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Figure 7.10. Speed contour map from the SB p.m. I-5 FREEVAL-RL model with CAF adjustment. Figure 7.11. Real-world speed contour map for the southbound I-5 in the p.m. period. 7.5 Scenario Testing CSMP Scenario Development The objective of the scenario testing is to evaluate if FREEVAL-RL can model the reliability of various investment scenarios found in the I-5 CSMP. Each CSMP scenario is a combination of several improvement projects. Due to the limitations of FREEVAL-RL and the limited size of the area that can be modeled in the tool, not all of the CSMP projects could be modeled and evaluated. Table 7-4 lists the CSMP scenarios and the corresponding projects for each test run. The table also indicates whether the scenario can be modeled and evaluated by FREEVAL-RL. 148
Table 7.4. I-5 CSMP Scenario Summary CSMP Scenarios Projects Applicability Notes a.m. p.m. 1 (2010 Demand) & 2 (2020 Demand) Continuous-access high-occupancy vehicle conversion from Tustin to Red Hill N/A N/A Outside study area; high- occupancy vehicle not considered Estrella interchange improvement N/A N/A Outside study area Camino Capistrano interchange improvement N/A N/A Outside study area La Paz interchange improvement N/A N/A Improved locations outside study area Jamboree interchange improvement N/A N/A Outside study area SR-74 interchange improvement YES N/A AM: Add one NB on-ramp for the traffic from EB Ortega Highway and related detectors and ramp metering 3 (2010 Demand) & 4 (2020 Demand) Advanced ramp metering with queue control N/A N/A Outside study area; ramp metering strategy not considered Connector metering on SR-57, SR- 22, and SR-55 interchanges N/A N/A Outside study area; ramp metering strategy not considered 5 (2010 Demand) & 6 (2020 Demand) a.m. Model: incident clearance time reduction at NB I-5 postmile 18.50 YES N/A p.m. Model: incident clearance time reduction at SB I-5 postmile 18.50 N/A YES 149
CSMP Scenarios Projects Applicability Notes a.m. p.m. 7 (2020 Demand) Add a second high-occupancy vehicle lane within existing high- occupancy vehicle facility in the City of Tustin and Santa Ana N/A N/A Outside study area; high- occupancy vehicle not considered. Add 1 GP lane in both directions and improve the interchanges between I-5 truck bypass and SR- 55 interchange N/A YES Add 1 GP lane in both directions between I-5 truck bypass and SR- 55 interchanges; Alternative 2B option 1 selected for interchanges reconfiguration, including Alton Pkwy., Sand Canyon Ave., Jeffrey Rd., Culver Dr., Jamboree Rd., Tustin Ranch, and Red Hill Ave interchanges. Operational improvements between El Toro and Junipero Serra interchange YES YES Add 1 GP lane in both directions between El Toro Rd. and Junipero Serra Rd. interchanges; Add new auxiliary lanes from north of SR-73 connectors to NB Avery off-ramp, and from Oso Pkwy on-ramp to La Paz off-ramp; Not applicable to # of lane more than 6; high- occupancy vehicle lanes are not under consideration for study purposes. Add 1 high-occupancy vehicle lane in both directions from Avenida Pico to San Juan Creek Rd., and reconfigure interchanges N/A N/A High-occupancy vehicle not considered; interchange realignment not applicable in FREEVAL. Figure 7.12 shows the flowchart of I-5 CSMP scenarios to be evaluated in FREEVAL- RL. This is a modification of the flowchart shown in Figure 3.8, which lists all of the scenarios tested in the I-5 CSMP microsimulation modeling (Caltrans 2012). Scenarios 3 and 4 could not be tested in FREEVAL-RL, because the improvements fall outside the study area. As in the CSMP modeling, the scenarios were tested for two model years: base year (2010) and horizon year (2020). 150
Figure 7.12. I-5 CSMP scenario to be tested in FREEVAL-RL. For the NB a.m. model, there are seven CSMP scenarios to be tested in FREEVAL-RL: 1. Base Scenario, Base demand 2. Scenario 0, Horizon demand 3. Scenario 1, Base demand, with addition of one NB on-ramp at the SR-74 interchange 4. Scenario 2, Horizon demand, with addition of one NB on-ramp at the SR-74 interchange 5. Scenario 5, based on the Scenario 2 model, with a 45-minute incident blocking the rightmost lane at NB p.m. 18.5, affecting Segment 49 from 7:00 a.m. to 7:45 a.m. 6. Scenario 6, based on the Scenario 2 model, with a 30-minute incident blocking the rightmost lane at NB p.m. 18.5, Segment 49 from 7:00 a.m. to 7:30 a.m. 7. Scenario 7, based on the Scenario 2 model, with addition of one GP lane between El Toro and Junipero Serra interchange. For the SB p.m. model, there are five CSMP scenarios to be tested in FREEVAL-RL: 1. Base Scenario, Base demand 2. Scenario 0, Horizon demand 3. Scenario 5, based on the Scenario 2 model, with a 45-minute incident blocking the rightmost lane at SB p.m. 90.5, affecting Segment 33 from 5:00 p.m. to 5:45 p.m. 4. Scenario 6, based on the Scenario 2 model, with a 30-minute incident blocking the rightmost lane at SB p.m. 18.5, affecting Segment 33 from 5:00 p.m. to 5:30 p.m. 5. Scenario 7, based on the Scenario 2 model, with addition of one GP lane between SR-55 interchange and I-5 truck bypass and between El Toro and Junipero Serra interchange. 151
Future Year Demands The study team obtained the horizon-year demands by analyzing the origin-destination (O-D) matrix for the Paramics model developed for the I-5 CSMP. Since the network in the microsimulation model is roughly linear (as illustrated in Figure 7.13), there are limited route choices, so the team was able to calculate the demand flows at all cordon points of the FREEVAL-RL model within the study areas. The I-5 Paramics model has an hourly O-D matrix and uses a 5-minute demand profile to represent the temporal distribution of demand. Thus, the team had to develop a procedure and method to calculate the 15-minute demand flow needed by FREEVAL-RL. 152
Figure 7.13. I-5 Paramics model limits. Scenario Testing Procedure The study team adopted the following procedure to test CSMP scenarios in FREEVAL-RL: ⢠Develop the seed file for the CSMP scenario based on the calibrated base model, ⢠Generate the seed file results and verify the reasonableness of the speed contour map by comparing against the corresponding I-5 Paramics model results, and ⢠Perform reliability testing for the scenario and analyze the TTI results. 153
Several parameters are needed for the reliability testing, including weather effects, incident effects, and demand patterns. For the weather effect, the study team chose simply to use FREEVAL-RL default values for the Los Angeles area. For the incident effects, the team decided not to consider them in the testing. It should be noted that there are two CSMP scenarios that involve incident management, which were modeled by adjusting the CAFs of the segment with the major incident for the affected time intervals. The major parameter for reliability testing is the demand pattern. The demand pattern in FREEVAL-RL is split into two parts. The first part covers the daily and monthly demand adjustment multipliers (DMs) based on daily and monthly variability of traffic demand for the subject facility. The second part covers the overall demand pattern. The inputs are displayed in a calendar format to show the configuration of demand patterns for the subject facility. For the first part, FREEVAL-RL provides a national default for urban and rural freeways, as shown in Table 7.5. The study team derived customized DMs based on the study area and modeling hours for the NB a.m. model (as shown in Table 7.6) and the SB p.m. model (as shown in Table 7.7) using VMT data collected from PeMS for the 2010 base year. The study team analyzed the deviations of the default DMs (as shown in Table 7.8) and customized DMs (as shown in Tables 7.9 and 7.10). The study team found that the default DMs have higher deviations or variation than the customized DMs. The study team further compared the reliability testing results using both DMs for the Base Scenario (as shown in Figure 7.14). The team found that the higher deviation in the default DMs led to higher TTIs estimated in FREEVAL-RL. These estimates were unrealistic compared to the baseline TTI measured using PeMS. As a result, the study team decided to use the customized DMs to estimate travel time reliability for all of the test scenarios. 154
Table 7.5. Default DMs for Urban and Rural Freeways Default DM Day of Week Mon Tue Wed Thu Fri M on th Jan 0.822158 0.822158 0.838936 0.864104 0.964777 Feb 0.848710 0.848710 0.866031 0.892012 0.995936 Mar 0.920502 0.920502 0.939288 0.967466 1.080181 Apr 0.975575 0.975575 0.995484 1.025349 1.144807 May 0.973608 0.973608 0.993477 1.023281 1.142499 Jun 1.021796 1.021796 1.042649 1.073929 1.199047 Jul 1.132925 1.132925 1.156046 1.190728 1.329453 Aug 1.032614 1.032614 1.053688 1.085299 1.211741 Sep 1.063101 1.063101 1.084797 1.117341 1.247516 Oct 0.995243 0.995243 1.015554 1.046021 1.167888 Nov 0.995243 0.995243 1.015554 1.046021 1.167888 Dec 0.978525 0.978525 0.998495 1.028450 1.148269 Table 7.6. Customized DMs for the Northbound I-5 a.m. Model NB a.m. DM Day of Week Mon Tue Wed Thu Fri M on th Jan 0.9434 1.0113 0.9799 0.9690 0.8783 Feb 0.9489 1.0277 1.0199 1.0113 0.9647 Mar 1.0108 1.0141 1.0034 1.0097 0.9695 Apr 1.0067 1.0058 1.0018 0.9943 0.9642 May 0.9313 1.0283 1.0415 1.0460 1.0121 Jun 1.0489 1.0505 1.0475 1.0517 1.0057 Jul 0.9273 1.0253 1.0301 1.0341 0.9867 Aug 1.0288 1.0316 1.0489 1.0394 0.9868 Sep 0.8862 1.0423 1.0217 1.0392 1.0002 Oct 0.9982 1.0206 0.9763 1.0103 0.9922 Nov 1.0212 1.0303 1.0153 0.8944 0.8938 Dec 0.9678 0.9406 0.9251 0.9552 0.8175 155
Table 7.7. Customized DMs for the Southbound I-5 p.m. Model SB p.m. DM Day of Week Mon Tue Wed Thu Fri M on th Jan 0.9288 0.9340 0.9250 0.9521 0.9394 Feb 0.9534 0.9721 0.9944 1.0122 0.9723 Mar 0.9813 0.9974 0.9774 1.0104 0.9801 Apr 0.9670 0.9725 0.9876 0.9968 0.9560 May 0.9310 1.0080 1.0037 1.0060 0.9296 Jun 1.0031 1.0124 1.0134 0.9992 0.9915 Jul 0.9447 1.0292 1.0248 1.0285 0.9836 Aug 1.0001 1.0196 1.0208 1.0164 0.9808 Sep 0.9088 1.0180 1.0257 1.0259 0.9882 Oct 0.9890 0.9680 1.0180 1.0401 1.0086 Nov 0.9976 1.0107 0.9907 0.9550 0.9589 Dec 0.9433 0.9618 0.9671 0.9839 0.9250 156
Table 7.8. Deviation of Default DMs Default DM Day of Week Mon Tue Wed Thu Fri Sat Sun M on th Jan -18% - 18% -16% -14% -4% N/A N/A Feb -15% - 15% -13% -11% 0% N/A N/A Mar -8% -8% -6% -3% 8% N/A N/A Apr -2% -2% 0% 3% 14% N/A N/A May -3% -3% -1% 2% 14% N/A N/A Jun 2% 2% 4% 7% 20% N/A N/A Jul 13% 13% 16% 19% 33% N/A N/A Aug 3% 3% 5% 9% 21% N/A N/A Sep 6% 6% 8% 12% 25% N/A N/A Oct 0% 0% 2% 5% 17% N/A N/A Nov 0% 0% 2% 5% 17% N/A N/A Dec -2% -2% 0% 3% 15% N/A N/A Total 74% 74% 74% 91% 188% N/A N/A Table 7.9. Deviation of Customized Northbound I-5 a.m. DMs NB DM Day of Week Mon Tue Wed Thu Fri Sat Sun M on th Jan -6% 1% -2% -3% -12% N/A N/A Feb -5% 3% 2% 1% -4% N/A N/A Mar 1% 1% 0% 1% -3% N/A N/A Apr 1% 1% 0% -1% -4% N/A N/A May -7% 3% 4% 5% 1% N/A N/A Jun 5% 5% 5% 5% 1% N/A N/A Jul -7% 3% 3% 3% -1% N/A N/A Aug 3% 3% 5% 4% -1% N/A N/A Sep -11% 4% 2% 4% 0% N/A N/A Oct 0% 2% -2% 1% -1% N/A N/A Nov 2% 3% 2% -11% -11% N/A N/A Dec -3% -6% -7% -4% -18% N/A N/A Total 51% 35% 35% 43% 56% N/A N/A 157
Table 7.10. Deviation of Customized Southbound I-5 p.m. DMs SB DM Day of Week Mon Tue Wed Thu Fri Sat Sun M on th Jan -7% -7% -7% -5% -6% N/A N/A Feb -5% -3% -1% 1% -3% N/A N/A Mar -2% 0% -2% 1% -2% N/A N/A Apr -3% -3% -1% 0% -4% N/A N/A May -7% 1% 0% 1% -7% N/A N/A Jun 0% 1% 1% 0% -1% N/A N/A Jul -6% 3% 2% 3% -2% N/A N/A Aug 0% 2% 2% 2% -2% N/A N/A Sep -9% 2% 3% 3% -1% N/A N/A Oct -1% -3% 2% 4% 1% N/A N/A Nov 0% 1% -1% -4% -4% N/A N/A Dec -6% -4% -3% -2% -7% N/A N/A Total 46% 29% 26% 25% 40% N/A N/A Base Scenario Scenario 0 158
Figure 7.14. Comparison of TTI results for I-5 from default DMs and customized DMs. Scenario Testing Results and Comparison As shown in the scenario testing flow chart (Figure 7.12), the study team tested the scenarios like those in the I-5 CSMP. These scenarios included two different forecast years: a base year of 2010 and a horizon year of 2020. The base year (2010) demands were used to model the Base Scenario (i.e., no-build in the base year) and Scenario 1. The horizon-year (2020) demands were used to model Scenarios 0 (i.e., no-build in the horizon year), 2, 5, 6, and 7. The next several 159
sections show how the different CSMP scenarios compare to the corresponding no-build scenarios modeled in FREEVAL-RL and measured in PeMS (for the base year). The study team shows speed contours and TTI estimates for the 50th, 80th, and 95th percentile. Base Scenario and Scenario 1: NB a.m. model Figure 7.15 shows the speed contours for the Base Scenario and Scenario 1 (i.e., the first set of investments for base year demands) from the northbound a.m. model. The figure compares the congestion results estimated in FREEVAL-RL to those estimated for the I-5 CSMP using the Paramics microsimulation model. Note that these are static analyses. However, if the static analyses look reasonable, then the dynamic scenario estimation in FREEVAL-RL may produce reasonable reliability estimates. FREEVAL-RL Base Scenario Paramics Base Scenario FREEVAL-RL Scenario 1 Paramics Scenario 1 Figure 7.15. Speed contours of NB I-5 a.m. model: Base Scenario and Scenario 1. In Scenario 1, the improvement project involves building a new on-ramp at the SR-74 interchange (at approximately p.m. 82) to improve access to the freeway. As shown in Figure 160
7.15, Scenario 1 performs very similarly to the Base Scenario. In addition, the FREEVAL-RL model results match the Paramics modeling fairly closely. Figure 7.16 shows the 50th, 80th, and 95th percentile TTI for the Base Scenario and Scenario 1. As seen in the charts, the new on-ramps at the SR-74 interchange do not appear to improve 50th, 80th, or 95th percentile travel times, so reliability is largely unimproved. The figure also shows the TTI measured in PeMS. The real-world TTI is much lower than those estimated in FREEVAL-RL. Figure 7.16. TTI results of the NB I-5 a.m. model: Base Scenario and Scenario 1. 161
No-Build Horizon Scenario (Scenario 0), Scenario 2, and Scenario 7: NB a.m. model Figure 7.17 shows similar results for the horizon-year scenarios using the northbound a.m. model. Scenario 0 is the no-build, Scenario 2 corresponds to Scenario 1 (new on-ramps at SR-74 interchange), and Scenario 7 (add a single GP lane between El Toro and the Junipero Serra interchange). Scenarios 0 and 2 show very little change, but Scenario 7 improves traffic conditions. These results cover the mainline only, since the high-occupancy vehicle lanes were ignored in the FREEVAL-RL modeling. In addition, the FREEVAL-RL results for Scenario 7 are similar to the results for the Paramics microsimulation modeling. Note that the Paramics model covers a larger area than the FREEVAL-RL model, and thus its speed contour maps for Scenarios 0 and 2 shows a queue propagated backward from downstream. The FREEVAL-RL speed contours look more congested and have higher shockwave speed than those of Paramics. A possible reason is that the traffic flow characteristics of FREEVAL-RL are not able to reflect the capacity drop observed in the real world. Thus, the study team had to calibrate the model to have a relatively lower capacity in order to replicate the congestion period. 162
FREEVAL-RL Scenario 0 Paramics Scenario 0 FREEVAL-RL Scenario 2 Paramics Scenario 2 FREEVAL-RL Scenario 7 Paramics Scenario 7 Figure 7.17. Speed contours of NB I-5 a.m. model: Scenario 0, Scenario 2, and Scenario 7. Figure 7.18 shows 50th, 80th, and 95th percentile TTI results for Scenarios 0, 2, and 7. These results show that Scenario 7 results in greater travel time reliability than do Scenarios 0 and 2. In comparing Scenarios 0 and 2, Scenario 2 TTIs are slightly higher (i.e., travel time reliability is slightly worse). This may occur because the improvement allows vehicles to enter the freeway mainline from SR-74 more easily and causes the mainline to be less reliable. 163
Figure 7.18. TTI results of NB I-5 a.m.: Scenario 0, Scenario 2, and Scenario 7. 164
Scenarios 5 and 6: NB a.m. model Scenarios 5 and 6 were used to test the benefits from incident management in the I-5 CSMP (Caltrans 2012). The study team implemented these two scenarios by decreasing CAFs for the segment with incident and affected time intervals. This means that the seed files for the two scenarios have lower capacities for some time intervals. The study team applied an incident that causes one lane closure at Segment 49 (at the El Toro interchange) from 7:00 a.m. to 7:45 a.m. (corresponding to an incident duration of 45 minutes) in Scenario 5 and from 7:00 a.m. to 7:30 a.m. (corresponding to an incident duration of 30 minutes) in Scenario 6. Figure 7.19 clearly shows that congestion in Scenario 5 lasts longer than in Scenario 6. Accordingly, a significant difference can be observed in the TTI results of Scenarios 5 and 6 (as shown in Figure 7.20). FREEVAL-RL Scenario 5 Paramics Scenario 5 FREEVAL-RL Scenario 6 Paramics Scenario 6 Figure 7.19. Speed contours of NB I-5 a.m. model: Scenario 5 and Scenario 6. 165
Figure 7.20. TTI Results of NB I-5 a.m. model: Scenario 5 and Scenario 6. Base Scenario, No-Build Horizon (Scenario 0), and Scenario 7: SB p.m. Model Figure 7.21 shows the speed contour maps from the FREEVAL-RL seed file results and the I-5 Paramics model for the Base Scenario, Scenario 0, and Scenario 7. The speed contour maps for these three scenarios (especially Scenario 0) are less congested, which can be seen from the comparison against the Paramics microsimulation results shown on the right side of Figure 7.21. The reason is that FREEVAL-RL has limitations on model freeway-to-freeway connector and 166
ramp merge models. For this case, southbound has a major freeway-to-freeway connector (postmile 90) located just upstream of the bottleneck area. The connector has high flow, about 4,000 to 5,000 vehicles per hour. FREEVAL-RL cannot serve all demands from the three-lane freeway-to-freeway connector, which has been modeled as two on-ramps, based on the suggestion from the FREEVAL-RL developer. A further analysis shows that the ramp merge model does not allow the vehicles on the ramp to merge to the freeway mainline if the mainline is congested and the on-ramp flow is high. Also, the improvement applied in Scenario 7 involves the addition of one GP lane to the portions of freeway mainline between the SR-55 interchange and I-5 truck bypass and between the El Toro and Junipero Serra interchanges. The scenario is expected to increase the mainline capacity significantly and provide congestion reduction benefits. However, the speed contour map for Scenario 7 is only slightly better than that of Scenario 0. Scenario 0 shows less congestion than in the Paramics model. 167
FREEVAL-RL Base Scenario Paramics Base Scenario FREEVAL-RL Scenario 0 Paramics Scenario 0 FREEVAL-RL Scenario 7 Paramics Scenario 7 Figure 7.21. Speed contours of SB I-5 p.m. model: Base Scenario, Scenario 0, and Scenario 7. 168
The TTI results for these three CSMP scenarios are shown in Figure 7.22. For the Base Scenario, the 80th percentile TTIs estimated by FREEVAL are similar to the real-world PeMS TTIs, although the study team felt the SB p.m. FREEVAL-RL seed file was not well-calibrated. The TTI values for Scenarios 0 and 7 were slightly higher than the Base Scenario. However, the amount of increase is lower than expected because these seed file results were not congested enough to show benefits. Figure 7.22. TTI Results of SB I-5 p.m. model: Base Scenario, Scenario 0, and Scenario 7. 169
Scenarios 5 and 6: SB p.m. Model The study team ran Scenarios 5 and 6 to test benefits from incident management during the p.m. period. The scenarios were modeled by decreasing CAFs for the segment with an incident and the affected time intervals. This is the same approach as used for the CSMP modeling in Paramics. The study team applied an incident that causes one lane closure at Segment 33 (located at the El Toro interchange) from 5:00 p.m. to 5:45 p.m. (corresponding to an incident duration of 45 minutes) in Scenario 5 and from 5:00 p.m. to 5:30 p.m. (corresponding to an incident duration of 30 minutes) in Scenario 6. As observed in Figure 7.23, the improvement provided incident management benefits. Travel time reliability also improved, as shown by the TTI results in Figure 7.24. However, the congestion benefits shown in FREEVAL-RL are significantly less than those in the Paramics microsimulations, because of the failure to serve all demands from the freeway-to-freeway connector, as previously discussed. FREEVAL-RL Scenario 5 Paramics Scenario 5 FREEVAL-RL Scenario 6 Paramics Scenario 6 Figure 7.23. Speed Contours of SB I-5 p.m. model: Scenario 5 and Scenario 6. 170
Figure 7.24. TTI Results of SB I-5 p.m. model: Scenario 5 and Scenario 6. Tables 7.11 and 7.12 show the average hourly TTI results for all CSMP scenarios from the NB a.m. and SB p.m. models. 171
Table 7.11. TTI Summary for Northbound I-5 a.m. Model NB/AM Base Scenario 0 Scenario 1 Scenario 2 Scenario 5 Scenario 6 Scenario 7 50th Pct 6:00 1.21 1.75 1.21 1.76 1.78 1.77 1.59 7:00 1.49 3.47 1.49 3.73 3.79 3.77 2.89 8:00 1.43 3.31 1.39 3.53 3.57 3.56 2.76 9:00 1.12 2.28 1.12 2.56 2.59 2.58 2.26 80th Pct 6:00 1.37 2.14 1.37 2.22 2.24 2.24 1.91 7:00 1.70 4.13 1.68 4.36 4.53 4.47 3.22 8:00 1.67 3.81 1.66 4.13 4.14 4.14 3.09 9:00 1.28 2.75 1.28 3.02 3.11 3.06 2.42 95th Pct 6:00 1.44 2.31 1.43 2.38 2.43 2.43 1.21 7:00 2.15 4.74 2.06 5.08 5.18 5.13 3.70 8:00 1.96 4.08 2.00 4.41 4.41 4.41 3.23 9:00 1.61 3.23 1.59 3.54 3.69 3.63 2.76 Table 7.12. TTI Summary for Southbound I-5 p.m. Model SB/p.m. Base Scenario 0 Scenario 5 Scenario 6 Scenario 7 50th Pct 15:00 1.11 1.32 1.32 1.32 1.17 16:00 1.22 1.34 1.34 1.34 1.24 17:00 1.28 1.39 1.97 1.75 1.30 18:00 1.15 1.28 1.44 1.40 1.16 19:00 1.07 1.10 1.10 1.10 1.05 80th Pct 15:00 1.31 1.50 1.50 1.50 1.45 16:00 1.28 1.46 1.46 1.46 1.37 17:00 1.34 1.42 2.04 1.81 1.37 18:00 1.27 1.36 1.55 1.52 1.24 19:00 1.10 1.15 1.19 1.18 1.06 95th Pct 15:00 1.35 1.54 1.54 1.54 1.59 16:00 1.43 1.58 1.58 1.58 1.80 17:00 1.40 1.46 2.13 1.90 1.58 18:00 1.36 1.46 1.73 1.63 1.34 19:00 1.14 1.20 1.29 1.25 1.10 172
Concluding Remarks The study team has successfully demonstrated the potential of the FREEVAL-RL tool. However, the tool needs to be further improved. The most important aspects of improvement include the enhancement of its merge model, addition of the ability to model HOV lanes and on-ramps or freeway connectors with more than two lanes, and software bug fixes (such as the inability to take the calibrated capacity adjustment factor in the scenario testing process). 173
