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PROBLEMS For the intersection ed at this 4-leg signalizedi intersection data provided below th at this 4-leg signalized iniet would he stimate Condition Major Street AADT Minor Street AADT Red-Light Cameras Number of Approaches with LT Lanes Number of Approaches with RT Lanes pect 253 Value 60,000 vebiday 25,000 In place on all approaches of Approaches with Exclusive LT Phasing RTOR Prohibited Number of Appronches with Intersection Lighting Total Pedestrian Crossing Volume Maximum Number of Lanes Crossed by a Pedestrian Number of Bus Stops within 1.000 ft of the Intersect None Provided 1,800 peds/day 6 lanes None mber of Schools within 1,000 ft of the Intersection Nu of Liquor Stores within 1,000 ft of the Intersection Num Local Calibration Factor 1.04 Follow the example below to solve this problem.
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4SG Intersection Table 12.12: Data for Illustrative HSM Analysis of a Value 34,000 veh/day 16,000 veh/day Condition Major Street AADT Minor Street AADT Red-Light Cameras Number of Approaches with LT Lanes Number of Approaches with RT Lanes Number of Approaches with Exclusive LT Phasing Number of Approaches with RTOR Prohibited Intersection Lighting Total Pedestrian Crossing Volume Maximum Number of Lanes Crossed by a Pedestrian Number of Bus Stops within 1,000 ft of the Intersection Number of Schools within 1,000 ft of the Intersection Number of Liquor Stores within 1,000 ft of the Intersection Local Calibration Factor None None None Provided 540 peds/day 6 lanes None None 0.94
Sample Problem 12-1: HSM Analysis of an Intersection c. Nbmv(PDO)= exp[-11.02+102 d. NbsvTOTAL = exp[-10.21 + 0.68 e. Nbsy(F)= exp[-9.25 + 0.43 A four-leg signalized intersection on an urban arterial is to be evaluated for safety. No reliable crash history data are available. The HSM is used to predict the expected crash fre- quency. Known data for the intersection are summarized n x In(34,000)+024 x In(16,000)1-70 Table 12.12. x In(34,000) +02 x1n( 16,000)] = 061 Step 1: Find SPFs for multivehicle and single-vehicle crashes and vehicle-pedestrian crashes (crashes/year). using Equation 12-3 and Table 12.4 for multivehicle crashes, Equation 12-6 and Table 12.5 for single- vehicle crashes, and Equation 12-7 and Table 12.6 for vehicle-pedestrian crashes: In( 34,000) 0.29 x In(16,000)] 0.14 Nbry(PDO) = exp[-11.34 + 0.79 f. X In (34,000)+0.2 x In (16,000)] 0.45 a. MbmvTOTAL = exp[-10.99 + 1.07 X In (34,000) + 0.23 × In (16,000)] = 11.03 g. Npedbaseexp-9.530.4 × ln(34,000 + 16,000) x In (16,000/34,000) 045 x1n (540) + 0.04 x 61- b. NumFnexp[-13.14 1.18 bmv(F) X In (34,000) +0.22 Y1n 16 000)1-3.68
y and sv SPF values so that the sum of FI Adjust ins matches the base total (crashes/year), mv and sv SPF val Npred m-11.03 x 0.81 x 0.88 x 1.00 x 1.00 x 0.911 x 1.00 7.162 crashes/yr predsv 0.61 x 0.81 x 0.88 x 1.00 x 1.00 x 0.911 x 1.00-0.396 crashes/yr u Equations 12-4 and 12-5: Nom(F)11.03 x 3.68 3.68 +7.00 -3.80 11.03-3.80-7.23 A perusal of Table 12.12 also shows that there is only one CMF that would apply to the current case: a school is located within 1,000 ft of the intersection. From Table 12.11, the CMFscH is 1.35. Again, all other CMFs that might apply to vehicle-pedestrian crashes are, by definition, 1.00. Using Equation 12-13: Nor(FT)-0.61 x 0.14 0.14+0.46 0.14 oo,-0.61-0.14 = 0.46 nd total predicted average crash frequency for Npdpred 0.10 x 1.00 x 1.35 x 1.00 - 0.135 crashes/yr Nom 3.80+ 7.23-11.03 Ny0.14 +0.46 0.61 NN.-11.03 +0.61 리 1.64 Nnt Step S: Find predicted average vehicle-bicycle crashes The number of vehicle-bicycle crashes is estimated us- ing Equation 12-8: these totals now agree with the predictions of total crashes in Step 1 Nbikei = (Myred.mv + Npred.r.) ×fheri Nitei (7.162 + 0.396) x 0.015 Find CMFs. A perusal of Table 12.12 indicates that there are three conditions that do not conform to the base conditions for multivehicle and single-vehicle crashes: (a) there are two approaches with an LT lane, (b) there are two approaches with an exclusive LT phase (fully protect- ed), and (c) the intersection is well-lighted. p4 0.113 crashes/yr where 0.015 is the prescribed adjustment factor for 4SG intersections From Table 12.9, the CMF for LT lanes is 0.81, Step 6: Predict total crashes/yr for the intersection while the CMF for exclusive LT phasing is 0.88. The CMF for a lighted intersection is defined by Equation 12-10: The total number of crashes for the subject intersection is given by Equation 12-2 CMF 1-0.38 Paigh CMF-1-(0.38 x 0.235) -0911 pred.inNot +Nooli + Naser Npred.int 094 (7.162 +0.396+0.135+0.113) 7.806 crashes/yr By definition, all other CMFs applied to multivehicle and single-vehicle crashes conform to base conditions, ie CMF 1.00 for these conditions. Then, applying Equa- tion 12-12: where 0.94 is the local calibration factor cited in Table 12.12, and Noi is the sum of the multivehicle and single-vehicle crashes predicted (7.162 and 0.396, respectively).
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