Simulation of a Large Freeway/Arterial Network with CORSIM, INTEGRATION and WATSim

Transcription

1 Simulation of a Large Freeway/Arterial Network with CORSIM, INTEGRATION and WATSim PANOS D. PREVEDOUROS, Ph.D. Associate Professor and YUHAO WANG M.S.C.E. Department of Civil Engineering University of Hawaii at Manoa 240 Dole Street, 383 Honolulu, HI tel.: fax: pdp@hawaii.edu Final version for publication in the Transportation Research Record April 19, 1999

2 ABSTRACT Simulation of a large integrated (street/freeway) network with three state-of-the art software is presented. The 20 centerline km network includes three on-ramps, three off-ramps, an on/offramp weaving section, and a high design arterial with eleven signalized intersections. All three software were able to replicate field measured volumes well, after considerable modifications to default settings. INTEGRATION required extensive modifications to approximate complex signal timing plans and had problems with lane alignment on the wide arterial. CORSIM s FRESIM component had a problem with vehicles that miss their destination and required carfollowing parameter settings corresponding to unusually high capacities to produce good results. WATSim needed the fewest modifications and it was primarily sensitive to merging/acceleration lengths. WATSim and CORSIM speeds were close to each other. INTEGRATION s simplified treatment of signalization produced higher street link speeds. 1

3 INTRODUCTION A traffic engineering literature search for comprehensive comparisons of traffic software based on real-world applications will yield little, particularly with respect to newer software. Overviews of software can be found through McTrans, PC-Trans, developers publications and a long term study at Leeds University (1) which is the most up-to-date and comprehensive software summary yet. This paper presents simulation results from the application of three state-of-the-art software, INTEGRATION (2), CORSIM (3), and WATSim (4), on a rather large (20 centerline kilometers) freeway/arterial integrated network. Smaller-scale applications which also include comparisons with field measured characteristics (e.g., speed) were first investigated (). INTEGRATION, TSIS/CORSIM, and WATSim were applied to three heavily loaded traffic networks for which exact volumes and speeds (on specific lanes and locations) were known. The models produced reasonable and comparable simulated results on most of the tested network links. The experiments also revealed that the main limitation of these models is the large number of parameters that need to be modified in order to replicate the real traffic conditions. In no case did the default parameters offer satisfactory results. Specific strengths and weaknesses of the three software examined in () were as follows: CORSIM has the most realistic lane-changing maneuvers. Oddly, car-following parameter settings corresponding to freeway capacities as high as 3,000 vphpl were used to duplicate the real traffic conditions. (CORSIM does not utilize capacity; see discussion later.) As in 2

4 NCHRP 38, we concluded that the percentile input for off-ramps is inconvenient and causes difficulty in replicating field conditions. INTEGRATION is the only model which can simulate the U-turn movement among these models, but it also has the most limited ability to simulate signalized intersections. The optional lane-striping file enhances flexibility in simulating a variety of traffic operations, but the lane-changing mechanism may not reflect Honolulu driver behavior (e.g., most weaving maneuvers occur at the first 1 / 3 of a given weaving length) and is not user-adjustable. WATSim required the least modification to default parameters to achieve good results but its animation is relatively inferior. The globally (both the surface street and freeway) applied NETSIM car-following and lane-changing parameters are derived internally based on userinput capacity; direct user-input would be more desirable. Although in our earlier research we concluded that given some effort for parameter calibration, the three models are capable of fitting detailed field data, it is uncertain whether this capability is applicable to large integrated networks. Thus, the objective of the second part of the research was to: simulate the existing traffic conditions of a large integrated network, assess the ability of each model to replicate existing traffic flows, and compare the relative magnitudes of the resultant measures of effectiveness (MOEs), primarily speed. 3

5 DATA DESCRIPTION The network consists of the eastbound H-1 freeway, the one-way eastbound School St., east- and westbound Vineyard Blvd. and nine bi-directional north-south streets. Within this network, the Liliha St. on-ramp merge and Pali Hwy. on-ramp/kinau St. off-ramp weaving sections are heavily congested during the morning peak period, as is the eastbound traffic on Vineyard Blvd. This network is depicted in Figure 1 along with a large part of the data. Additional specifications for the data are given below. 1. A 1-minute period (7:30-7:4 AM) was simulated after proper initialization. The initialization was also 1 minutes long, so each run simulated one half hour. The aforementioned period is the peak 1-minutes. The entire peak hour was not simulated due to time limitations considering the size of the network, the processing speed (first generation 86 processor) and the large number of runs required for parameter adjustment with each software. 2. Freeway volumes were counted from videotapes using AUTOSCOPE and by manually checking selected ramps and mainline segments. All freeway data used in the analyses are from simultaneous and contemporaneous tapes. 3. O-D data are needed to run INTEGRATION. There are 23 origin-destination nodes in the network. The O-D matrix was derived on the basis of the observed link volumes, turning movements, and on-ramp destination surveys. An iterative process assured that differences between actual and estimated (O-D) volumes were within 1% (6). 4. Intersection volumes were obtained in the field. All counts were taken by a team of 10 people. At two critical locations (nodes 1 and 7 in Figure 1), intersection counts were done at the same time with freeway counts. The counts in other locations were taken within two 4

6 weeks from the date of freeway counts, excluding Mondays and Fridays. In general, the intersection counts were stable and consistent.. Traffic signal data were collected simultaneously with volume data. All signals in this network operate in actuated mode, but most are not coordinated. Actuated data were averaged and the signalization was modeled as pretimed. This was necessary for two reasons: (i) INTEGRATION can only model pretimed signal timings, and (ii) field measurements are not sufficient for deriving all the parameters required for NETSIM (which is a part of CORSIM and WATSim) simulation. The latter problem could not be overcome because the responsible agency did not provide signal controller settings. Intersections 1 and 7 (Figure 1) operated on a fixed 10 second cycle from 6:30 to 9:00 A.M. During the most part of the peak hour, the rest of the signals were running in a pretimed mode (maxed out) since all critical approaches were saturated. As a result, a de facto pretimed operation was in effect during the simulated peak 1 minutes. 6. Since traffic flow changes with space, 10 m link increments were modeled along the freeway mainline to compare the three models' results over space. 7. H-1 freeway has 3 lanes per direction throughout the simulated segment. Vineyard Blvd. is a high-design arterial with 3 lanes per direction and left turn lanes at all intersections. Several streets intersecting Vineyard Blvd. also have exclusive right and left turn lanes. The base settings for essential network simulation parameters are shown below. Several of these settings were subsequently modified to improve model fit.

7 Vineyard Other Freeway Ramp Blvd. streets sat. flow rate (vphpl) free-flow speed (km/h) speed at capacity (km/h) jam density (v/km/l) TESTED SOFTWARE TSIS/CORSIM and WATSim are similar in many respects, whereas INTEGRATION s logic is distinctly different. The essentials of the tested software are reviewed next. CORSIM is virtually a combination of two microscopic models, NETSIM and FRESIM. These two predecessor models are reviewed first. NETSIM (NETwork SIMulation) is the only microscopic model available for urban street networks. NETSIM, formerly called UTCS-1, was initially released in 1971 and integrated within the TRAF (an integrated traffic simulation system) in the early 1980s. NETSIM can simulate most operational conditions experienced in an urban street network environment. It provides a high level of detail and it may be the most widely-used traffic simulation model (7). The TRAF-NETSIM model uses an interval-scanning simulation approach to move vehicles each second according to car-following logic and in response to traffic control and other conditions (8). Like most other stochastic models, TRAF-NETSIM uses Monte Carlo simulation to represent real-world behavior. Therefore, the individual vehicle/driver combinations, the vehicle turning movements on new links, and many other behavioral and operational decisions are all represented as random processes. The recent version of TRAF- NETSIM uses an identical seed number technique to represent identical traffic streams and reduce output variability (9). 6

8 INTRAS (INtegrated TRAffic Simulation) is a microscopic, stochastic simulation model, developed by KLD Associates in the late 1970s and was enhanced continuously through the 1980s (10). It uses a vehicle-specific, time-stepping, highly detailed lane-changing and carfollowing logic to realistically represent traffic flow and traffic control in a freeway corridor and surrounding surface street environment. INTRAS requires fairly detailed geometric and traffic information, including link length, lane numbers, location, free-flow speeds, vehicle composition, traffic volumes, O-D data, etc. This model has been used to evaluate the freeway reconstruction alternatives (11) and weaving area capacity analysis (12,13). These research results pointed out that INTRAS was not yet fully operational, especially in the freeway weaving areas. JFT and Associates reprogrammed INTRAS with support from the FHWA according to structure design techniques and made more user-friendly. The revised model was called FRESIM and it also became a part of the TRAF family (10,14). The FRESIM model can simulate complex freeway geometrics, such as lane add/drop, inclusion of auxiliary lanes, and variation in slopes, superelevation, and radius of curvature. The model can handle freeway operational features such as lane-changing, on-ramp metering, and representation of a variety of traffic behaviors in freeway facilities. FRESIM has become the most complete and updated microscopic freeway simulation model. CORSIM is capable of simultaneously simulating traffic operations on surface streets as well as freeways in an integrated fashion. However, within the earlier integrated traffic simulation system (TRAF), the total freeway/urban street systems simulated by the combination of NETSIM and FRESIM could only be called "composite" networks rather than the fully "integrated" networks, in terms of the TRAF system characteristics of distinct separation of the assignment and simulation phases of the analysis, independent control strategies in each subnetwork, data 7

9 transfers between models/modules, and the lack of rerouting capability (1). At the present, a Windows version of TSIS (Traffic Software Integrated System) (3) is available to provide an integrated, user-friendly, graphical user interface and environment for running CORSIM. A traffic assignment module with two assignment options, system optimal or user equilibrium, is available in NETSIM. It utilizes user input O-D trip information to generate turning fractions for intersections. TSIS/CORSIM was released for public use late in spring 1996; version 4.2 became available in spring WATSim (Wide Area Traffic Simulation) is based entirely on NETSIM and was first presented at the 1996 annual meeting of the Transportation Research Board. At the time of the tests WATSim was not marketed as a stand-alone software but it is offered as part of a contract with its developer, KLD Associates. However, the developer planned to offer WATSim as a standalone software sometime in WATSim extends the functionality of TRAF-NETSIM to incorporate both freeway and ramp operations simulation with surface street traffic simulation. WATsim s operational features include those in TRAF-NETSIM plus HOV configurations, light rail vehicles, toll plazas, path tracing, ramp metering, and real time simulation and animation (4). The WATSim simulation model also includes an interface with a traffic assignment model. INTEGRATION was developed in the late 1980s (16). It is a mesoscopic routingoriented simulation model of integrated freeway and surface street networks. In the model, individual vehicle movements through the network are traced to monitor and control the unique behavior of vehicles that belong to a certain subpopulation. The model differs from most other models in that only the aggregate speed-volume interactions of traffic and not the details of a vehicle's lane-changing and car-following behavior are explicitly considered (17), thus, its classification as mesoscopic. The model is routing- based in that only a vehicle's trip origin, 8

10 destination, and departure times are specified external to it, leaving the actual trip path and the arrival times at each link along the path to be derived within the simulation based on the modeled interactions with any other vehicles. Another distinctive feature of the INTEGRATION is that it may be the first simulation model which considers the ITS route guidance information in the vehicle routing/rerouting mechanism (18,19). While INTEGRATION provides a graphical capability to view vehicles as they move through the network, it provides no graphical user interface (GUI) for viewing and editing network data. Some view this as a main drawback of INTEGRATION because the ability to view/edit data is essential for model setup, calibration, and scenario testing (20). A much more sophisticated version of INTEGRATION (v.20 able to run under Windows) became available in late 1998 but was not used in our tests. INTEGRATION Simulation Two major problems were revealed during the simulations with INTEGRATION. The first is the traffic congestion in the 4-lane Pali Hwy. on-ramp/kinau St. off-ramp weaving section (see Figure 1). This section consists of a 3-lane freeway mainline and an auxiliary lane which begins at the Pali Hwy. on-ramp and ends at the Kinau St. off-ramp. The animation showed that almost all weaving maneuvers were completed at the divergence point of the weaving section. Many weaving vehicles from the upstream mainline to the Kinau St. off-ramp remained on the two left lanes while they approached the divergence point. Then, they stopped in search of gaps for lane change and exit through the off-ramp. As simulation time elapsed, the queue extended backward both on the mainline and on the Pali Hwy. on-ramp, a phenomenon that does not occur in reality. 9

11 This simulation problem did not improve by using a higher freeway capacity (2,00 vphpl). Instead, a lane-stripping file was used to force the weaving vehicles from the upstream mainline to the off-ramp to change lanes earlier. By using the striping file with a 2,300 vphpl capacity, the weaving congestion (which was largely a software artifact) was greatly reduced. A more extensive problem was the signal control at intersections. In INTEGRATION, any link can be served by up to two signal phases. However, links with protected left turns often are served in three phases (i.e., left only, left and through, through only). In small networks this problem can be solved by using a separate link configuration for the left turn movement, as explained later. However, link prohibition codes must be defined for each link, otherwise some through (or left-turn) vehicles may get into and clog the left-turn (or through) link. To avoid this occurrence, different vehicle types need to be specified for left-turn and through movement vehicles in the INTEGRATION O-D file. The problem with larger networks such as the one presented herein is that there are 9 intersections along Vineyard Blvd. and most have protected left turns, but there are only vehicle types which can be defined in the O-D file. As a result, up to 4 intersections per direction can be modeled with left turn bays and exclusive left turn phasing, i.e., vehicle types 1, 2, 3 and 4 along the north-bound direction are destined to the left turn bays at intersections 1, 2, 3 and 4, respectively and vehicle type are through vehicles; similarly for the east-, west-, and southbound approaches. Thus, a separate link configuration can be utilized to deal with the signal problem for only a part of this large network. For links on which a separate link configuration was not specified, the left-turn operation is, by default, modeled as permitted (the impact of permitted left turns on the simulated speeds is 10

12 discussed later). An example of separate link configuration is depicted in Figure 2 and is described below. Three distinct issues were present at the Vineyard/ intersection, node 1 in Figure 1. First, phase 4 does not permit left turns, but INTEGRATION cannot prohibit left turns as long as they are modeled as a part of the through link. This issue is present at all the intersections along the Vineyard Blvd. arterial. Second, U-turns are permitted on (and are a sizeable portion of) the west-bound left turn operation (twin-lane). This issue applies to a few other intersections along this arterial. Third, INTEGRATION internally determines the proper alignment between an upstream link and its downstream link. This is true for a 3-lane link which is followed by a 3- or 2-lane downstream link. However, a lane alignment problem was found for a 4-lane link (Link 13) or a -lane link (Link 11) which are followed by 3-lane downstream links. INTEGRATION assigned the two through lanes to the middle lane of the downstream link. This issue also applied to other intersections along Vineyard Blvd. To solve these signalization and lane alignment problems, the geometry was modified to include a separate link for each protected left turn movement. For example, Link 11.1 in Figure 2 is created for left-turn (and U-turn) movements only; through movement vehicles are prohibited from using it. In INTEGRATION, no two links can have identical starting and ending nodes. This is bypassed by introducing an extra node (i.e., Node k in Figure 2), which splits the through movement into two sublinks (Link 11.2 and Link 11.3). In this way, the through and left turn movements no longer have nodes i and j as common start and end. This simple node insertion and link assignment resolved both the lane alignment and signal phasing issues. A sample resolution is given next. 11

13 Phases 2 and 3 were modeled for Link 11.1, and phases 3 and 4 were modeled for Link 11.3, exactly as in real conditions; the phasing diagram is shown below node 1 in Figure 1. The three through movement lanes of Link 11.3 were all correctly aligned to the corresponding lanes of the downstream link because there is no lane drop between Link 11.3 and Link 16. Destination node m is all that was required for the U-turns on Link 11.1 to work. The separate link configuration was modeled for the eastbound Vineyard Blvd. links to Palama St., Liliha St. and Aala St. intersections and for westbound Vineyard Blvd. links to St., Queen Emma St., Pali Hwy. and Nuuanu Ave. intersections. All these Vineyard Blvd. links have three signal phases. Table 1 lists the actual and simulated volumes on critical freeway links and street links. The errors are very small on freeway links and within ±% on most street links. CORSIM Simulation CORSIM s NETSIM component had no problems with default model parameters for the surface street subnetwork, but low freeway volumes and a large number of destination-reassigned and missed vehicles were produced by FRESIM. Car-following and lane-changing parameters have significant effects on FRESIM results. The FRESIM default car-following parameters usually cannot produce good results (). For this network simulation, car-following parameters were decreased from the default array [1,14,13,12,11,10,9,8,7,6] to [4,4,4,4,3,3,3,3,2,1] which, according to Payne (21), increases the capacity from the default level of 2,30 vphpl to about 3,300 vphpl. The lanechanging parameters were set to 2. seconds of lane-changing duration and 2% of cooperative drivers; the defaults are 3.0 seconds and 20%, respectively. Lane change activating distances 12

14 were modified from the default 2,00 ft. (70 m) to 4,00 ft. (1,30 m) for vehicles diverging to the Pali Hwy. off-ramp and 3,000 ft. (900 m) to the St. off-ramp. Table 2 lists the simulated volumes on critical links of the network. All volume errors are small. Multiple replications gave surprisingly (given the size of the network) consistent results with speeds on selected critical links varying by only 2 to km/h. WATSim Simulation Freeway capacities can be defined explicitly in WATSim, which is a desirable feature. Capacities of 2,300 vphpl and 2,000 vphpl were assigned to freeway mainline links and ramps, respectively. Most lane-changing default parameters remained unchanged, except for the distance for activating the mandatory lane-changing maneuvers. This distance parameter was modified from the default 10 ft. (4 m) to 600 ft (180 m). There were no simulation problems for the surface streets with the default model parameters. However, a significant problem was present at the Liliha St. on-ramp merge segment. The Liliha St. on-ramp vehicles merged into the mainline smoothly, but the upstream mainline vehicles were excessively impeded. By changing the capacity of the merge link from 2,300 vph to 2,00 vph and increasing the link length from 21 ft. (6 m) to 400 ft. (120 m) --the added length was subtracted from the immediate downstream mainline link-- both mainline and on-ramp vehicles could merge into the downstream mainline segment. The simulated volumes are listed in Table 3. Again, good proximity between actual and simulated volumes was achieved. COMPARISON OF MOEs 13

15 The simulated travel speeds along the freeway are shown in Figure 3. The speed plots from the three simulation models exhibit similar trends. There are three obvious bottlenecks for eastbound vehicles: the Liliha St. on-ramp merge, the Pali/Kinau weaving section and the Vineyard on-ramp merge. Traffic conditions at the Liliha St. on-ramp merge segment are the worst: The simulated speeds are below 30 km/h. Notably, the CORSIM and WATSim speeds began to decrease at least 40 to 600 m upstream of the Liliha St. on-ramp link whereas the INTEGRATION speed decreased only about 10 m from the merge link. CORSIM and WATSim better represent the actual merge condition seen through the surveillance camera. Vehicle speeds gradually increase from the valley before the Liliha St. on-ramp merge and reach a maximum on the link following the St. on-ramp merge. The CORSIM and WATSim speed curves are close to each other. The INTEGRATION speed estimates were always lower than the CORSIM and WATSim speeds on off-ramp divergence segments because, as shown in the animation, some diverging vehicles on the left lanes did not change lanes early enough. Subsequently, they stopped in search of a gap and blocked the vehicles behind them. These results were produced using a lane capacity of 2,300 vph in both INTEGRATION and WATSim. As mentioned earlier, the car-following parameters in CORSIM were set to a level corresponding to a capacity of 3,300 vph (see Payne et al. (21)). The 3 m length, four-lane Pali/Kinau weaving section was modeled as two equal-length links. The minimum speeds of CORSIM (3.4 km/h) and WATSim (0.6 km/h) on the weaving section were very close, but the former was reached on the second part of the weaving section and the latter on the first part. vehicles reached minimum speed on the second part of the weaving section as well; its output differs from CORSIM s in that almost all weaving vehicles completed lane-changing maneuvers at the off-ramp divergence point. 14

16 The Vineyard Blvd. on-ramp merge segment also is a major bottleneck along the eastbound H-1 freeway. CORSIM and WATSim produced comparable speeds on this segment whereas INTEGRATION s speed was high. Simulated speeds on the link downstream of the Vineyard Blvd. on-ramp merge increase rapidly within a short distance. Actual speed profiles are available from HDOT instrumented vehicle surveys. Surveys from four days in 1997 and 1998 (at 7:30 and 8:00 A.M.) were averaged to generate the speed profile labeled ACTUAL in Figure 3. The plots of model speed output and actual speed averages are similar. One exception is the Pali-on/Kinau-off section which all models tend to over-represent as a bottleneck. Also, congestion caused by the Vineyard on-ramp bottleneck propagates backward and the predicted speeds of about 80 km/h at the location labeled upstream of Vineyard merge are not realized. This is a likely consequence of the short simulation period. Figure 4 illustrates the simulated speeds along the eastbound Vineyard Blvd. Travel speed on a street link is defined as the link length divided by the total time, including stop time, that all vehicles experience on the link. The curves from all software are very close to each other, except for INTEGRATION s speed at the Nuuanu Ave. intersection. Since the separate link configuration was not modeled for the left turn lane of this link, vehicles on left-turn pockets were permitted to turn left during the through movement phase. Therefore, the simulated stop times for left-turn vehicles were shorter than the actual times, resulting in higher speeds in comparison with reality and with the protected left-turn movements simulated in CORSIM and WATSim. For eastbound Vineyard Blvd. links to the Pali Hwy., Queen Emma St. and St. intersection, the INTEGRATION speeds are close to the CORSIM and WATSim speeds although the separate link configuration was not modeled. This is because both the through movement phase length at these intersections is relatively shorter than at the Nuuanu Ave. 1

17 intersection and the opposing through movements are heavy, so few, if any, permitted left-turns occurred. Actual travel speeds are not available for comparison. The simulated speeds on westbound Vineyard Blvd. links are presented in Figure. The link speeds from the three models are close to each other for out of 9 intersections. The separate link configuration was specified for these links in INTEGRATION. For westbound Vineyard Blvd. links west (to the left in Figure ) of Nuuanu Ave., the INTEGRATION speeds are considerably different from the CORSIM and WATSim speeds. Permitted left-turn operations adopted due to software limitations resulted in higher INTEGRATION speeds. Actual travel speeds are not available for comparison. Summary results from the 2,16 m freeway mainline segment between the Liliha St. onramp and the Vineyard Blvd. on-ramp, and the 1,72 m segment of Vineyard Blvd. between Palama St. and St. are shown below. All CORSIM and WATSim results are close. The INTEGRATION results are somewhat different, especially on the freeway mainline and westbound arterial. Using CORSIM as the base, WATSim estimates vary between -9% and %; INTEGRATION estimates vary between -22% and 28%. TRAVEL TIME (sec/veh) FREEWAY EB Arterial WB Arterial INTEGRATION CORSIM WATSim

18 AVERAGE TRAVEL SPEED (km/h) FREEWAY EB Arterial WB Arterial INTEGRATION CORSIM WATSim CONCLUSIONS AND DISCUSSION INTEGRATION s two main problems are in modeling complex signalization and lanechanging. INTEGRATION speeds are higher than the speeds obtained from the other two models on links where protected left-turn operation cannot be modeled using the separate link modification developed and presented herein. While in CORSIM and WATSim the distance for activating mandatory lane-changing maneuvers can be adjusted so that vehicles may activate lane changes earlier, INTEGRATION does not permit user input. Instead, the lane-changing propensity gradually increases as a vehicle approaches a "hardwall" (2), at which point, a mandatory lane change must be completed. As a result, vehicles may give up lane-changing opportunities on upstream, less congested links and finally cannot find gaps to change lanes under heavy traffic conditions near the "hardwall." This usually leads to some stopped vehicles on freeway divergence segments and surface streets with heavy turn movements. CORSIM and WATSim employ a similar logic in simulating surface street networks, and both produced close results for the Vineyard Blvd. arterial and other street links. However, the difference in freeway simulation is apparent. CORSIM evokes FRESIM which usually produced lower simulated speeds on freeway on-ramp merge segments. The CORSIM parameters (especially the car-following factors that affect capacity) needed radical modifications to duplicate 17

19 observed volumes, which is not a desired feature. Relatively speaking, WATSim can produce reasonable results with fewer adjustments. Within the examined network, only the Liliha St. onramp merge with its short acceleration length presented a difficulty for WATSim. The latest version of TSIS/CORSIM (4.2) produced more missed and re-assigned vehicles. It is hoped that answers to the questions such as: 1) what did the model do with these vehicles? 2) why these vehicles did not reach their intended destination? and 3) what parameters affect the growth and decay of missed/re-assigned vehicles? posed by Jacobson (22) are answered soon. Judging by the comparisons of actual versus simulated volumes for freeway and street links, all three software examined produced acceptable results for the simulated network. These software were able to handle the integrated freeway/arterial network and produced helpful animation in addition to a multitude of numerical outputs. Best results were achieved with the NETSIM-based models which could be improved further by encoding the actuated signal operation. INTEGRATION execution is hampered by the tedious O-D table determination and the modeling of complex signalization and lane-changing. However, after reliable O-D flows have been estimated, then, INTEGRATION is more efficient and arguably more suitable for planning analyses that involve significant vehicle routing changes (e.g., lane closures, directional changes, turn prohibitions, ITS applications, etc.). Acknowledgment The authors wish to thank FHWA and McTrans-University of Florida for the supply of and assistance with TSIS/CORSIM as well as Mr. R. Goldblatt of KLD Associates, Inc. for the supply of and assistance with WATSim. 18

20 REFERENCES 1. SMARTEST: Simulation Modeling Applied to Road Transport European Scheme Tests, Leeds University, 2. VanAerde, M. and the Transportation Systems Research Group. INTEGRATION - Release 2, User's Guide. December, KAMAN Science Corporation. CORSIM User's Guide Version June, KLD Associates, Inc. WATSim Model: User Guide. April, Wang, Y. and P. D. Prevedouros. Comparison of CORSIM, INTEGRATION, and WATSim in Replicating Volumes and Speeds on Three Small Networks. In Transportation Research Record 1644, TRB, National Research Council, Washington, D.C., 1998, pp Wang, Y. Evaluation of Integrated Traffic Simulation Models: CORSIM, INTEGRATION, and WATSim. Master Thesis, Department of Civil Engineering, University of Hawaii at Manoa, Rathi, A. K., and A. J. Santiago. The New NETSIM Simulation Program. Traffic Engineering & Control, No., pp ,

21 8. Andrews, B., E.B. Lieberman and A. J. Santiago. The NETSIM Graphic System. In Transportation Research Record 1112, TRB, National Research Council, Washington, D.C., pp , Rathi, A. K. and A. J. Santiago. Identical Traffic Streams in the TRAF-NETSIM Simulation Program. Traffic Engineering & Control, No. 6, pp. 31-3, May, A. D. Simulation Models Revisited. In Transportation Research Record 1132, TRB, National Research Council, Washington, D.C., pp , Cohen, S. L., and J. Clark. Analysis of Freeway Reconstruction Alternatives Using Traffic Simulation. In Transportation Research Record 1132, TRB, National Research Council, Washington, D.C., pp. 8-13, Skabardonis, A., M. Cassidy, A. D. May and S. Cohen. Application of Simulation to Evaluate the Operation of Major Freeway Weaving Sections. In Transportation Research Record 122, TRB, National Research Council, Washington, D.C., pp , Fazio, J., and N. M. Rouphail. Conflict Simulation in INTRAS: Application to Weaving Area Capacity Analysis. In Transportation Research Record 1287, TRB, National Research Council, Washington, D.C., pp. 42-2,

22 14. VanAerde, M., S. Yagar, S., A. Ugge and E. R. Case. A Review of Candidate Freeway- Arterial Corridor Traffic Models. In Transportation Research Record 1132, TRB, National Research Council, Washington, D.C., pp. 3-6, VanAerde, M. and S. Yagar. Dynamic Integrated Freeway/Traffic Signal Networks: Problems and Proposed Solutions. Transportation Research A, Vol. 22A, No. 6, pp , VanAerde, M. and S. Yagar. Dynamic Integrated Freeway/Traffic Signal Networks: A Routing-Based Modeling Approach. Transportation Research A, Vol. 22A, No. 6, pp , Hellinga, B. and M. VanAerde. An Overview of a Simulation Study of the Highway 401 Freeway Traffic Management System. Canadian Journal of Civil Engineering, Vol. 21, pp , Rilett, L. R., M. VanVerde and G. MacKinnon. Simulating the TravTek Route Guidance Logic Using the Integration Traffic Model Vehicle Navigation and Information Systems Conference Proceedings, pp , Case, E. R., and M. VanAerde. Supporting Routines for Modeling the Traffic Responsive Features of the Travtek System Using Integration Vehicle Navigation & Information System Conference Proceedings, pp ,

23 20. Marcus, C. T. and D. Krechmer. The Use of Simulation Models on the Central Artery/Third Harbor Tunnel Project. 199 Vehicle Navigation & Information Systems Conference Proceedings, pp , Payne, H. J., S. Thompson and G-L. Chang. Calibration of FRESIM to Achieve Desired Capabilities. Preprint, 76th Annual Meeting of the Transportation Research Board, Washington, D.C.,

24 Aala St School St Liliha On-ramp H-1 F reeway Pali Hwy. Off-ramp Off-ramp Pali Hwy. On-ramp Kinau Weaving Section 2 12 N Kinau Off-ramp 3 Vineyard Blvd To Lusitana St. 10 Palama St. 19 Pua St. 18 Liliha St Maunakea St. 1 Nuuanu Ave. 14 Pali Hwy. 13 Q. Emma St. 12 St Origin Node 9 Destination Node Origin/Destination Node Signal Actual Volume (vph) Figure 1. The simulated Vineyard Boulevard and east-bound H-1 Freeway network. Link 14 Node j Node k Node i Link 16 Link 11.3 Link 11.2 Link 11.1 Link 13 Link 1 Link 12 Node j Node m Figure 2. The separate link modification for the Vineyard Blvd. intersection with St. 23

25 Figure 3: Simulated Travel Speeds Along Eastbound H-1 Freeway Upstream of Pali On-ramp Merge Upstream of Vineyard On-ramp Merge Speed (km/h) Pali Hwy. Off-ramp Diverge Off-ramp Diverge Liliha On-ramp Merge INTEGRATION CORSIM WATSim ACTUAL Kinau Off-ramp Diverge Direction of traffic Vineyard On-ramp Merge H-1 Freeway Distance (m) 24

26 Figure 4. Simulated Travel Speeds Along Eastbound Vineyard Blvd INTEGRATION CORSIM WATSim To H-1 40 Lusitana Speed (km/h) 30 Palama Pua Maunakea Aala 20 Liliha Nuuanu 10 Direction of traffic Pali Queen Emma Vineyard Blvd. Distance (m) 2

27 Figure. Simulated Travel Speeds Along Westbound Vineyard Blvd INTEGRATION CORSIM WATSim 40 Speed (km/h) 30 Pua Aala 20 Palama Liliha Nuuanu Maunakea 10 Direction of traffic Pali Queen Emma Vineyard Blvd. Distance (m) 26

28 Table 1. INTEGRATION Volume Comparison H-1 Freeway Volume (vph) H-1 Entry Link Liliha On-ramp Pali Off-ramp Off-ramp On-ramp Kinau Off-ramp Vineyard On-ramp H-1 Exit Link Actual Simulated % error Vineyard Blvd. Link (eastbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Vineyard Blvd. Link (westbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Other Critical Street Link Volume (vph) SB Palama NB Palama SB Liliha NB Liliha SB Pali NB Pali SB NB Actual Simulated % error

29 Table 2. CORSIM Volume Comparison H-1 Freeway Volume (vph) H-1 Entry Link Liliha On-ramp Pali Off-ramp Off-ramp On-ramp Kinau Off-ramp Vineyard On-ramp H-1 Exit Link Actual Simulated % error Vineyard Blvd. Link (eastbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Vineyard Blvd. Link (westbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Other Critical Street Link Volume (vph) SB Palama NB Palama SB Liliha NB Liliha SB Pali NB Pali SB NB Actual Simulated % error

30 Table 3. WATSIM Volume Comparison H-1 Freeway Volume (vph) H-1 Entry Link Liliha On-ramp Pali Off-ramp Off-ramp On-ramp Kinau Off-ramp Vineyard On-ramp H-1 Exit Link Actual Simulated % error Vineyard Blvd. Link (eastbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Vineyard Blvd. Link (westbound, approaching the listed intersection) Volume (vph) Palama Pua Liliha Aala Maunakea Nuuanu Pali Queen Emma Actual Simulated % error Other Critical Street Link Volume (vph) SB Palama NB Palama SB Liliha NB Liliha SB Pali NB Pali SB NB Actual Simulated % error