2030 Higher Household Growth in Region Scenario: Travel Model Results and Accessibility Analysis

1. Item #3 2030 Higher Household Growth in Region Scenario:Travel Model Results and Accessibility Analysis Presentation to the Joint Technical Working Group of the Regional Mobility and Accessibility Study April 15, 2005 Mark Moran Metropolitan Washington Council of Governments 2005-04-15_hhg_scenar_modelres.ppt

2. 2030 Higher Household Growth in Region (HHG) Scenario:What is it? • Land use: 2030 Higher Household Growth • Network: 2030 Transit-oriented development (TOD) Presentation to the JTWG of the RMAS

3. 2030 Higher Household Growth in Region Land UseColor Map • Based on Round 6.4 land activity forecasts • Assumes 215,000 more households in the Washington region than in Round 6.4 forecast for 2030. Most are located in regional activity centers / clusters • 100,000 come from beyond the external cordon • 115,000 come from jurisdictions beyond the Washington region, but within the external cordon • Reduces growth in commuter and other vehicle trips from areas outside the region • Assumed additional 215,000 households represents 60% of 2010-to-2030 growth, but only 9.0% of the total 2030 HHs) Presentation to the JTWG of the RMAS

4. 2030 Higher Household Growth in Region Land Use:Black & White Map • Based on Round 6.4 land activity forecasts • Assumes 215,000 more households in the Washington region than in Round 6.4 forecast for 2030. Most are located in regional activity centers / clusters • 100,000 come from beyond the external cordon • 115,000 come from jurisdictions beyond the Washington region, but within the external cordon • Reduces growth in commuter and other vehicle trips from areas outside the region • Assumed additional 215,000 households represents 60% of 2010-to-2030 growth, but only 9.0% of the total 2030 HHs) Presentation to the JTWG of the RMAS

5. Transit-oriented development network Presentation to the JTWG of the RMAS

6. Transportation network: Fixed guideway improvements • Heavy rail (Metrorail, commuter rail) • Light rail (LRT) • Bus rapid transit (BRT) • Transitway (can be BRT or LRT) Presentation to the JTWG of the RMAS

7. Transportation network: 2005 Presentation to the JTWG of the RMAS

8. Transportation network: 2030 CLRP Presentation to the JTWG of the RMAS

9. Transportation network: 2030 CLRP+ • CLRP+ assumes no capital improvements, only enhancements to transit service • Most significant service enhancement: the lifting of the 2005 transit constraint through the DC core • CLRP+ is the baseline network Presentation to the JTWG of the RMAS

10. Transportation network: TOD, Map 1 of 2 Presentation to the JTWG of the RMAS

11. Transportation network: TOD, Map 2 of 2 Presentation to the JTWG of the RMAS

12. Map legend: Fixed guideway extensions in TOD network Presentation to the JTWG of the RMAS

13. 2030 CLRP+ vs. TOD network:Fixed guideway miles in the HHG scenario • Fixed guideway miles have increased from 412 to 691 miles (67%), but most of the increase is in the transitway category, which includes BRT/LRT lines that may operate in mixed traffic, separate right-of-way, or a combination of the two. • Metrorail miles increase by 23% and commuter rail miles by 12%. Source: rail_link_miles2.xls, staprotp.rpt Presentation to the JTWG of the RMAS

14. HHG scenario: Model results • Compared to the 2030 CLRP+, the 2030 HHG scenario results in 219,000 more transit trips per day (16% increase). • 165,000 (75%) due to land use effect • 54,000 (25%) due to network (TOD) effect • (TOD scenario was 8% increase or 109,000 more transit trips) • Regional transit mode share goes from 5.7% to 6.2% • This is the 2nd largest regional mode share for transit of the scenarios tested (the largest was 6.3% for the 2030 TOD scenario) • Home-based work (HBW) transit mode share goes from 20.5% to 22.2% • This is the highest transit mode share for work trips out of all the scenarios tested (2030 TOD was close with 22.1% transit) Presentation to the JTWG of the RMAS

15. HHG scenario: Model results, 2 • VMT drops by about 1.3% (from 149.8 million to 147.8 million vehicle miles of travel). This is impressive, given the fact that motorized person trips went up by 6.8% (Generally, when motorized person trips go up, VMT goes up). • HBW walk and bike trips increased 17.8%, from 253,000 to 298,000 • Carpool commuters: There is increase of 37,000 daily trips (5.8%) • AM congestion: the number of AM lane miles with a volume-to-capacity ratio > 1.0 drops by 6.4% (from 2,560 to 2,400 miles) Presentation to the JTWG of the RMAS

16. HHG scenario: Model results, 2 Presentation to the JTWG of the RMAS

17. Accessibility Analysis 2030 Higher Household Growth in Region Scenario

18. Accessibility analysis overview • Accessibility to • Jobs or households • Via • AM transit, walk-access to transit • AM transit, best of walk-access or drive-access to transit • AM highway network • Threshold • 45 minutes travel time • Base scenario • 2030 CLRP+ network with Round 6.4 land use • Alternative scenario • 2030 Transit-Oriented Development network with Higher Household Growth in Region land use Presentation to the JTWG of the RMAS

19. Change in Accessibility to Jobsvia AM Transit, Walk AccessLegend scale: Large • Compared to the CLRP+, the HHG scenario results in moderate gains in accessibility to jobs. • In the HHG scenario, only HHs are moved (not jobs). Thus, this map shows increases in accessibility due only to the TOD network improvements. Gains are clustered around the transit improvements. Presentation to the JTWG of the RMAS

20. Change in Accessibility to Jobsvia AM Transit, Walk AccessLegend scale: Small • Same as previous map, but legend scale is “small” to show more detail concerning accessibility changes. • As was the case on the previous map, this map shows increases in accessibility due only to the TOD network improvements. There is no land use effect, since the measure is “acc. to jobs.” Presentation to the JTWG of the RMAS

21. Change in Accessibility to Householdsvia AM Transit, Walk AccessLegend scale: Large • Compared to the CLRP+, the HHG scenario results in significant gains in accessibility to HHs. • This map shows both the land use effect (moving HHs in) and the network effect (TOD network). The increases in accessibility are concentrated in the areas where either HHs were added, TOD network improvements were made, or both. Presentation to the JTWG of the RMAS

22. Change in Accessibility to Householdsvia AM Transit, Walk AccessLegend scale: Small • Same as previous map, but legend scale is “small” to show more detail concerning accessibility changes. • The increases in accessibility are concentrated in the areas where either HHs were added, TOD network improvements were made, or both. Presentation to the JTWG of the RMAS

23. Change in Accessibility to Jobsvia AM Transit, Best of Walk or Drive AccessLegend scale: Large • Compared to the CLRP+, the HHG scenario results in moderate gains in accessibility to jobs. • In the HHG scenario, only HHs are moved (not jobs). Thus, this map shows increases in accessibility due only to the TOD network improvements. Gains are clustered around the transit improvements. • One area shows a moderate loss in accessibility. This is an area where the drive-access transit path is dominant and it is likely that the added development around transit has slowed auto travel slightly (including drive-access to transit). Presentation to the JTWG of the RMAS

24. Change in Accessibility to Householdsvia AM Transit, Best of Walk or Drive AccessLegend scale: Large • Compared to the CLRP+, the HHG scenario results in significant gains in accessibility to jobs. • This map shows both the land use effect (moving HHs in) and the network effect (TOD network). The increases in accessibility are concentrated in the areas where either HHs were added, TOD network improvements were made, or both. Presentation to the JTWG of the RMAS

25. Change in Accessibility to Jobsvia AM Highway SpeedLegend scale: Large • Since there was no job movement as part of this scenario, this map shows the effects of the land use change only. • Compared to the CLRP+, the HHG scenario results in both moderate gains and moderate losses in accessibility to jobs, via the AM highway network. • Both the gains and the losses are due to changes in congestion, which affects travel times. • There were moderate gains in accessibility in Montgomery and Prince George’s counties, due to fewer long-distance commuting trips from Howard & Anne Arundel counties. • There were moderate losses in accessibility in Prince George’s County (inside the Beltway) and S.E. DC, due to the added households in these areas, which resulted in increased congestion and lower travel speeds. • There were moderate losses in accessibility via the AM highway network in other scattered areas for the same reason cited above. Presentation to the JTWG of the RMAS

26. Change in Accessibility to Householdsvia AM Highway SpeedLegend scale: Large • This map shows the effects of both the land use change and the network change, since the HHG scenario has changes in both these entities. • Compared to the CLRP+, the HHG scenario results in moderate gains in accessibility to HHs, via the AM highway network, throughout the region. • The gains are predominantly found in the jurisdictions that were the recipients of the added HHs • No areas showed losses in accessibility to HHs Presentation to the JTWG of the RMAS

27. Findings/Summary • HHG scenario • TOD network • Added 215,000 HHs (9% of total 2030 HHs) • Reduced external vehicle trips by corresponding amount • Results in 16% increase in transit trips (+219,000 trips) • 2030 TOD scenario: 8% increase (+109,000 trips) • Regional transit mode share increased to 6.2% (only the 2030 TOD scenario produced a higher number, 6.3%) • Home-based work (HBW) transit mode share increased to 22.2% (the highest of all scenarios tested to date) • Despite a 6.8% increase in motorized person trips, VMT dropped by 1.3% Presentation to the JTWG of the RMAS

28. Findings/Summary • Changes in accessibility were logical and consistent • Accessibility to jobs via AM transit: • Increases were concentrated around transit improvements • Accessibility to HHs via AM transit: • Increases were concentrated around areas with transit improvements, added HHs, or both • Accessibility to jobs via AM highway: • Increases in areas where road congestion improved (Montgomery & PG counties, due to fewer long-distance commuting trips from Howard & Anne Arundel counties) • Decreases in areas where road congestion worsened (S.E. DC and PG Co. inside the Beltway, which had large increases in HHs) • Accessibility to HHs via AM highway: • Moderate gains throughout much of the COG planning area. Presentation to the JTWG of the RMAS

29. Acknowledgments • Program Manager: Bob Griffiths • Travel model development and overview: Ron Milone and Jim Hogan • Network development: Bob Snead, John Bethea, Wanda Hamlin, Joe Davis, Bill Bacon • Mapping and technical support: Meseret Seifu, Don McAuslan • Travel modeling: Mark Moran Presentation to the JTWG of the RMAS

30. Thank you Questions?

31. TPB modeled area Presentation to the JTWG of the RMAS

32. Four-step model: Overview • Trip generation • Predict the no. of trip ends generated in each zone • Trip distribution • Predict where trips are going, i.e., connecting trip ends into trips • Mode choice • Predict the share of trips made by each travel mode • Trip assignment • Assign trips to the network. Equilibration of supply and demand Graphic from “Urban Transportation Planning,” Meyer & Miller, 1984. Presentation to the JTWG of the RMAS