions for alleviating human uncertainty instead of providing specific methods to ensure operation accuracy in real-time. This paper presents a general framework for a reliable system that compensates for human-operating uncertainty during operation. This system learns the response of the user, constructs the user’s behavior pattern, and then creates compensated instructions to ensure the completion of the desired tasks, thus improving the reliability of the man–machine system. The proposed framework is applied to the development of an intelligent vehicle parking assist system. Existing parking assist systems do not account for driver error, nor do they consider realistic urban parking spaces with obstacles. The proposed system computes a theoretical path once a parking space is identified. Audio commands are then sent to the driver with real-time compensation to minimize deviations from the path. When an operation is too far away from the desired path to be compensated, a new set of instructions is computed based on the collected uncertainty. Tests with various real-world urban parking scenarios indicated that there is a possibility to park a vehicle with a space that is as small as 1.07 times the vehicle length with up to 30% uncertainty. Results also show that the compensation scheme allows diverse operators to reliably achieve a desired goal.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.

References

Pentland, A., and Liu, A., 1999, “Modeling and Prediction of Human Behavior,” Neural Comput., 11(1), pp. 229–242. 10.1162/089976699300016890 [PubMed]
Sekizawa, S., Inagaki, S., Suzuki, T., Hayakawa, S., Tsuchida, N., Tsuda, T., and Fujinami, H., 2007, “Modeling and Recognition of Driving Behavior Based on Stochastic Switched ARX Model,” IEEE Trans. Intell. Transp. Syst., 8(4), pp. 593–606. 10.1109/TITS.2007.903441
Kumagai, T., Sakaguchi, Y., Okuwa, M., and Akamatsu, M., 2003, “Prediction of Driving Behavior Through Probabilistic Inference,” Proceedings of the 8th International Conference on Engineering Applications of Neural Networks, International Neural Network Society, Warsaw, Poland, pp. 8–10.
Mitrovic, D., 2005, “Reliable Method for Driving Events Recognition,” IEEE Trans. Intell. Transp. Syst., 6(2), pp. 198–205. 10.1109/TITS.2005.848367
Cheng, J.-H., and Chang, Y.-H., 1999, “Application of a Fuzzy Knowledge Base on Bus Operations Under Uncertainty,” 1999 IEEE International Fuzzy Systems Conference Proceedings, FUZZ-IEEE’99, Vol. 3, pp. 1355–1360, IEEE, Seoul, Korea.
Stanton, N., and Stevenage, S., 1998, “Learning to Predict Human Error: Issues of Acceptability, Reliability and Validity,” Ergonomics, 41(11), pp. 1737–1756. 10.1080/001401398186162 [PubMed]
Nigam, S., and Turner, J., 1995, “Review of Statistical Approaches to Tolerance Analysis,” Comput. Aided Des., 27(1), pp. 6–15. 10.1016/0010-4485(95)90748-5
Hung, T.-C., and Chan, K.-Y., 2013, “Multi-Objective Design and Tolerance Allocation for Single- and Multi-Level Systems,” J. Intell. Manuf., 24(3), pp. 559–573. 10.1007/s10845-011-0608-3
Reason, J., 1988, “Modelling the Basic Error Tendencies of Human Operators,” Reliab. Eng. Syst. Saf., 22(1), pp. 137–153. 10.1016/0951-8320(88)90071-3
Lipow, M., 1980, “Prediction of Software Failures,” J. Syst. Software, 1, pp. 71–75. 10.1016/0164-1212(79)90006-2
Chen, L.-H., 2012, “Wind Farm Optimization With Turbine Blade Design Considering Geographical Constraints,” Master’s thesis, National Cheng Kung University.
Pintelon, R., Guillaume, P., and Schoukens, J., 2007, “Uncertainty Calculation in (Operational) Modal Analysis,” Mech. Syst. Signal Process., 21(6), pp. 2359–2373. 10.1016/j.ymssp.2006.11.007
Ribas, G., Leiras, A., and Hamacher, S., 2012, “Operational Planning of Oil Refineries Under Uncertainty,” IMA J. Manage. Math. Spec. Issue Appl. Stochastic Optim., 23(4), pp. 397–412. 10.1093/imaman/dps005
Johnson, C., 1999, “Why Human Error Modeling has Failed to Help Systems Development,” Interact. Comput., 11(5), pp. 517–524. 10.1016/S0953-5438(98)00041-1
Zimmermann, H.-J., 2000, “An Application-Oriented View of Modeling Uncertainty,” Eur. J. Oper. Res., 122(2), pp. 190–198. 10.1016/S0377-2217(99)00228-3
McInvale, H. D., 2009, “Optimal Control Policies for Stochastic Networks With Multiple Decision Makers,” Ph.D. thesis, Vanderbilt University.
Wall, T. D., Cordery, J. L., and Clegg, C. W., 2002, “Empowerment, Performance, and Operational Uncertainty: A Theoretical Integration,” Appl. Psychol., 51(1), pp. 146–169. 10.1111/apps.2002.51.issue-1
Bea, R., 2006, “Reliability and Human Factors in Geotechnical Engineering,” J. Geotech. Geoenviron. Eng., 132(5), pp. 631–643. 10.1061/(ASCE)1090-0241(2006)132:5(631)
Möller, N., and Hansson, S., 2008, “Principles of Engineering Safety: Risk and Uncertainty Reduction,” Reliab. Eng. Syst. Saf., 93(6), pp. 798–805. 10.1016/j.ress.2007.03.031
Rouse, W., and Rouse, S., 1983, “Analysis and Classification of Human Error,” IEEE Trans. Syst. Man Cybern., SMC-13(4), pp. 539–549. 10.1109/TSMC.1983.6313142
Nechyba, M., and Xu, Y., 1997, “Human Control Strategy: Abstraction, Verification, and Replication,” IEEE Trans. Control Syst., 17(5), pp. 48–61. 10.1109/37.621469
Kim, J., Kim, Y., and Hwang, D., 2005, “Modeling of Human Driving Behavior Based on Piecewise Linear Model,” Proceedings of the IEEE Symposium on Industrial Electronics, ISIE-IEEE, Croatia. 10.1109/ISIE.2005.1528883
Maxion, R., and Reeder, R., 2005, “Improving User-Interface Dependability Through Mitigation of Human Error,” Int. J. Hum. Comput. Stud., 63(1), pp. 25–50. 10.1016/j.ijhcs.2005.04.009
Gong, R., and Kieras, D., 1994, “A Validation of the GOMS Model Methodology in the Development of a Specialized, Commercial Software Application,” Proceedings of the ACM Conference on Human Factors in Computing Systems, Boston.
Gunia, D., Kalabis, M., Meise, J., M¨uller, K. C., Rolfes, N., Toledo, S., Wey, T., 2012, “Vehicle Park Assist System and Method for Parking a Vehicle Using Such System,” , 169, 341, May 1, 2012.
Ford Active Park Assist Diagram, FORD Motor Company, accessed Apr. 17, 2014.
Parking Guidance System and the Method, Automotive Research and Testing Center, accessed Apr. 17, 2014.
Automatic Parking Guidance System (APGS), Automotive Research and Testing Center, accessed Jan. 21, 2014.
Su, D., 2014, “Compensating for Operational Uncertainty in Man-Machine Systems: A Case Study on Intelligent Vehicle Parking Assist System,” Master’s thesis, National Cheng Kung University.
Wang, Y., and Cartmell, M. P., 1998, “Autonomous Vehicle Parallel Parking Design Using Function Fitting Approaches,” Robotica, 16(2), pp. 159–170. 10.1017/S0263574798000496
Choi, S., Boussard, C., and D’Andrea-Novel, B., 2011, “Easy Path Planning and Robust Control for Automatic Parallel Parking,” Proceedings of the 18th IFAC World Congress, Vol. 18, International Federation of Automatic Control, Italy, pp. 656–661.

Figures

Grahic Jump Location
Fig. 1

Standard processes in man–machine systems

Grahic Jump Location
Fig. 2

Concept of Type I human uncertainty

Grahic Jump Location
Fig. 3

Concept of Type II human uncertainty

Grahic Jump Location
Fig. 4

Concept of Type III human uncertainty

Grahic Jump Location
Fig. 5

Concept of Type IV human uncertainty: (a) Comparison of different machine and (b) comparison of different instructions

Grahic Jump Location
Fig. 6

Method of compensation for human uncertainty

Grahic Jump Location
Fig. 7

Ford parking assist system: (a) Ford parallel parking assist system patent flowchart [25] and (b) Ford parallel parking assist system diagram [26]

Grahic Jump Location
Fig. 8

ARTC parking assist system: (a) ARTC parallel parking assist system patent flowchart [27] and (b) ARTC parallel parking assist system diagram [28]

Grahic Jump Location
Fig. 9

Flowchart of the intelligent parking assist system

Grahic Jump Location
Fig. 10

Parking path generation from [30]: (a) Path comparison and (b) steering comparison

Grahic Jump Location
Fig. 11

Circle path [31]: (a) Circle path simulation via Matlab and (b) summary of geometric calculations for several commercial vehicles

Grahic Jump Location
Fig. 12

Vehicle and path models in VI sequence generation

Grahic Jump Location
Fig. 13

Simulation results: (a) Sequence of steering angle and (b) parking trajectory

Grahic Jump Location
Fig. 14

Different types of parking scenario: (a) Normal, (b) narrow alley, and (c) obstacles

Grahic Jump Location
Fig. 15

Normal parking scenario results with no driver error: (a) Parking trajectory and (b) VI sequence of steering angle

Grahic Jump Location
Fig. 16

Narrow alley parking scenario results with no driver error: (a) Parking trajectory and (b) VI sequence of steering angle

Grahic Jump Location
Fig. 17

Obstacles parking scenario results with no driver error: (a) Parking trajectory and (b) VI sequence of steering angle

Grahic Jump Location
Fig. 18

Comparison of results considering operation uncertainty

Grahic Jump Location
Fig. 19

Experimental configuration

Grahic Jump Location
Fig. 20

Comparisons of minimal parking space: (a) Comparison of experiment and simulation and (b) parking trajectory simulation

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Articles from Part A: Civil Engineering
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In