Microsimulation Analysis of Traffic Operations at Two...

Research ArticleMicrosimulation Analysis of Traffic Operations atTwo Diamond Interchange Types

Rui Yue 1 Guangchuan Yang 2 Zong Tian1 Hao Xu1 Dongmei Lin 3 and Aobo Wang1

1Department of Civil and Environmental Engineering University of Nevada Reno NV 89557 USA2Department of Civil and Architectural Engineering University of Wyoming Laramie WY 82071 USA3DKS Associates Portland OR 97205 USA

Correspondence should be addressed to Rui Yue ryuenevadaunredu

Received 12 November 2018 Accepted 14 February 2019 Published 3 March 2019

Academic Editor Eleonora Papadimitriou

Copyright copy 2019 Rui Yue et al This is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The operational performance of standard Single PointUrban Interchange (SPUI) andTightDiamond Interchange (TDI) has alreadybeen widely studied In general SPUI is more efficient than a TDI in terms of increased capacity and decreased traffic delays eventhough building a SPUI generally incurs a higher cost However due to right-of-way constraints a standard SPUI may not beimplementable at locations with restricted land use thus the variations of SPUI are usually considered Currently there is noestablished methodology or guideline available on the performance evaluation of variations of SPUI This paper aims to investigatethe operational efficiency of SPUI with frontage roads (SPUI-F a variation of SPUI) Based on a field case the performance ofSPUI-F was investigated using microsimulation An analytical model for capacity estimation which considered early return anddischarge flow rate was also established and validated based on microsimulation Multiple traffic scenarios were analyzed andtheir performance measures were compared against the equivalent TDI design Simulation results revealed that TDI outperformedSPUI-F in terms of average delay speed and queue length and the proposed analytical model can be used for reliable capacity anddelay estimationThe findings from this study can aid the decision-makers choosing an appropriate interchange type for achievingthe best benefit-cost ratio

1 Introduction

Signalized interchanges have been deemed as an efficient andfeasible way to connect a freeway to the surface arterials Cur-rently the Single Point Urban Interchange (SPUI) and TightDiamond Interchange (TDI) make up a high proportion ofall interchange types in the US due to their stable operationalperformance particularly under heavy traffic volume condi-tions [1] In real-world condition to accommodate locationswith limited land use space some variations of diamondinterchanges have to be proposed to fit more right of ways[2] However geometry variation also leads to the changeof conflict movements and thus changes the operationalstrategy which may consequently influence the operationalefficiency Among the variations a frequently used variationhas been the Single Point Urban Interchange with FrontageRoad (SPUI-F) Nevertheless the operational efficiency ofSPUI-F has not been comprehensively investigated This is

supposed as necessary since a minor change in geometrymight cause a significant decrease or increase in its efficiencyMeanwhile in practice choosing an appropriate interchangetype for a site is critical for improving the efficiency of thetransportation system

Assessing the operational efficiency of different trans-portation facilities purely based on microscopic simulationmay not be convincible Deploying field case studies canbenefit the calibration and validation of microsimulationmodels and thus provide more realistic results In RenoNevada a field case of Single Point Urban Interchange withFrontage Road (SPUI-F) existed which can be used fortesting the field performanceWith thismotivation this studyfocuses on the operational efficiency evaluation of SPUI-Fand TDI for providing comprehensive recommendations onthe selection of interchange types VISSIM was employed asthe microsimulation software to conduct the evaluation anal-ysis Signal timing data of this interchange was retrieved from

HindawiJournal of Advanced TransportationVolume 2019 Article ID 6863480 11 pageshttpsdoiorg10115520196863480

2 Journal of Advanced Transportation

the Cityrsquos Advanced Traffic Management System (ATMS)Seven different turning volume scenarios combined with asensitivity analysiswere applied whichwas supposed to coverthe most realistic traffic conditions At the same time ananalytical model is introduced for estimating capacity withemphasis on the impact of early returns and discharge flowrate based on which the interchange capacity can be moreaccurately evaluated The delay of interchanges can also berealistically adjusted as a result of modification on capacityfunction

The rest of the paper is organized as follows first acomprehensive literature review on the previous studiesthen description of the case study site and the calibrating theexisting models on capacity and delay after that evaluationmethodology and VISSIM model calibration finally resultsanalysis and conclusions of this study

2 Literature Review

An increasing volume of literature is available on the oper-ational features applications and safety concerns of bothinterchanges Meanwhile calibration and validation of mi-crosimulation road network are also constantly growing

21 Operational Features and Applications of SPUI and TDIThe ITE Freeway and Interchange Geometric Design Hand-book first officially documented the interchange types ofSPUI and TDI [3] In recent decades ascribed to the increas-ing urban traffics both interchanges have been constantlystudied in order to seek the one that has more operationalefficiency In reality the two interchanges appeared to havedifferent advantages SPUI was found to have less right of wayconstraints in contrast to TDI according to conflict pointstheory [4] Moreover its special geometry also enables thedual left-turn operation and thus improves the operationalefficiency in heavy left-turn scenarios Apart from the fewerconflict points its wide radius [5 6] can also help to reinforcethe operational efficiency by awarding a higher turning speedto vehicles on which the capacity would be enlarged Besidesthose advantages its disadvantage is also noticeable SPUIdesign usually cannot accommodate site with limited spacesince it requires a longer bridge span [7] for the dedicatedleft-turn lanes implementation Another obvious deficient isits large open area which has different entry points which canbe unsafe due to the fact that vehiclesmaymisunderstand andviolate lane remarks

The application of the SPUI is currently prevalent but notlimited to theUS It also aroused attention fromvariousAsiancountries In Hong Kong the Kwai Tsing interchange usedthe design of SPUI [8] In Indonesia National Route 1 has theSPUI design implemented on its mainline [8] In Singaporethe SPUI was implemented in Eunos Flyover [8] Apart fromAsia SPUI was also widely accepted in Australia [8]

22 Operational Features and Applications of TDI The mostsignificant advantage of TDI is its appearance since it issimilar to two standard intersections it can greatly reducethe confusions among drivers Moreover it does not requireadditional land resources and a longer bridge span [5] to

fulfill the implementation which may better accommodateurban conditions However the design of TDI may notaccustom to heavy left-turn conditions according to the pre-vious research The reason may due to its capacity limitationbetween its two intersections

The application of TDI greatly benefits from its multiplecontrol types Three-phase [9ndash11] and four-phase control arerecommended with different conditions As the increasedpercentage of TDI interchanges is deployed in urban areasfour-phase controls are frequently employed because it couldenable vehicle make no stops in the middle which catereddriverrsquos expectationThemost popularmethod to achieve thisis to use TTI four-phase operation [12ndash15] It overlaps theramp phase and through phase via two dummy phases andthe operational efficiency was thus enhanced

23 Studies on Safety The safety issues were also necessary tobe considered In the view of safety FHWA reportmentionedthat the SPUI might be advantageous to TDI due to itsfewer conflict points In other words the SPUI is expectedto cause less safety problem regarding this view HoweverSmithrsquos study [16] did not find significant safety performancedifference between two interchanges This conclusion alsoreceived the support from field investigation [17] Anothersafety researchwas conducted byMesser et al [18] they foundthat in most cases the red clearance time was insufficient butno evidence proved that this limitation causes severe safetyissues in the real world Therefore by now no solid evidenceindicated that one interchange type is over another regardingthe view of safety

24 Studies on Microscopic Simulation Recent years guide-lines published on the microscopic simulation were continu-ously updated those methodologies benefited researchers ingenerating reasonable microscopic simulation models Parket al [19] came up with a microscopic simulation modelcalibration and validation procedure and then tested it onan arterial Dowling and his fellows [20] were devoted toa systematic level calibration and emphasized the practicaloperational studies Park et al [21] later provided a moreformal procedure for calibration of microscopic level modelsand in this research VISSIM was applied Menneni et al [22]proposed another research on microsimulation calibrationbut in the view using the speed-flow relationship Its test bedwas US-101 and results approved the approach with betterperformance than capacity view methods Three years laterLownes et al [23] were dedicated to calibrated driver behaviorparameters which aims to provide a better estimation ofdriversrsquo influence to capacity

25 Existing Research Shortcoming The research abovealready stated the pros and cons of the two interchanges inmultiple aspects However very fewmentioned the change inoperational efficiency when SPUI is implemented with twofrontage roads Leisch [24] mentioned that with the frontageroad the SPUI delay would approximately have an increaseof 30 However this conclusion has not been updatedfor several decades It may differ from todayrsquos results dueto the fact that traffic volumes and driving patterns have

Journal of Advanced Transportation 3

been changed significantly over the years Also there is nocurrent practice of capacity or delay estimation to addressthe interchange discharge patterns and early return ratesTherefore this research is devoted to filling the gap by apply-ing a wide-volume range comparison analysis to comprehen-sively study the operational difference between SPUI-F andTDI

3 Case Study

As previously mentioned field data are critical to the modelcalibration processThe calibration process was mainly basedon the comparison of field observed queue lengths and sim-ulated queue lengths Based on this real-world SPUI-F casethis research collected sample traffic flow and performancedata to more accurately develop and calibrate the VISSIMmodels For this evaluation the case study can be even morecritical since the current SPUI-F was converted from a TDIwhich can serve as a good contrast case as its geometry can beeasily accessed by Google Earthrsquos achieved data This researchwas conducted based on a real-world variation diamondinterchange case in Reno Nevada (ie the I-580Plumb Lninterchange) which can be used for contrasting the opera-tional performance for SPUI-F and TDI Prior to 2004 theinterchange was a TDI Due to the annual growth of trafficthe local transportation engineers found that the TDI designcannot accommodate the traffic demands Meanwhile themajority of research at that time continuously declared thatSPUI outperformed TDI in terms of operational efficiencyTherefore the TDI design was eventually changed to a SPUIdesignHowever due to the constraints of the crossroad to thenorth of Plumb Ln the through lanes were preserved at theon- and off-ramps Consequently the interchangewas revisedto a SPUI with frontage road (SPUI-F) to accommodate theconnection between the crossroad and freeway

Nevertheless in reality it was found that there are anumber of issues with the SPUI-F operation Since theinterchange connects the Reno-Tahoe airport and midtownarea of Reno thus traffic volumes are usually heavy at thesite In addition this interchange is located in the vicinity ofthe shopping area indicating that the interchange serves notonly the commuting and tourists traffic but also the shoppingtraffic The geometric layout of this SPUI-F interchange isdistinct from a typical SPUI as illustrated in Figure 1(a)In addition Figure 1(b) outlines the scope of the originalTDI which was extracted from the historical document fromGoogle Maps

To generate reasonable and convincible results thisresearch used the current I-580 SPUI-F interchange geometryas the basis of evaluation network with the same scale as fielduse For TDI road network it was constructed depending onthe same lane configurations of SPUI-F without changing theexterior geometry

4 Modeling Capacity and Delay

The existing capacity estimation model for signalized inter-changes did not fully involve the effects of the discharge flowrate and effective green time This may not bring significant

affection to at-grade intersections (no view blockage) butwillsignificantly impact interchanges For example since driversrsquoview of sight tends to be blocked by the bridge drivers maynot confidently accelerate when the green light is on In termsof effective green time for this interchange traffic flow fromthe off-ramps might significantly vary from the crossroadsthus the off-ramp may trigger gap out option resulting insignal early return to coordinate phases This phenomenonwould increase the capacity of specificmovementsThereforethe calibrated models mainly focused on taking account ofthese two aspects into the estimation of interchange capacityAccording to HCM 2010 [25] the capacity of a signalizedinterchange is summarized as follows

119888 = 119873 sdot 119878 sdot119892119862 (1)

where119873 = number of lanesS = saturation flow rateg = effective green timeC = cycle lengthThe formula above represents a generalized capacity

estimation towards signalized intersections and interchangesHowever to the best of the authorrsquos knowledge very fewguidelines were published on the selection of the satura-tion flow rate considering the variations of interchangesTherefore to avoid underestimating or overestimating thecapacity of an interchange reasonable saturation flow rateswere needed to apply to the capacity estimation In mostcircumstances (especiallywhen the initial queue appears) thesaturation flow rate can generally be replaced by saturationdischarge flow rate In this regard the above capacity estima-tion function can be revised as

119888 = 119873 sdot 119878119889 sdot119892119862 (2)

where119878119889 = saturation discharge flow rateAs mentioned before the actual average green time

also influences capacity In most of the current interchangecontrols actuated coordinated strategy is often used Thismeans that the effective green time may not be fixedInstead the noncoordinated phases can gap out thus thecoordinated phases can utilize the time from the gap-outphases Consequently the capacity varies differently fromfixed time control In order to address this phenomenon (2)is written as

119888 = 119873119894 sdot 119878119889119894 sdot1198921015840119894119862

(3)

where119873119894 = the lane number under phase i control119878119889119894 = the saturation discharge flow rate of phase i1198921015840119894 = the actual average green time of phase iTo estimate the average green time the average gap out

and early return indexes need to be taken into accountAverage gap out index reduces the designed splits while theearly return index promotes the designed splits Note that


1

7744

8833

2

2 1 4 387

Frontage road Frontage road

On ramp On ramp

(a) Existing SPUI-F configuration

2222

6666

8+16

4+12


On ramp

55+6

11+2

2 4 12 18716 5

(b) Previous TDI configuration

Figure 1 Geometric configuration of I-580Plumb Ln Interchange


coordinated phases can only have a promotion with the greentime The noncoordinated phases should be considered withboth gap out and early return With this consideration thefollowing formula is then derived

119899

sum119894119895=0

119888119894119895 =119899

sum119894=0

119873119894 sdot 119878119889119894 sdot119892119888119894 sdot 119890119894119862+119899

sum119895=0

119873119895 sdot 119878119889119895 sdot119892119899119895 sdot 119890119895 sdot 119900119895119862 (4)

wheresum119899119894119895=0 119888119894119895 = the estimated capacity of the whole intersec-

tion119873119894 = the lane number of the ith coordinated phase119892119888119894 = the designed green time of the ith coordinated phase119890119894 = the average early return receive index of ith coordi-

nated phase119873119895 = the lane number of the jth noncoordinated phase119878119889119895 = the saturation discharge flow rate of the jth

noncoordinated phase119892119899119895 = the designed green time of the jth noncoordinated

phase119890119895 = the average early return receive index of the jth

noncoordinated phase119900119895 = the average gap out index of the jth noncoordinated

phaseThe saturation discharge flow rates for off-ramp left turn

movement (phase 1 or 2 in Figure 1(a)) and crossroad leftturnmovement (phase 3 or 7 in Figure 1(a)) were investigateddue to the difference in the vehicle turning radius and viewblock conditions of two investigated interchange types Forthrough movements the saturation discharge flow rate ofboth interchanges should be the same as a standard inter-section According to the field study the traffic flow ratesfor crossroad left-turn movement on SPUI and TDI werefound as 1526 vehh and 1241 vehh Rates for SPUI-F werecollected on site while TDI data was collected at a similar site(with similar turning radius and blockage condition) For off-ramp left turn movements the traffic flow rate for both theinterchanges configurations was 1350 vehh For early returnrate and gap out indexes these two parameters varied caseby case Therefore these parameters were calculated basedon the historical data obtained from the cityrsquos AdvancedTransportation Management System (ATMS)

The calibrated capacity can also be used for delay estima-tion using the updated volume-to-capacity ratio referring toHCM [25] Regarding this case with TTI four-phase strategythe cycle length of TDI could be significantly reduced in con-trast to SPUI-F with split phase which indicates it may have alarger effective green time to cycle length ratio in contrast toSPUI-F However for SPUI-F the saturation discharge flowrate of crossroad left turn movement was higher than TDINevertheless it seems that the credit of saturation dischargeflow rate cannot counteract the advantages of TDI Withthis consideration TDI might be more efficient than SPUI-F To further validate this conclusion the next section of thispaper will employ the microsimulation modeling approachto further investigate the operational efficiency of the twointerchange configurations

5 Microsimulation Modeling

This study employed VISSIM microsimulation for testingthe performance of the two interchange alternatives undervarious traffic demand cases The experiment design consid-ered different traffic flow scenario traffic demand levels andsignal timing plans The operational efficiency was assessedby different Measures of Effectiveness (MOEs) includingaverage delay average speed and average queue length

51 Volume Scenario Design Seven volume scenarios weredesigned to address different volume patterns The base sce-nario was directly derived from the field collected PM peakhour traffic flow The remaining six scenarios have thedifferent emphasis left turn (one direction) dual left turn(both directions left turn) through dual through ramp anddual rampThe details are summarized as follows

(i) Base Scenario derived from existing PM peak hourtraffic volume

(ii) Scenario 1 (one approach heavy left turn scenario)designed for evaluation of heavy left turn conditionsFor this scenario the eastbound left turn movementwas increased

(iii) Scenario 2 (two approaches heavy left turn scenario)based on the previous scenario the left turn volumeof westbound was also changed which aimed to testboth directions

(iv) Scenario 3 (one approach heavy through scenario)designed for evaluating one heavy through move-ment

(v) Scenario 4 (two approaches heavy through scenario)the aim of the scenario was similar to the previousone expect both opposite approaches were tested

(vi) Scenario 5 (one approach heavy ramp scenario)focused on how the ramp volume variations influencethe evaluation results

(vii) Scenario 6 (two approaches heavy ramps scenario)tested both sides of the ramp volume variations on theevaluation results

52 Volume Sensitivity Design Thesensitivity test is a dimen-sion extension of volume scenario design in this study Eachaforementioned scenario was divided into five cases Caseswere generated based on volume factors (a percentage tothe original volume) which varied from 70 to 130 withan increment of 15 Since these cases were tested for bothinterchange configurations a total number of seventy caseswere simulated for yielding convincible results

Table 1 uses the base scenario (for both SPUI-F and TDI)as an example to indicate how the sensitivity analysis wasapplied Volume percentage ranged from 70 to 130 ofthe default volume applied and tested on the basis of eachdesigned scenario Therefore in total 35 cases were appliedfor each interchange


Table 1 Base scenario group

SBT SBL SBR EBT EBL EBR NBT NBL NBR WBT WBL WBR ToTAL

BASE SCENARIO

70 Volume 77 28 420 175 560 490 21 336 140 210 196 42 269585 Volume 94 34 510 213 680 595 25 408 170 255 238 51 3273Default Case 110 40 600 250 800 700 30 480 200 300 280 60 3850115 Volume 127 46 690 288 920 805 35 552 230 345 322 69 4429130 Volume 143 52 780 325 1040 910 39 624 260 390 364 78 5005

SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e

Simulation VolumeFigure 2 Volume contrast (field vs simulation)

53 Signal Operation Setting Feasible timing plans and rea-sonable engineering adjustments were also adopted alongsidethose cases to VISSIM

Basic timing information phase splits and sequenceswere adjusted for each case This study did not considerpedestrian constraints for the sake of fully testing the oper-ational efficiency Parameters like vehicle extension time(passage time) minimum green yellow and red clearancewere determined separately for two interchanges withoutfurther changes when applied to different cases

In this research TDI and SPUI-F were also applied todifferent operational strategies Three phase operations couldnot be applied to SPUI-F due to the existence of the twofrontage roads Thus four-phase control was needed to splitthe ramp operations For TDI since in this case there wasnot enough queue storage in the middle for vehicles the TTIfour-phase [12ndash15] was therefore applied to this interchangeto ensure a nonstop traffic between the two adjacent intersec-tions

6 Model Calibration and Validation

Model calibration and validation were conducted on thebasis of the PM peak hour volume In this research thecalibration involved three adjustments network scale adjust-ment signal control strategy adjustment and driver behavioradjustment [26] Network scale adjustment was conductedbased on the real scale of the interchange Lane widthsegment length pocket length and signal head locationswere accuratelymodified based on the field conditions Signal

timing parameters were input which conformed the ATMS[27] information Truck volumes were also investigated inthe calibration process Based on the observation and videorecording this paper deployed the default truck percentagesetting in VISSIM (2) For model calibration of truckbehavior this paper employed the speed and acceleration datarecommended by Yang et al [28 29] For passenger vehicledriver behaviors apart from vehicle length and standstilldistance the vehicle speed was majorly concerned in thisstudy To input a reasonable speed the authors drove a probevehicle in the flow during the experiment multiple times toobtain the actual travel speed

The GEH volume validation [30] was used for the modelvalidation VISSIM produced reasonable results accordingto Figure 2 The total volume of each movement generallyyielded a goodmatch between the simulation and field obser-vation with an average GEH of 033 (good to be accepteddue to it being less than 5) The simulation time was set toan hour and divided into 12 intervals (5 min intervals) Themaximum queues at the four critical movements were alsocollected for validation as illustrated in Figure 3 The MeanAbsolute Percentage Error (MAPE) [31] was employed toidentify the difference between field observed queue lengthsand simulated queue lengths as demonstrated in Figure 3

119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)

where119872119898 =model calculated MOEs119872119891 = field (simulation) collected MOEs


0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

Observed Maximum QueueSimulation Maximum Queue

0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals




Figure 3 Calibration of VISSIM model (EBL WBL SBL and NBL accordingly)

Results showed that the simulated queue lengths alignwith field observed queues with the MAPE value of 014(since queue in number of vehicles is small one vehicledifference can result in a large MAPE increase therefore 014here could be accepted) which suggested the network modelcould represent the actual situation and perform the analysis

7 Results

Simulation results are illustrated in Figures 4ndash7 Figure 4summarizes the average delays for all cases Average delaykept significantly increasing as the volume level increased forboth interchanges Nevertheless delay of SPUI-F seemed tohave a dramatic growth trend especially in the cases of +15and +30 scenarios In contrast a stable increase trend wasfound regarding the delay of TDI Moreover the delay ofSPUI-F at -30 volume level was even larger than TDI delay

at +30 volume level which implies that TDI is superiorto SPUI-F Therefore TDI outperformed SPUI-F in viewof average delay which also supported the previous studiesconcerning the operational difference between SPUI-F andTDI

Figure 5 illustrates the average speed performance forall cases With the previous results from average delay itwas not surprising that the average speed of TDI generallyperformed better than SPUI-F For reliability the range ofSPUI-F was almost twice larger than TDI in any scenariowhich proved that TDI was more reliable Therefore theresults fromaverage speed reinforced the results fromaveragedelay and consistently demonstrated that the performance ofTDI was obviously better than SPUI-F

Figure 6 demonstrates the average queue lengths for allcases A consistent trend was found for the average delay andspeed results The general trend indicated that SPUI-F was


0

20

40

60

80

100

120

140

Base Scenario scenario 1 scenario 2 scenario 3 scenario 4 scenario 5 scenario 6

Aver

age D

elay

(s)

Scenarios

Average Delay of All Cases

-30 Volume SPUI-F -15 Volume SPUI-F +0 Volume SPUI-F +15 Volume SPUI-F +30 Volume SPUI-F

-30 Volume TDI -15 Volume TDI +0 Volume TDI +15 Volume TDI +30 Volume TDI

Figure 4 Comparison of average delay under various volume scenarios

0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios

Average Speed of All Cases



Figure 5 Comparison of average speed under various volume scenarios


0

50

100

150

200

250

300

350

400

Base Scenario scenario 1

Aver

age Q

ueue

Len

gth

(ft)

scenario 2 scenario 3 scenario 4 scenario 5 scenario 6Scenarios

Average Queue Length of All Cases



Figure 6 Comparison of average queue length under various volume scenarios

y = 09641x + 09196

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100Delay Estimated by VISSIM (s)

Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839

Figure 7 Comparison ofVISSIM results andmodel results on delay

eager to block more vehicles once the volume increased Forlow traffic volume conditions the difference in average queuelength for SPUI-F and TDI was not obvious However thesituation started to turn down at moderate volume levels andheavy volume levels Hence TDI still performed better thanSPUI-F in terms of average queue length

From the comparisions of average delay average speedand average queue length under various volume scenarios asillustrated in Figures 4 to 6 it could be concluded that SPUI-F is not recommended for field implementation The reasonbehind the performance drop may be due to the limitationof capacity Recalling the operation strategies TDI used theTTI-four-phase multiple overlaps were used with this special

technique which enhanced the efficiency On the other handSPUI-F also used four-phase operation however the strategyfor SPUI-F had to be used Owing to the fact that split controlwas the only choice for SPUI-F the operational efficiencydramatically dropped Therefore it was not surprising thatTDI is more advanced than SPUI-F in all of the designedconditions

8 Modeling Results against Simulation

Since it is difficult to collect field data for comparison totest the effectiveness of the proposed model delays estimatedby the proposed model were compared against VISSIMsimulation outputs MAPE was employed to identify thedifference between model estimated delay and simulateddelay

Delays for both interchange types were calculated for allthe tested cases It was found that theMAPE results for SPUI-F were 5 and TDI was 31 which validated the accuracyof the model Figure 7 shows the comparison between thesimulation and calculation The residue square was 098which further illustrated that the calibrated model could beused for delay estimation

9 Conclusion

This research systematically compared the operational per-formance between SPUI-F and TDI and developed analyticalmodels for capacity and delay estimation for the two diamond


interchange types The capacity and delay estimation modelswere validated using a calibrated VISSIM microsimulationmodel which was initially validated by field traffic data

The results revealed that SPUI with frontage road isless efficient than TDI in operational performance whichis consistent with Leischrsquos findings [24] Also this researchfound that TDI wasmore reliable when handling heavy trafficvolume scenarios Conversely the sensitivity test exposedthe shortcomings of SPUI-F that the delay and other MOEsincreased considerably faster than TDI The average queuelength performance was quite noticeable since the unex-pected steep increase of trends in SPUI-F may result insevere congestion problem In reality the spillback mightoccur under heavy volume conditions In this study TDIoverperformed SPUI-F all the MOEs provided consistentresults throughout the simulation experiments ThereforeSPUI-F is not recommended for interchanges with heavytraffic volumeThedelay of SPUI-F calculated from themodelgenerallymatched the simulation results which isworth to beused for delay estimation in real-world cases

The paper still has some limitations regarding the caseconstraints this research only adopted the case in RenoNevada Cases in multiple cities can be discovered and con-trasted in future research In addition the calibrated modeldid not consider factors such as lane change and pedestrianbut it still provided consistent results with the previousresearch withmore cases being analyzed Future works can bedevoted to evaluate operational efficiency ofmore geometriesvariations between SPUI and TDI and utilize the Hardware-in-the-Loop Simulation to generatemore accurate simulationresults

Data Availability

The ATMS data supporting this model calibration analysisare from Regional Transportation Commission-Washoe andCity of Reno under license and so cannot be made freelyavailable The simulation data are available from the corre-sponding author upon request

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

The authors would like to thank the Regional TransportationCommissionWashoe (RTC-Washoe) for the funding supportand ATMS access to this research

References

[1] E G Jones and M J Selinger ldquoComparison of operations ofsingle-point and tight urban diamond interchangesrdquo Trans-portation Research Record vol 1847 no 1 pp 29ndash35 2003

[2] G Yang Z Tian Z Wang H Xu and R Yue ldquoImpact of on-ramp traffic flow arrival profile on queue length at metered on-rampsrdquo Journal of Transportation Engineering Part A Systemsvol 145 no 2 2019

[3] J P Leisch Freeway and Interchange Geometric Design Hand-book 2005

[4] B Fowler ldquoAn operational comparison of the single-point urbanand tight-diamond interchangesrdquo ITE Journal vol 64 no 4 pp19ndash26 1993

[5] N J Garber and M J Smith ldquoComparison of the Operationaland Safety Characteristics of the Single Point Urban andDiamond Interchangesrdquo Tech Rep FHWAVA-97-R6 1996

[6] D J P Hook and J O N A T H A N Upchurch ldquoComparisonof operational parameters for conventional and single-pointdiamond interchangesrdquo Transportation Research Record vol1356 p 47 1992

[7] D R Merritt ldquoGeometric design features of single-point urbaninterchangesrdquoTransportation Research Record pp 112-112 1993

[8] Single-Point Urban Interchange 2017 httpsenwikipediaorgwikiSingle-point urban interchange

[9] Z Z Tian and A A Dayem ldquoTechniques to improve safety andoperations at signalized diamond interchanges in nevadardquo TechRep RDT 08 003 2008

[10] S R Sunkari and I I Urbanik ldquoSignal design manual fordiamond interchangesrdquo Tech Rep FHWATX-011439-6 2000

[11] N A Chaudhary and C L Chu ldquoGuidelines for timing andcoordinating diamond interchanges with adjacent traffic sig-nalsrdquo Tech Rep TX-004913-2 Texas Transportation InstituteTexas A ampM University System 2000

[12] E C-P Chang S L Cohen C Liu N A Chaudhary andC Messer ldquoMAXBAND-86 program for optimizing left-turnphase sequence in multiarterial closed networksrdquo Transporta-tion Research Record no 1181 pp 61ndash67 1988

[13] Z Z Tian K Balke R Engelbrecht and L Rilett ldquoIntegratedcontrol strategies for surface street and freeway systemsrdquoTransportation Research Record no 1811 pp 92ndash99 2002

[14] S Lee C Lee and D-G Kim ldquoDesign and evaluation ofactuated four-phase signal control at diamond interchangesrdquoKSCE Journal of Civil Engineering vol 18 no 4 pp 1150ndash11592014

[15] W Hughes R Jagannathan D Sengupta and J E HummerldquoAlternative intersectionsinterchanges informational report(AIIR)rdquo No FHWA-HRT-09-060 2010

[16] M J Smith and N J Garber ldquoGuidelines for selecting single-point urban and diamond interchanges Nationwide survey andliterature reviewrdquo Transportation Research Record no 1612 pp48ndash54 1998

[17] J Bared A Powell E Kaisar and R Jagannathan ldquoCrash com-parison of single point and tight diamond interchangesrdquo Journalof Transportation Engineering vol 131 no 5 pp 379ndash381 2005

[18] C J Messer Single Point Urban Interchange Design and Opera-tions Analysis vol 345 Transportation Research Board 1991

[19] B B Park and J D Schneeberger ldquoMicroscopic simulationmodel calibration and validation case study of VISSIM simu-lation model for a coordinated actuated signal systemrdquo Trans-portation Research Record vol 1856 pp 185ndash192 2003

[20] RDowling A Skabardonis J Halkias GMcHale andG Zam-mit ldquoGuidelines for calibration of microsimulation modelsframework and applicationsrdquo Transportation Research Recordno 1876 pp 1ndash9 2004

[21] B Park and H Qi ldquoDevelopment and evaluation of a proce-dure for the calibration of simulation modelsrdquo TransportationResearch Record no 1934 pp 208ndash217 2005

[22] S Menneni C Sun and P Vortisch ldquoMicrosimulation calibra-tion using speed-flow relationshipsrdquo Transportation ResearchRecord no 2088 pp 1ndash9 2008


[23] N E Lownes and R B Machemehl ldquoSensitivity of simulatedcapacity to modification of VISSIM driver behavior param-etersrdquo Transportation Research Record vol 1988 pp 102ndash1102006

[24] J P Leisch T Urbanik II and J P Oxley ldquoComparison oftwo diamond interchange forms in urban areasrdquo ITE Journal(Institute of Transportation Engineers) vol 59 no 5 pp 21ndash271989

[25] HighwayCapacityManualHCM2010 TransportationResearchBoard National Research Council Washington DC USA2010

[26] R Wang J Hu and X Zhang ldquoAnalysis of the driverrsquos behaviorcharacteristics in low volume freeway interchangerdquoMathemat-ical Problems in Engineering vol 2016 Article ID 2679516 9pages 2016

[27] ATMS Central Management System 2018 httpswwwtraffic-warecomcentral-managementhtml

[28] G Yang H Xu Z Wang and Z Tian ldquoTruck accelerationbehavior study and acceleration lane length recommendationsfor metered on-rampsrdquo International Journal of TransportationScience and Technology vol 5 no 2 pp 93ndash102 2016

[29] G Yang H Xu Z Tian and Z Wang ldquoVehicle speed andacceleration profile study for metered on-ramps in CaliforniardquoJournal of Transportation Engineering vol 142 no 2 2016

[30] A R De Villa J Casas M Breen and J Perarnau ldquoMinimis-ing GEH in static OD estimationrdquo in Australasian TransportResearch Forum Proceedings 2 vol 4 2013

[31] W Li W Wang and D Jiang ldquoCapacity of unsignalized inter-sections with mixed vehicle flowsrdquo Transportation ResearchRecord Journal of the Transportation Research Board vol 1852no 1 pp 265ndash270 2003

International Journal of

AerospaceEngineeringHindawiwwwhindawicom Volume 2018

RoboticsJournal of

Hindawiwwwhindawicom Volume 2018


Active and Passive Electronic Components

VLSI Design



Shock and Vibration


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of



Journal ofEngineeringVolume 2018

SensorsJournal of



RotatingMachinery


Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation


Hindawi

wwwhindawicom Volume 2018

Advances in

Multimedia

Submit your manuscripts atwwwhindawicom


the Cityrsquos Advanced Traffic Management System (ATMS)Seven different turning volume scenarios combined with asensitivity analysiswere applied whichwas supposed to coverthe most realistic traffic conditions At the same time ananalytical model is introduced for estimating capacity withemphasis on the impact of early returns and discharge flowrate based on which the interchange capacity can be moreaccurately evaluated The delay of interchanges can also berealistically adjusted as a result of modification on capacityfunction

The rest of the paper is organized as follows first acomprehensive literature review on the previous studiesthen description of the case study site and the calibrating theexisting models on capacity and delay after that evaluationmethodology and VISSIM model calibration finally resultsanalysis and conclusions of this study

2 Literature Review

An increasing volume of literature is available on the oper-ational features applications and safety concerns of bothinterchanges Meanwhile calibration and validation of mi-crosimulation road network are also constantly growing

21 Operational Features and Applications of SPUI and TDIThe ITE Freeway and Interchange Geometric Design Hand-book first officially documented the interchange types ofSPUI and TDI [3] In recent decades ascribed to the increas-ing urban traffics both interchanges have been constantlystudied in order to seek the one that has more operationalefficiency In reality the two interchanges appeared to havedifferent advantages SPUI was found to have less right of wayconstraints in contrast to TDI according to conflict pointstheory [4] Moreover its special geometry also enables thedual left-turn operation and thus improves the operationalefficiency in heavy left-turn scenarios Apart from the fewerconflict points its wide radius [5 6] can also help to reinforcethe operational efficiency by awarding a higher turning speedto vehicles on which the capacity would be enlarged Besidesthose advantages its disadvantage is also noticeable SPUIdesign usually cannot accommodate site with limited spacesince it requires a longer bridge span [7] for the dedicatedleft-turn lanes implementation Another obvious deficient isits large open area which has different entry points which canbe unsafe due to the fact that vehiclesmaymisunderstand andviolate lane remarks

The application of the SPUI is currently prevalent but notlimited to theUS It also aroused attention fromvariousAsiancountries In Hong Kong the Kwai Tsing interchange usedthe design of SPUI [8] In Indonesia National Route 1 has theSPUI design implemented on its mainline [8] In Singaporethe SPUI was implemented in Eunos Flyover [8] Apart fromAsia SPUI was also widely accepted in Australia [8]

22 Operational Features and Applications of TDI The mostsignificant advantage of TDI is its appearance since it issimilar to two standard intersections it can greatly reducethe confusions among drivers Moreover it does not requireadditional land resources and a longer bridge span [5] to

fulfill the implementation which may better accommodateurban conditions However the design of TDI may notaccustom to heavy left-turn conditions according to the pre-vious research The reason may due to its capacity limitationbetween its two intersections

The application of TDI greatly benefits from its multiplecontrol types Three-phase [9ndash11] and four-phase control arerecommended with different conditions As the increasedpercentage of TDI interchanges is deployed in urban areasfour-phase controls are frequently employed because it couldenable vehicle make no stops in the middle which catereddriverrsquos expectationThemost popularmethod to achieve thisis to use TTI four-phase operation [12ndash15] It overlaps theramp phase and through phase via two dummy phases andthe operational efficiency was thus enhanced

23 Studies on Safety The safety issues were also necessary tobe considered In the view of safety FHWA reportmentionedthat the SPUI might be advantageous to TDI due to itsfewer conflict points In other words the SPUI is expectedto cause less safety problem regarding this view HoweverSmithrsquos study [16] did not find significant safety performancedifference between two interchanges This conclusion alsoreceived the support from field investigation [17] Anothersafety researchwas conducted byMesser et al [18] they foundthat in most cases the red clearance time was insufficient butno evidence proved that this limitation causes severe safetyissues in the real world Therefore by now no solid evidenceindicated that one interchange type is over another regardingthe view of safety

24 Studies on Microscopic Simulation Recent years guide-lines published on the microscopic simulation were continu-ously updated those methodologies benefited researchers ingenerating reasonable microscopic simulation models Parket al [19] came up with a microscopic simulation modelcalibration and validation procedure and then tested it onan arterial Dowling and his fellows [20] were devoted toa systematic level calibration and emphasized the practicaloperational studies Park et al [21] later provided a moreformal procedure for calibration of microscopic level modelsand in this research VISSIM was applied Menneni et al [22]proposed another research on microsimulation calibrationbut in the view using the speed-flow relationship Its test bedwas US-101 and results approved the approach with betterperformance than capacity view methods Three years laterLownes et al [23] were dedicated to calibrated driver behaviorparameters which aims to provide a better estimation ofdriversrsquo influence to capacity

25 Existing Research Shortcoming The research abovealready stated the pros and cons of the two interchanges inmultiple aspects However very fewmentioned the change inoperational efficiency when SPUI is implemented with twofrontage roads Leisch [24] mentioned that with the frontageroad the SPUI delay would approximately have an increaseof 30 However this conclusion has not been updatedfor several decades It may differ from todayrsquos results dueto the fact that traffic volumes and driving patterns have



3 Case Study







119888 = 119873 sdot 119878 sdot119892119862 (1)



119888 = 119873 sdot 119878119889 sdot119892119862 (2)



119888 = 119873119894 sdot 119878119889119894 sdot1198921015840119894119862

(3)




1

7744

8833

2

2 1 4 387


On ramp On ramp


2222

6666

8+16

4+12


On ramp

55+6

11+2

2 4 12 18716 5





119899

sum119894119895=0

119888119894119895 =119899

sum119894=0

119873119894 sdot 119878119889119894 sdot119892119888119894 sdot 119890119894119862+119899

sum119895=0


























BASE SCENARIO


SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e









119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




3 Case Study







119888 = 119873 sdot 119878 sdot119892119862 (1)



119888 = 119873 sdot 119878119889 sdot119892119862 (2)



119888 = 119873119894 sdot 119878119889119894 sdot1198921015840119894119862

(3)




1

7744

8833

2

2 1 4 387


On ramp On ramp


2222

6666

8+16

4+12


On ramp

55+6

11+2

2 4 12 18716 5





119899

sum119894119895=0

119888119894119895 =119899

sum119894=0

119873119894 sdot 119878119889119894 sdot119892119888119894 sdot 119890119894119862+119899

sum119895=0


























BASE SCENARIO


SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e









119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



1

7744

8833

2

2 1 4 387


On ramp On ramp


2222

6666

8+16

4+12


On ramp

55+6

11+2

2 4 12 18716 5





119899

sum119894119895=0

119888119894119895 =119899

sum119894=0

119873119894 sdot 119878119889119894 sdot119892119888119894 sdot 119890119894119862+119899

sum119895=0


























BASE SCENARIO


SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e









119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia




119899

sum119894119895=0

119888119894119895 =119899

sum119894=0

119873119894 sdot 119878119889119894 sdot119892119888119894 sdot 119890119894119862+119899

sum119895=0


























BASE SCENARIO


SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e









119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia





BASE SCENARIO


SBTSBL

SBR

WBTWBL

WBR

NBL

NBT

NBR EBT

EBL

EBR

0

100

200

300

400

500

600

700

800

900

0 100 200 300 400 500 600 700 800 900

Fiel

d Vo

lum

e









119872119860119875119864 = 1119899

119899

sum119894=1

1003816100381610038161003816100381610038161003816100381610038161003816

119872119898 minus119872119891119872119891

1003816100381610038161003816100381610038161003816100381610038161003816(5)



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



0

2

4

6

8

10

12

14

16

18

20

22

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals


0

2

4

6

8

10

12

14

16

18

1 2 3 4 5 6 7 8 9 10 11 12

Que

ue C

ount

s

Time Intervals






7 Results






0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



0

20

40

60

80

100

120

140


Aver

age D

elay

(s)

Scenarios





0

5

10

15

20

25


Aver

age S

peed

(mph

)

Scenarios






0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



0

50

100

150

200

250

300

350

400


Aver

age Q

ueue

Len

gth

(ft)






y = 09641x + 09196

0

20

40

60

80

100


Dela

y Es

timat

ed b

y N

ew M

odel

(s)

２2= 09839








9 Conclusion






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






Data Availability




Acknowledgments


References



































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia














RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


Microsimulation Analysis of Traffic Operations at Two...

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Transcript of Microsimulation Analysis of Traffic Operations at Two...