Title: 2030 Higher Household Growth in Region Scenario: Travel Model Results and Accessibility Analysis
12030 Higher Household Growth in Region
ScenarioTravel Model Results and Accessibility
Analysis
Item 3
- 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
22030 Higher Household Growth in Region (HHG)
ScenarioWhat is it?
- Land use 2030 Higher Household Growth
- Network 2030 Transit-oriented development (TOD)
32030 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)
42030 Higher Household Growth in Region Land
UseBlack 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)
5Transit-oriented development network
2030 CLRP Based on 2003 CLRP and FY 2004-2009 TIP
2030 CLRP 2030 CLRP with enhanced transit service, especially elimination of the 2005 transit constraint through DC core
2030 TOD 2030 CLRP with new transit projects Metrorail, Commuter rail, Transitways (BRT/LRT)
6Transportation network Fixed guideway
improvements
- Heavy rail (Metrorail, commuter rail)
- Light rail (LRT)
- Bus rapid transit (BRT)
- Transitway (can be BRT or LRT)
7Transportation network 2005
8Transportation network 2030 CLRP
9Transportation 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
10Transportation network TOD, Map 1 of 2
11Transportation network TOD, Map 2 of 2
12Map legend Fixed guideway extensions in TOD
network
132030 CLRP vs. TOD networkFixed 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
14HHG 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)
15HHG 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 gt 1.0 drops by 6.4
(from 2,560 to 2,400 miles)
16HHG scenario Model results, 2
17Accessibility Analysis
- 2030 Higher Household Growth in Region Scenario
18Accessibility 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
19Change 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.
20Change 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.
21Change 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.
22Change 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.
23Change 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).
24Change 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.
25Change 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 Georges counties, due to
fewer long-distance commuting trips from Howard
Anne Arundel counties. - There were moderate losses in accessibility in
Prince Georges 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.
26Change 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
27Findings/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
28Findings/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.
29Acknowledgments
- 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
30Thank you
31TPB modeled area
32Four-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.