Development of Accident Predictive Model for Rural Roadway
This paper present the study carried out of accident
analysis, black spot study and to develop accident predictive models
based on the data collected at rural roadway, Federal Route 50 (F050)
Malaysia. The road accident trends and black spot ranking were
established on the F050. The development of the accident prediction
model will concentrate in Parit Raja area from KM 19 to KM 23.
Multiple non-linear regression method was used to relate the discrete
accident data with the road and traffic flow explanatory variable. The
dependent variable was modeled as the number of crashes namely
accident point weighting, however accident point weighting have
rarely been account in the road accident prediction Models. The result
show that, the existing number of major access points, without traffic
light, rise in speed, increasing number of Annual Average Daily
Traffic (AADT), growing number of motorcycle and motorcar and
reducing the time gap are the potential contributors of increment
accident rates on multiple rural roadway.
[1] Hadi, M.A., Aruldhas, J., Chow, L.F., Wattleworth, J.A., Estimating
Safety Effects of Cross-Section Design for Various Highway Types Using
Negative Binomial Regression. Transportation Research Record, 1500,
TRB, National Research Council,1993.
[2] Miaou, S.-P. and Lum, H.. "Modeling Vehicle Accidents and Highway
Geometric Design Relationships." Accident Analysis and Prevention
25(6): 689-709(1993).
[3] Gwynn, D.W. ; Relationship between road accident and hourly volumes.
Traffic Quartely, pp.407-418, (1967).
[4] Berhanu, G.; Model relating traffic safety with road environment and
traffic flow on arterial roads in Addis Ababa. Adis Ababa University, pp
697-704(2004).
[5] Quimby, A., Maycock, G., Palmer, C., & Grayson, G.B. (1999 b). Drivers
speed choice: an indepth study. Transport Research Laboratory TRL,
Report 326, Crowthorne.
[6] Taylor, M.C., Lynam, D.A., and Baruya, A. (2000) The effects of drivers-
speed on the frequency of road accidents, Transport Research Laboratory
Report 421, Crowthorne, Bucks: Transport Research Laboratory
[7] W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA:
Wadsworth, 1993, pp. 123-135.
[8] Brilon, W., Koenig, R. and Troutbeck, R.J. :Useful estimation procedures
for critical gaps. Transportation Res.- A 33 pp 161-186(1999).
[9] Miller A.J., "Nine estimators of gap acceptance parameters". Proceedings
of the 5th International Symposium on the Theory of Traffic Flow, pp.
215-235 (1972).
[10] Hauer, E.: Identification of sites with promise, Transportation Research
Record, 30, 54-60 (1996).
[11] S.Harnen, R.S.Radin Umar, S.V.Wong, W.I.Wan Hashim;Motorcycle
Crash Prediction Model For Non-Signalized Intersections.IATSS
Research Vol.27 No.2,(2003).pp.508-65.
[1] Hadi, M.A., Aruldhas, J., Chow, L.F., Wattleworth, J.A., Estimating
Safety Effects of Cross-Section Design for Various Highway Types Using
Negative Binomial Regression. Transportation Research Record, 1500,
TRB, National Research Council,1993.
[2] Miaou, S.-P. and Lum, H.. "Modeling Vehicle Accidents and Highway
Geometric Design Relationships." Accident Analysis and Prevention
25(6): 689-709(1993).
[3] Gwynn, D.W. ; Relationship between road accident and hourly volumes.
Traffic Quartely, pp.407-418, (1967).
[4] Berhanu, G.; Model relating traffic safety with road environment and
traffic flow on arterial roads in Addis Ababa. Adis Ababa University, pp
697-704(2004).
[5] Quimby, A., Maycock, G., Palmer, C., & Grayson, G.B. (1999 b). Drivers
speed choice: an indepth study. Transport Research Laboratory TRL,
Report 326, Crowthorne.
[6] Taylor, M.C., Lynam, D.A., and Baruya, A. (2000) The effects of drivers-
speed on the frequency of road accidents, Transport Research Laboratory
Report 421, Crowthorne, Bucks: Transport Research Laboratory
[7] W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA:
Wadsworth, 1993, pp. 123-135.
[8] Brilon, W., Koenig, R. and Troutbeck, R.J. :Useful estimation procedures
for critical gaps. Transportation Res.- A 33 pp 161-186(1999).
[9] Miller A.J., "Nine estimators of gap acceptance parameters". Proceedings
of the 5th International Symposium on the Theory of Traffic Flow, pp.
215-235 (1972).
[10] Hauer, E.: Identification of sites with promise, Transportation Research
Record, 30, 54-60 (1996).
[11] S.Harnen, R.S.Radin Umar, S.V.Wong, W.I.Wan Hashim;Motorcycle
Crash Prediction Model For Non-Signalized Intersections.IATSS
Research Vol.27 No.2,(2003).pp.508-65.
@article{"International Journal of Architectural, Civil and Construction Sciences:60140", author = "Fajaruddin Mustakim and Motohiro Fujita", title = "Development of Accident Predictive Model for Rural Roadway", abstract = "This paper present the study carried out of accident
analysis, black spot study and to develop accident predictive models
based on the data collected at rural roadway, Federal Route 50 (F050)
Malaysia. The road accident trends and black spot ranking were
established on the F050. The development of the accident prediction
model will concentrate in Parit Raja area from KM 19 to KM 23.
Multiple non-linear regression method was used to relate the discrete
accident data with the road and traffic flow explanatory variable. The
dependent variable was modeled as the number of crashes namely
accident point weighting, however accident point weighting have
rarely been account in the road accident prediction Models. The result
show that, the existing number of major access points, without traffic
light, rise in speed, increasing number of Annual Average Daily
Traffic (AADT), growing number of motorcycle and motorcar and
reducing the time gap are the potential contributors of increment
accident rates on multiple rural roadway.", keywords = "Accident Trends, Black Spot Study, Accident
Prediction Model", volume = "5", number = "10", pages = "492-6", }