An Assessment of Congestion in the Kansas City Region using the MARC Travel Demand Model

Transcription

1 An Assessment of Congestion in the Kansas City Region using the MARC Travel Demand Model The Congestion Management Process Federal Regulations state that all metropolitan planning organizations must carry out a Congestion Management Process or CMP. The metropolitan planning organization Mid-America Regional Council (MARC) manages and caries out the CMP for the Kansas City region. The Congestion Management Process was developed to support effective regional decision making in transportation planning by providing up-to-date information, analysis on the transportation system performance and strategies to manage traffic congestion. More specifically the CMP must identify the location, duration, extent, causes of current and future congestion, and evaluate the effectiveness of implemented strategies. The Federal Highway Administration guides the various regional MPOs management of the CMP with an eight step outline of a suggested process to follow. These eight steps include: 1. Develop Regional Objectives for Congestion management 2. Define CMP network 3. Develop multimodal performance measures 4. Collect data/monitor system performance 5. Analyze congestion problems and needs 6. Identify and assess strategies 7. Program and implement strategies 8. Evaluate strategy effectiveness These eight steps are meant to be cyclical in order to facilitate a continuous process that will evolve as technology, strategies and regions evolve. MARC has recently updated steps five and six, analyzing congestions problems and needs, and identifying and assessing strategies for the Congestion Management Process. The purpose of this analysis is to improve MARC s current understanding of the traffic congestion conditions the Kansas City region faces, as well as the future conditions. This analysis will also provide a base from which MARC may better track and analysis transportation improvement projects and their effect on the regional congestion. By tracking the projects effects and projecting a projects future effects on congestion will provide information that will assist in decision making for future transportation projects. Regional Congestion Analysis Regional Travel Demand Model Overview To support long range planning of the regional transportation and to address the federal guidelines for the CMP, MARC maintains a regional travel demand model. MARC devotes a great amount of resources to the development, maintenance and accuracy to the model. The analysis from the model addresses steps five and six of the federal guidelines. The model also assists in the planning and development of the Transportation Improvement Program or TIP, and the Long-Range Transportation Plan or LRPT. 1

2 MARC uses the EMME software for the travel demand model. The model looks at seven counties in the Kansas City region, Johnson, Leavenworth, and Wyandotte in Kansas and Cass, Clay, Jackson and Platte in Missouri. The model uses minor collector streets to interstate highways, as well as some local streets in its analysis network. Using population and employment projections in the Kansas City metropolitan area, the model generates trips between origins and destinations, then distributes them onto Travel Analysis Zones and by mode of travel (transit, carpool, individuals in vehicles, etc.), then assigns trips to the model network for one hour time segments for twenty-four hours. The model works as a daily demand model, which is meant to look at population demographics and assign trips to the network in relation to the regional conditions and population s travel behavior. It does not function as an operational model that looks at smaller scale driver behavior, traffic signal timing or queuing. The travel demand model focuses on the regional congestion, but cannot attain enough detail to look at causes or micro level traffic operations. The outputs that the MARC model includes are travel time, delay, volumes, and volume-capacity ratio for each road segment on the model road network. These model values are for one hour time spans for twenty-four hours. Travel time is the real time it takes to arrive at the destination. Delay is the free flowing travel time subtracted from the real travel time. Volume is the amount of cars that pass through a segment for an hour and volume-capacity ratio or V/C is the volume divided by the assigned carrying capacity of the segment. These can be aggregated by segment, by hour or for the whole twenty-four hours for the whole network. Analysis Methodology For the purpose of this analysis, the results of three different forecast scenarios were evaluated: 2010 baseline, 2040 build, and 2040 no-build. Each forecast scenario is unique in terms of the network (supply) and land use (demand) assumptions, which are briefly described in Table 1. Table 1 Model Assumptions Scenario Population/Employment Network 2010 Baseline 2010 estimates Existing (2010) 2040 Build 2040 projections Existing TIP projects + financially-constrained LRTP projects 2040 No-Build 2040 projections Existing TIP projects For each of these scenarios maps and figures were created to help display the location, duration and extent of congestion. The location maps show the road segments that reach over capacity according to the model at any point during the day. If any segment had a V/C>=1 or volume-capacity ratio of 1 or greater for any hour the segment is displayed as red and are labeled as congested. The extent of congestion was analyzed for each scenario by summarizing the total number of centerline miles that experienced a V/C>=1 for one or more hours. Another analysis preformed on the model data was the duration of the congestion by mapping the number of hours that segments have a V/C>=1. If a segment 2

3 experienced five or more hours with a V/C>=1, it was labeled as severe congestion. Segments with three to four hours with a V/C>=1 were moderate and segments with two hours or less with a V/C>=1 were normal or no congestion. This shows which segments of the network are congested for the longest amount of time. Looking at the different maps for the three different scenarios will show the magnitude of growth expected from the 2010 scenario to the 2040 scenarios. The regional congestion analysis focused only on the Congestion Management Network (CMN). The CMN, as defined in the MARC CMP Policy, includes all National Highway System (NHS), routes with significant transit service, and road segments longer than 2 miles with daily traffic volumes (AADT) greater than 25,000. These selected road segments are considered most significant in the congestion of the region. Comparing these three scenarios a system wide evaluation was made Baseline Scenario The following map (figure 2) displays the 2010 scenario that used a volume-capacity ratio to identify the congested segments. The map shows portions of most all interstates and major highways leading to the Downtown area reaching over-capacity at least once within 24 hours. The length that a facility experiences a V/C>=1 is typically short and intermittent, but not many facilities experience constant congestion. In figure 1 only 10% of the total centerline miles on the CMN reach over-capacity at some point in the 24 hour period.. This still leaves 90% of centerline miles under capacity, which means 90% of roadways do not experience congestion. Centerline miles are the length of the road segments in miles, but centerline miles do not account for the varying amount of lanes a facility may have. Centerline provides an idea of the facilities as a whole. Figure 3 displays the 2010 baseline scenario and shows that most facilities do not reach over-capacity for more than 2 hours. There are only a small number of facilities that are over-capacity for more than 4 hours. These areas are for example on places such as US 69 and Interstate 29. Figure 1 3

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6 2040 No-Build Scenario The 2040 no-build scenario displays the forecasted travel demands for 2040 with the existing road conditions and the projects on the TIP. This produces a picture of how much congestion there could be if only TIP projects are completed. Figure 5 is the 2040 no-build scenario displaying the location of the segments with a V/C>=1 for at least 1 hour over a 24-hour period. The 2040 no-build scenario shows significantly more congestion for greater lengths along the various facilities. These include interstates as before, but also connecting highways and arterial roads that feed into the interstates. There is also an increase in intra-suburban travel that is not solely directed to the downtown area. This could be caused by the increase in population as well as an increase in suburban employment locations. The congestion last longer along corridors and facilities meaning traffic will experience more constant congestion, instead of occurring intermittently along routes. The percent of the congested centerline miles is 25% in the 2040 no-build scenario, shown in figure 4. There is a larger amount of congestion with an increase of 15% in segments with a V/C>=1. Now only 75% of all centerline miles on the CMN are not over-capacity at some point during the twenty-four hour period. This is the worst-case scenario, but when improvement projects are inputted into the model for the 2040 build scenario the congestion is partially alleviated. The 2040 no-build scenario displays a larger number of segments that are over-capacity 5 hours or more, shown in figure 6. These include Interstate 70 on the East side of Kansas City, Interstate 29 north of Kansas City and parts of US 69, Interstate 35 and Kansas Highway 10. Moreover there are a large number of segments experiencing three to four hours of congestion, which is spreading the congestion and the severity of the congestion further out into the suburban regions where congestion did not pervade in the 2010 scenario. Figure 4 6

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9 2040 Build Scenario The 2040 Build scenario shows the forecasted travel demand with the TIP projects, and all of the financially constrained projects on the Long Range Transportation Plan (LRTP) or Transportation Outlook Figure 8 shows the segments that reach over-capacity or are congested in the 2040 build scenario. This map shows the areas that are absent of congestion due to roadway projects such as the US 69 corridor. K-7 has also seen reduction in congestion. There is still more congestion in the 2040 build scenario than the 2010 baseline scenario, but this could show areas that are being neglected that possibly should be revisited. This model makes it possible to see how future projects will or will not affect congestion in the future. Figure 7 shows the percentage of the segments that are congested in the 2040 build scenario. The model shows that 19% of the CMN will be congested or reach over-capacity at some point during the 24 hour period. This is a 6% reduction from the 2040 no-build scenario and only a 9% increase from the 2010 baseline scenario. Although there is almost double the number of congested roadways in 30 years, the comparison to the 2040 no-build scenario shows the difference the roadway and transportation projects makes. Figure 9 shows the duration of congestion for the 2040 build scenario. There are improvements in congestion around Kansas highway 10, Interstate 35 and US 69 highway when compared to the 2040 nobuild scenario. The congestion in the 2010 scenario could be caused by the road projects in those areas. Some areas still are experiencing the same amount of congestion as in the 2040 no-build scenario. Moderate congestion is still wide spread across the region, so although some facilities were alleviated of congestion, the population increase will worsen the congestion for many other surrounding areas. Figure 7 9

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12 The MARC model also allows us to view in what hours the segments reached over-capacity. This illustrates the commuting peaks of the system and when it is most severely congested. In figure 10 the three scenarios are shown in comparison to view the duration and number of miles effected by congestion. In the morning, the majority of the segments with a V/C>=1 peak is concentrated into two hours. This means more people were traveling at one time increasing the severity of the congestion for those times. In the evening, the peak is spread between three hours or more making the severity not as great but the time span of congestion longer. Other than work trips, the evening congestion could also include errands and other daily trips. The MARC model accounts for all types of trips taken, not only commuting. Figure 10 12

13 Using the analysis from the model a table of congested facilities was created. Table 2 lists the parts of a facility that are a quarter of a mile or longer in length that were severely congested in one or more of the three scenarios. The table also list the financially constrained projects in Transportation Outlook 2040 the LRTP that correspond to the severely congested facilities. These projects are strategies in the LRTP to address congestion. The list helps show a reduction in forecasted congestion for many of those facilities that were benefited from a congestion management project from the LRTP. There is a facility that is congested in the 2040 build scenario and not congested in the 2040 no-build scenario, showing an increase in congestion. This could be due to the travel pattern changes in the model created from the new projects that altered the way the model is loading trips onto the network. This needs to be reviewed more to know the particular cause. 13

14 Analysis Of Future Congestion CONGESTED NAME FROM TO NO-BUILD BUILD 1. US69 HWY* W 87 ST COLLEGE BLVD x X 2. K10 HWY WOODLAND RD I435 X 694 Johnson County Gateway Roadway Capacity Project 716 K-10 - Noria Rd in Lawrence to I-435 in Lenexa Roadway Capacity 3. I 35* I435 W 119 ST X 538 BRT-I-35 Bus on shoulder Transit Non-Capacity 4. E I435* I 35 QUIVIRA RD x X X 593 I US69 TO QUIVIRA Roadway Capacity 5. E I70* JACKSON AVE Curve E I436 x X X 227 I-70 at I Interchange Roadway Capacity Improvements 6. E 31 ST** PROSPECT AVE JACKSON AVE x X X 7. I670* I35 INTERCHANGE US71/I70 INTERCHANGE 8. I70* I29/35 INTERCHANGE I670/US71 INTERCHANGE 9. N I35/29, INDEPENDENCE AVE ARMOUR RD x X X PASEO BRDG* 10. I 35* SOUTHWEST TRFY WEST PENNWAY ST X X 192 I-70 -Tracy to Topping (Downtown to I-435 Corridor Improvements) x X X 194 Downtown Loop Improvements (I-35, I-670 and US71) PHASE 1 x X X 194 Downtown Loop Improvements (I-35, I-670 and US71) PHASE N I29* OAK TRFY NE DAVIDSON RD x X X 150 I-29 - MO 210 (Armour Rd) to US 169 (Corridor Improvements) 12. BLUE PKWY ELMWOOD AVE HARDESTY AVE x X X 527 Blue Parkway - Elmwood to Eastwood 13. SHAWNEE MISSION PKWY** METCALF AVE LAMAR AVE X 581 BRT- EAST/WEST Gateway Enhanced Transit Service 14. I35* LAMAR AVE METCALF AVE X Roadway, Bike- Ped. Roadway, Bike- Ped. Roadway, Bike- Ped. Roadway, Bike- Ped. Capacity Non-Capacity Non-Capacity Non-Capacity Roadway Capacity Transit N/A 538 BRT-I-35 Bus on shoulder Transit Non-Capacity 422 I-35 and Lamar Ave Interchange Roadway Capacity 15. US69 HWY BLUE VALLEY PKWY W 135 ST X 706 US th St to I-435 Roadway Capacity 16. NE I70 NW 7 HWY NE ADAMS DAIRY PKWY X 182 I-70 - West of Little Blue PKWY to Lafayette County HWY W KANSAS ST LIBERTY DR X X (Corridor Improvements) Phase NE BARRY RD N CHURCH RD N I35 X X ID PROJECT NAME PROJECT TYPE Roadway, Bike- Ped. CAPACITY Capacity 19. E I70* PROSPECT AVE E TRUMAN RD X X 192 I-70-Tracy to Topping (Downtown to I-435 Corridor Improvements) 20. S M 291 HWY E GUDGELL RD E HIDDEN VALLEY RD X Roadway, Bike- Ped. Capacity *Facility is part of the KC Scout Advanced Traffic Management System (ATMS) **Facility is part of the Operation Green Light traffic signal coordination system 14

15 The Model is also capable of looking at a variety of other performance measure to help understand the regional congestion. Travel Time index, aggregate delay and peak period analysis can all be examined with the model to identify different characteristics of congestion. The model is a useful tool to help identify the congested areas and help determine the type of projects that are successful when attempting to alleviate congestion. There are still other data sources, such as real volume and travel time counts, that are necessary to complete the full view of the congestion in the regional area, but the model is useful when planning for long range transportation goals and future outcomes. 15

16 Glossary AADT: Average Annual Daily Traffic CMN: Congestion Management Network CMP: Congestion Management Process EMME: Software used to create travel demand modeling MARC: Mid-America Regional Council NHS: National Highway System TAZ: Travel Analysis Zone TIP: Transportation Improvement Program V/C: Volume-capacity Ratio 16