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There-fore, the use of the same speed limit (100 km/h) for both sitesmay not be completely correct.The correct way to solve this situation is the establishmentof speed zoning of reasonable and safe speed limits on road-ways based on an engineering study. A speed zone is a sectionof highway where a speed limits different from the statutoryspeed limit has been established [1].ConclusionsThe most important conclusions of the current paper are asfollows: first, the ANN models give so better and most confi-dence results than regression models in terms of predictingV85. The evident of this is as follows, the best ANN modelgives R2and RMSE equal to 0.978 and 3.11 for overall dataset compared with the best regression model gives R2andRMSE equal to 0.761, and 10.32 for all data set. The secondconclusion concludes that the most influential variable onV85 is PW, followed by MW and SA. The increase of PW from6.8 m to 7.1 leads to an increase of V85 by nearly 40 km/h. Alsothe increase in MW from 2.2 m to 2.8 m leads to an increase inV85 by 27 km/h, and the increase from 2.8 m to 7 m leads to anincrease in V85 by 21 km/h. In addition, the existing of SAleads to a considerable decrease of V85. Although the averageV85 at sites without SA is 95 km/h, the average V85 at sites withSA is 66 km/h. The last conclusion shows that as a result of thebest ANN model, the PSL has a very small effect on V85 andcan be neglected. This may be due to the bad behavior of drivers not to care with PSL signs generally in Egypt. Based onthe analysis of measured V85 at all sites, the results show con-siderable changes in 85th percentile speed among the studysites despite that they are in the same class (i.e. rural multi-lanetwo-way). The road characteristics of straight section used inthe present paper such as pavement width existing of sideaccess, and median width surly have significant impact ondrivers’ choice of speed at straight sections. The previous re-sults are so important for controlling V85 on multi-lane ruralhighways in Egypt. V85 can be controlled by targeting roadgeometric factors to improve the safety performance of thehighways. Finally, future research should be conducted to ex-tend all aspects of this research using comprehensive field datafrom various rural roads to increase number of sites to more than 100 sites in order to reach more accurate modeling andanalysis of V85. In addition, the use of curved and sloping sec-tions in order to explore the impact of them on operatingspeeds for rural multi-lane highways in Egypt.AcknowledgmentsThe author acknowledges Dr. Mohamed Semeida, Depart-ment of Civil Engineering, Faculty of Engineering, Port SaidUniversity for his assistance with the revision of languageand intellectual content in this paper. Also, the authoracknowledges Eng. Nasser Abdalla, Department of Civil Engi-neering, Faculty of Engineering, Al-Azhar University for hisassistance with the acquisition of spot speed data at sites underresearch. References[1] Hashim IH. Analysis of speed characteristics for rural two-laneroads: a field study from Minoufiya governorate, Egypt. ASEJ2011;2:43–52.[2] Homburger WS, Hall JW, Loutzenheiser RC, Reilly WR. Spotspeed studies.
In: Fundamentals of trafficengineering. Berkeley: Institute of Transportation Studies,University of California; 1996. p. 6.1–9.[3] Poe CM,Mason JM. Analyzing influence of geometric design onoperating speeds along low-speed urban streets: mixed modelapproach. Transport RES REC 2000;1737:18–25.[4] Fitzpatrick K, Carlson P, Brewer M, Wooldridge M. Designfactors that affect driver speed on suburban streets. TransportRES REC 2001;1优尔:18–25.[5] Lamm R, Chouriri EM, Mailaender T. Comparison ofoperating speeds on dry and wet pavements of two-lane ruralhighways. Transport RES REC 1990;1280:199–207.[6] Ali A, Flannery A, Venigalla M. Prediction models for freeflow speed on urban streets. Transport RES REC2007;1992:199–207.[7] Figueroa AM, Tarko AP. Speed factors on two-lane ruralhighways in free-flow conditions. Transport RES REC2005;1912:46–9.[8] Fitzpatrick K, Carlson P, Brewer M, Wooldridge M, Miaou S.Design speed, operating speed, and posted speed practices.Report submitted to Washington, DC. NCHRP 504; 2003.[9] Wang J, Dixon K, Li H, HunterMP. Operating speed model forlow-speed urban tangent sections based on in-vehicle globalpositioning systems. Transport RES REC 2006;1961:24–33.[10] Himes SC, Donnell ET. Speed prediction models for multi-lanehighways: a simultaneous equations approach. Transport ENG– J ASCE 2010;136(2):124–32.[11] Shankar V, Mannering F. Modeling the endogeneity of lane-mean speeds and lane-speed deviations: a structural equationsapproach. Transport RES A – POL 1998;32(5):24–33.[12] Porter RJ. Estimation of relationships between 85th percentilespeeds, speed deviations, roadway and roadside geometry, andtraffic control in freeway work zones. PhD dissertation.Pennsylvania State University; 2007.[13] Singh D, Zaman M, White L. Modeling of 85th percentile speedfor rural highways for enhanced traffic safety. Report submittedtoOklahomaDepartment of Transportation. FHWA2211; 2011.[14] Issa R, Zaman M, Najjar YM. Modeling the 85th percentilespeed on Oklahoma two-lane rural highways: a neural networkapproach. Report submitted to Oklahoma Department ofTransportation. Project no. 6007. ORA 125-5227; 1998.[15] McFadden J, Yang WT, Durrans SR. Application of artificialnetworks to predict speeds on two-lane rural highways.Transport RES REC 2001;1优尔:9–17.[16] Krammes RA, Brackett Q, Shafer MA, Ottesen JL, AndersonIB, Fink KL, et al. Horizontal alignment design consistency forrural two-lane highways. US Department of Transportation.FHWA-RD-94-034; 1995.[17] Abdalla NM. Relationship between traffic flow characteristicsand pavement conditions on roads in Egypt. M.Sc. thesis, Deptof Civil Eng, Faculty of Eng, Al-Azhar University; 2010.[18] Simpson AL, Rauhut JB, Jordahl PR, Owusu-Antwi E, DarterMI, Abroad R, et al. Sensitivity analyses for selected pavementdistresses. SHRP report no. SHRP-P-393; 1994.[19] Akgungor AP, Dogan E. An application of modified Smeed,adapted Andreassen and artificial neural network accidentmodels to three metropolitan cities of Turkey. SR&E2009;4(9):906–13.[20] Semeida AM. Analysis and evaluation of road safety in Egyptusing conventional and non-conventional modeling techniques.PhD thesis. Dept of Civil Eng, Faculty of Eng, Port SaidUniversity; 2011.[21] User’s Manual. ‘‘NeuroSolutions 7’’. NeuroDimension, Inc.Gainesville; 2010.[22] Voudris AV. Analysis and forecast of capsize bulk carriersmarket using artificial neural networks.M-D thesis, Departmentof Mechanical Engineering, Massachusetts Institute ofTechnology; June 2006.[23] Tarefder RA, White L, Zaman M. Neural network model forasphalt concrete permeability. Materials CIV ENG – J2005;17(1):19–27.[24] Semeida AM, El-Shabrawy M, Sabry M, Hashim IH, Sadek M.Investigation of factors contributing to accidents on rural roadsin Egypt using neural networks. PSERJ 2010;15(1):56–65.