Developing an Expert System for Choosing the Pedestrian Crossing Type in mid-block Segments

Authors

1 M.Sc. Grad, Transportation, Imam Khomeini International University, Qazvin, Iran

2 Assistant Professor, Ph.D., Transportation, Imam Khomeini International University, Qazvin, Iran

Abstract

One of the most important aspects of human presence in urban spaces, which causes the vitality and dynamism of these spaces, as well as their social role, is the pedestrian movement. Pedestrians are vulnerable road users and damages to them are often irreparable and irreversible and cause injury or death. The purpose of this study was to determine the percentage of using pedestrian bridges in Tehran as well as environmental and human factors affecting the use or non-use of pedestrians crossing at the bridge's influence. Several environmental factors such as the median pedestrian barriers as well as human factors such as the age and the personal characteristics were considered in this study. In this research, decision was made in a fuzzy environment, which is a multi-value environment. The knowledge base used in an expert system is formed using fuzzy logic and could be used as a fuzzy decision support system for managing and planning for the construction of new pedestrian bridges or for modifying existing bridges. The results of this research can be used to identify high-capacity bridges for equipping other bridges, locating for the construction of new bridges, assessing the status of each bridge and its use. The results show that the most effective factors for using the overpasses by pedestrians were the bridge facilities among the environmental factors and the perceived identity among the human factors. Having compared the results of this study using the fuzzy reasoning model with the real outputs show a 98 percent correlation and the 20 percent error in estimating the probability for using the pedestrian overpass to cross the street.
 

Keywords

References

-ایرانمنش، س.ح. و پاشاپور، ش. و آسترکی، م.، (1394)، "سیستم‌های خبره: رویکردی کاربردی"، ناشر شرکت هزاره سوم اندیشه.
-آذر، ع. و فرجی، ح. (1395)، "علم مدیریت فازی"
(چاپ پنجم)، مؤسسه کتاب مهربان نشر.
-بهنود، ح. و پیرایش نقاب، م. ح. و آیتی، ا.، (1392)،
"­ایجاد سیستم پشتیبانی از تصمیم فازی در مدیریت و برنامه ریزی اقدامات ایمن سازی راه"، مهندسی حمل­ونقل، سال پنجم، شماره دوم.
-جاسبی، ج. و مکوندی، پ. (1390)، "مدلسازی فرآیند پیش‌بینی سفر در برنامه‌ریزی حمل و نقل درون شهری مبتنی بر رویکرد ترکیبی استنتاج فازی"، فراسوی مدیریت، سال پنجم، شماره 17، تابستان 1390، ص. 7-32.
-عدل‌پرور، م. (1391)، "بکارگیری منطق فازی در مدل سازی انتخاب وسیله نقلیه سفرهای برون شهری"، مهندسی حمل و نقل، پاییز 1391، سال چهارم، شماره اول.
-کلاهدوز، ع. و ملاسلمانی، م. و کلی، ز. (1394)، "تحلیل و ارزیابی ایمنی عبور عابرین ‌پیاده از عرض خیابان در تقاطعهای چراغدار بر اساس ویژگیهای رفتاری عابرین"، پانزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک، 12-11اسفند، تهران، ایران.
-Balk, S.A. And Bertola, M.A. And Shurbutt, J. And Do, A. (2014), “Human Factors Assessment of Pedestrian Roadway Crossing Behavior”. Publication No. fhwa-hrt-13-098.
-Castro, J.L. and Delgado, M. and Medina, J. and Ruiz-Lozano, M.D.  (2011), “An expert fuzzy system for predicting object collisions”. Its application for avoiding pedestrian accidents. Expert Systems with Applications 38 (2011), pp.486–494.
-Durkin, J. (1994), Expert Systems: Design and Development, New York.
-Evans, D. and Norman, P. (1998), ‘Understanding pedestrians' road crossing decisions: an application of the theory of planned behaviour’, Health Education Research, vol.13 no.4, pp.481-489.
García, F. and García, J. and Ponz, A. and DE LA Eacalera, A. and Armingol, J.M. (2014), “Context aided pedestrian detection for danger estimation based on laser scanner and computer vision”. Expert Systems with Applications 41 (2014), pp.6646–6661.
-Holland, C.A. and Hill, R. and Cooke, R. (2009) ‘Understanding the role of self-identity in habitual risky behaviours: pedestrian road crossing decisions across the lifespan’, Health Education Research, 24(4), pp.674-685.
-Hong, T.P. and Lee, CH. Y.(1996) ‘Induction of fuzzy rules and membership functions from training examples’, Fuzzy Sets and Systems 84, pp.33-47.
-Obaidat, M.T. and Al-Masaeid, H. and Al-Haji, J. and Qudah, A.  (2007), “A Knowledge-based System for Pedestrian’s Roadway Crossing Behavior through Video Cameras”. Jordan Journal of Civil Engineering, Volume 1, No. 2.
-Wang, L. X. (1999), “A course in fuzzy systems: Prentice-Hall press”, USA.
Journal of Transportation Research
Volume 15, Issue 4
December 2019
Pages 195-206

Files

Share

How to cite

Statistics