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1ALAMEDA COUNTY TRANSPORTATION COMMISSION
2013 Performance Report
A presentation to PPLC
Tess Lengyel, Deputy Director of Planning and PolicyMatthew Bomberg, Assistant Transportation PlannerApril 14, 2014
2
• Track trends and progress towards goals in transportation plans
Purpose of Performance Report
transportation plans Countywide Transportation Plan
Countywide Bicycle and Pedestrian Plans
Congestion Management Program statute
• Identify needs for more extensive analysis• System level monitoring • System-level monitoring
Complemented by other more focused monitoring efforts (e.g. LOS monitoring, modal plans)
6.2
2
3Scope of Performance Report
Commute Patterns RoadwaysCommute PatternsGeneral population and employment trendsCommute flowsCommute mode share
yFreeway delaysFreeway speedsLocal road pavement conditionCollisions
TransitRidershipService utilizationCost-effectivenessService interruptions & fleet age
Bicycling and WalkingCollisionsCountsNetwork/project completion from local jurisdiction summaries
On-time performance & speedAll 7 operators, fixed route only
Master plan completionProgram participation
Data Sources: Existing or publically available dataPrevious fiscal year (FY12/13) or most recent available plus historic trends
4
• Demand for travel on the rise: Alameda County had largest percentage increase in population in California in 2013 and saw job growth for third consecutive year
Key Findings
j g y• Uneven employment recovery: Alameda County employment
rate lags the overall Bay Area• Regionally essential: More than 25% of all Bay Area commuters
touch Alameda County• More regional commute patterns: Alameda County residents
increasingly work in other counties; Alameda County workers increasingly commute from other countiesincreasingly commute from other counties
• Balanced commute modes: 36% of Alameda County workers use transit, walking biking, telecommute, or carpool, while 64% drive alone
• More multimodal: share of Alameda County workers using transit, walking, biking, and telecommuting up 5% since 2000
3
5
• Freeway congestion up: Severe congestion increased by over 20% on freeways last year
• Local road state of repair unchanged: Average local road
Key Findings, cont.
• Local road state of repair unchanged: Average local road condition not improving greatly and 20% of roads are poor or failed
• Overall safety improvements: Roadway collisions are down over last decade
• Transit ridership climbing but challenges loom: Ridership is up overall and for most operators but aging assets, crowding, and dense urban operating conditions (for buses) pose challengesdense urban operating conditions (for buses) pose challenges
• Walking and biking: counts are on the rise, collision rates declining, and network buildout continues
6Commute Patterns: Population and Jobs
Population and job recovery 12
14Quarterly Unemployment Rate
both continued in 2013
0
2
4
6
8
10
12
2005
, Q1
2005
, Q3
2006
, Q1
2006
, Q3
2007
, Q1
2007
, Q3
2008
, Q1
2008
, Q3
2009
, Q1
2009
, Q3
2010
, Q1
2010
, Q3
2011
, Q1
2011
, Q3
2012
, Q1
2012
, Q3
2013
, Q1
Alameda County Bay Area
640650660670680690700
1.481.5
1.521.541.561.58
loye
d (th
ousa
nd)
nts (
mill
ion)
Residents and Jobs in Alameda County
Source: Department of Finance Estimates, Bureau of Labor Statistics Local Area Employment data
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
600610620630640
1.41.421.441.46
Wor
kers
em
p
Resid
en
Residents Jobs
Alameda County employment rate lags region
4
7Commute Patterns: Worker FlowsAlameda County plays critical role supporting regional
commute travel.
3,160,000 318,000
309,000
246,0001,159,000
Commutes within, to, from, or through the Bay Area Region
Commutes within, to, from, or through Alameda County
From
286,000
Involving Alameda
County (27%)
Not Involving Alameda County (73%)
Within
ToThrough
Source: Census Bureau Longitudinal Employment-Household Dynamics data
8Commute Patterns: Worker Flows
O i i D ti ti i f k h li k i
Alameda County commutes became more regional in nature over last decade.
30% 34%
33% 35%
50%60%70%80%90%
100%
Origin-Destination pairs of workers who live or work in Alameda County
Live in another county, work in Alameda CountyLive in Alameda County
36% 31%
30% 34%
0%10%20%30%40%50%
2002 2011
Live in Alameda County, work in another countyLive and work within Alameda County
5
9Commute Patterns: Journey-to-work Mode ShareWorkers living in Alameda County use a diverse mix of
transportation modes to commute to work
10% 2% 4%1%
6%26%
All modes Non-driving modes
64%
13%
Drive Alone Carpool Public TransitBike Walk OtherWork from Home
Source: American Community Survey 2012 1-Year Estimate
10Commuting Patterns: Journey-to-work Mode Share
Alameda County commutes became more multimodal over last decade
20%
40%
60%
80%
100%
Perc
ent o
f wor
kers • Combined share of solo-
driving and carpooling dropped by 5 percent
• Working from home is fastest-growing mode
• Public transit walking
80% 75%
0%2000 2012
Drove AloneCarpooledPublic TransitBike, Walk, Telecommute, Other
Public transit, walking, and biking mode share all increased
• Biking mode share nearly doubled
Source: Census 2000 and American Community Survey 2012 1-Year Estimate
6
11Roadways: Freeway Delay
Average daily freeway delay increased by 22 percent overall from FY11/12 to FY12/13
30,000
40,000
50,000
60,000Average Daily Vehicle Hours of Delay vs. 35 mph threshold
NightEveningPMMidAM
21%
0
10,000
20,000
FY11/12 FY12/13 FY11/12 FY12/13
Weekday Weekend
AM
37%Note: chart
shows “severe” delay (excess
travel time from speeds below
35 mph)
Source: INRIX, Inc. Analytics Suite
12Roadways: Pavement Condition Index
100100%
Average PCI declined slightly and is flat over last 5 years; one in five roads is “failed” or “poor”
30405060708090100
30%40%50%60%70%80%90%
100%
Ave
rage
PC
I
cent
of L
ane-
Mile
s
01020
0%10%20%
2007 2008-9 2010 2011 2012
Per
Poor or Failed At Risk, Fair, or GoodVery Good or Excellent Average PCI
Source: MTC StreetSaver Database
7
13Roadways: Collisions
12035 000
Collisions continued a long-term downward trend in 2011; injury and fatal collisions down 32 percent since 2002.
70
80
90
100
110
120
15,000
20,000
25,000
30,000
35,000
mbe
r of F
atal
ities
mbe
r of C
ollis
ions
40
50
60
0
5,000
10,000
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Num
Num
Property Damage Only Injury & Fatal Fatalities
Source: Statewide Integrated Traffic Reporting System
14Transit: Ridership
Total annual boardings in Alameda County increased by 4 percent in FY12/13 over FY11/12
40,00060,00080,000
100,000120,000
Total Annual Boardings in Alameda County (thousand)
• BART accounted for two-thirds of ridership growth
• Bus boardings up after declining in four of five previous years amid major service cuts
020,00040,000
BART Commuter Rail Bus Ferry
• Ferry boardings increased while commuter rail declined
• Long-term shift from bus to BART
Source: National Transit Database (2005-2012) and preliminary NTD filings (2013)
8
15Transit: Service Utilization
115120125130
Lev
els
Boardings per RVH Trend
BARTAC Transit
Most transit operators saw improvement or minimal
change in service utilization in
Boardings per Revenue Vehicle Hour
Transit FY2005 FY2012 FY2013 Percent Percent
80859095
100105110
Perc
ent o
f 200
5
• Service utilization is measured by boardings per revenue vehicle hour (RVH)
• BART saw large increase in service utilization and carries nearly 15 passengers
gFY2012-13
Transit Operator
FY2005 FY2012 FY2013 Percent Change vs. FY2012
Percent Change vs. FY2005
BART 55.95 65.44 69.49 6% 24%
ACE 34.22 38.97 39.82 2% 16%
AC Transit 36.05 33.23 34.20 3% -5%
LAVTA 16.93 14.00 13.86 -1% -18%
Union City 10.05 12.74 12.52 -2% 25%
WETA 75.46 110.22 107.25 -3% 42%
carries nearly 15 passengers per RVH more than in 2005
• AC Transit improved service utilization in FY2013 and has improved this metric in 3 of last 4 years
Source: National Transit Database (2005-2012) and preliminary NTD filings (2013)
16Cost Efficiency• Most operators have seen increasing in cost per rider and/or cost per
Revenue Vehicle Hour since 2005
Transit: Other Trends
State of Good Repair• Frequency of service interruptions declined for all operators in FY12/13• Fleets of most operators are in midlife on average
Union City Transit (relatively new fleet) and BART (very old fleet) are exceptions
AC Transit unveiled first shipment of new bus purchase in late FY12/13 and BART procuring new cars
Service Quality• Experiences improving on-time performance were mixed
AC Transit achieves lower on-time performance but must contend with dense, congested urban conditions
• AC Transit has seen steady decline in commercial speed (speed accounting for delays) since 2005
9
17Bicycling and Walking: Counts
Data collected through the Alameda CTC bicycle and
pedestrian count program suggest 12001400
Number of Bicyclists Counted (9 long-term monitoring locations)
40%
Female Percent of Cyclists Counted
pedestrian count program suggest that levels of cycling and walking are growing and that the diversity
of cyclists is increasing
2500
Number of pedestrians counted (6 long-term monitoring locations)
0200400600800
10001200
2002* 2004* 2006 2008 2010 2011 2012
0%
10%
20%
30%
40%
2008 2009 2010 2011 2012
Source: Alameda CTC Bicycle and Pedestrian Count Program
0
500
1000
1500
2000
2002 2003 2010 2011 2012
18Bicycling and Walking: CollisionsCollisions involving bicyclists have
increased, however bicycle counts have increased faster.
Collisions involving pedestrians have declined even as counts of
pedestrians have increased
0
1
2
3
4
5
6
0100200300400500600700800
02 03 04 05 06 07 08 09 10 11
Fata
l Col
lisio
ns
Num
ber o
f Col
lisio
ns
0
5
10
15
20
25
30
35
0100200300400500600700800900
1000
2 3 4 5 6 7 8 9 0
Fata
l Col
lisio
ns
Num
ber o
f Col
lisio
ns
200
200
200
200
200
200
200
200
20 20
Sources: Statewide Integrated Traffic Reporting System, Alameda CTC Bicycle and Pedestrian Count Program
Changes from 2002 to 2011
Injury/Fatal Collisions
Counts
Biking +21% +75%Walking -18% +47%
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
10
19Bicycling and Walking: Network Completion
15
20
Miles of Bikeway InstalledJurisdictions reported installing more than 25 miles of bikeways and completing more than 30
0
5
10
Class I Class II Class III
Multi-use trail (paved)Bike lane (not upgraded*)Bike lane (upgraded*)Bike route (route with shared lane markings)Bike route (bicycle boulevard)
Multi-Use Trail Bike Lane Bike Route
p gmajor pedestrian capital
projects FY12/13
New trailSidewalk gap closure
Widened sidewalkCrossing improvements
Major Pedestrian Capital Projects Completed
Bike route (bicycle boulevard)
Source: Survey of Local Jurisdictions
0 10 20 30
Traffic calming elementsMajor pathway rehabilitation
Total
Note: categories defined by Alameda CTC staff based on responses from local jurisdictions staff. A project may fall in multiple categories. Chart does not include improvements including signal timings or detection to improve crossing safety, curb ramp installations, or installation of standalone traffic calming elements (e.g. single speed bump)
20Alameda CTC Performance Monitoring: What’s Next?
• Explore ways to integrate data requests with Compliance ReportsCompliance Reports
• Coordinate with regional agencies on collection of land use data (e.g. development approvals) and evaluation of land use/transportation coordination measures
• Identify new performance measures as part of Goods Movement, Arterials, and Transit plans System-level to Facility-level
• Evaluate investments in relation to performance
11
21
Questions?
22
EXTRAS
12
23Commute Patterns: Worker FlowsAlameda County commutes became more regional in
nature over last decade.
Where Alameda County
Workers Seek Employment
2002 2011
52%46%
54% 48%
Where Alameda County
Businesses Find Workers
20112002
52% 47%
53%48%
24Roadways: Freeway Travel Speeds
Average speeds declined in weekday AM and PM peaks and weekend midday from FY11/12 to FY12/13
54565860626466
Average Freeway Speed
FY10-11FY11-12
48505254
Weekday, AM Peak (7-9 am)
Weekday, Midday (12-2
pm)
Weekday, PM Peak (4-6 pm)
Weekend, Midday (12-2
pm)
FY11 12FY12-13
13
25Transit: Cost Efficiency
120
130
140
5 Le
vels
Cost per Rider Trend
BARTAC Transit
Cost containment is a critical challenge facing
transit operators
Cost per Rider ($2013)
Transit FY2005 FY2012 FY2013 Percent Percent
80
90
100
110
120
Perc
ent o
f 200
5transit operators
• Cost efficiency is one of many service planning considerations for transit operators; operators achieve different costs per rider based on different technologies and service structures
• BART has generally managed to Transit Operator
FY2005 FY2012 FY2013 Percent Change vs. FY2012
Percent Change vs. FY2005
BART $5.01 $4.21 $4.59 9% -8%
ACE $20.74 $15.86 $16.03 1% -23%
AC Transit $4.32 $5.61 $5.32 -5% 23%
LAVTA $5.76 $7.36 $7.14 -3% 24%
Union City $8.73 $6.26 $6.64 6% -24%
WETA $11.19 $9.57 $15.03 57% 34%
BART has generally managed to contain cost per rider though it saw an increase in FY2013
• AC Transit has seen longer term increases in cost per rider, though this metric declined in FY2013
Source: National Transit Database (2005-2012) and preliminary NTD filings (2013)
26
FY2009 FY2010 FY2011 FY2012 FY2013
Rail Mean Time Between Service Delay (Hours)
BART 2,683 2,796 2,995 3,216 3,758
Transit: Service Interruptions & Fleet Age
All transit operators reduced the ,683 ,796 ,995 3, 6 3,758
ACE 546 438 388 2,438 359
Bus Average Distance Between Mechanical Failure (Miles)
AC Transit 4,656 5,727 7,941 6,556 8,244
LAVTA 4,904 4,837 6,353 15,249 17,397
Union City 3,880 4,902 11,402 13,749 16,505
reduced the frequency of
service interruptions in FY2013
TransitO t
Average A ( )
Typical U f l Lif The fleets of most Operator Age (yrs) Useful Life
BART 33.8 34.8
ACE 13.5/12.1 30/40
AC Transit 7.6 15
LAVTA 8.7 15
Union City 4.4 12
WETA 12.6 15
The fleets of most operators are
midway through their useful lives on
averageSource: National Transit Database (2005-2012) and preliminary NTD filings (2013)
14
27Transit: On-Time Performance & Commercial Speed
80%100%
Percent On-Time Arrivals Bus operators generally saw declines in average commercial
speed (speed accounting for d l ) i FY12/13 diff t
0%20%40%60%
FY11 12 FY12 1314.00
15.00Average Commercial Speed (mph)
delays) in FY12/13; different operating conditions lead to differences in performance
across operators
FY11-12 FY12-13
11.00
12.00
13.00
AC Transit LAVTA Union City Transit
Experiences improving on-time performance were mixed;
different operating conditions lead to differences in
performance across operators. Source: National Transit Database (2005-2012) and preliminary NTD filings (2013)
28Transit: BART Trends
140
150
vels
120125130
ls
80
90
100
110
120
130
Perc
ent o
f 200
5 Le
v
80859095
100105110115120
Perc
ent o
f 200
5 Le
ve
BoardingsRevenue Vehicle HoursOperating Costs ($2013)Fare Revenue ($2013)
Boardings/RVHOp. Costs ($2013)/RVHOp. Costs ($2013)/Board
15
29Transit: AC Transit Trends
130
140ve
ls
130
140
ls
70
80
90
100
110
120
Perc
ent o
f 200
5 Le
v
80
90
100
110
120
Perc
ent o
f 200
5 Le
ve
BoardingsRevenue Vehicle HoursOperating Costs ($2013)Fare Revenue ($2013)
Boardings/RVHOp. Costs ($2013)/RVHOp. Costs ($2013)/Board
30Bicycling: Counts
7000
Number of Bicyclists Counted (61 locations countywide)
42%
Data collected through the Alameda CTC bicycle and pedestrian count program
0100020003000400050006000
2010 2011 2012
42%
Female Percent of Cyclists Counted
pedestrian count program suggest that levels of cycling
are growing and that the diversity of cyclists is
increasing
1400
Number of Bicyclists Counted (9 long-term monitoring locations)
0%
10%
20%
30%
40%
2008 2009 2010 2011 2012
0200400600800
100012001400
2002* 2004* 2006 2008 2010 2011 2012
64%
Source: Alameda CTC Bicycle and Pedestrian Count Program
16
31Bicycling: Collisions
Collisions involving bicyclists have increased,
2
3
4
5
6
200300400500600700800
of F
atal
Col
lisio
ns
mbe
r of C
ollis
ions
30%40%50%60%70%80%
Percent Change (2002 to 2011)
however bicycle counts have increased faster.
0
1
0100200
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011 Num
ber o
Num
Property Damage OnlyInjury & FatalFatal Collisions
0%10%20%
Injury and Fatal Collisions
Bicyclists Counted
Sources: Statewide Integrated Traffic Reporting System, Alameda CTC Bicycle and Pedestrian Count Program
32Bicycling: Local Master Plan Completion
At the conclusion
f FY12/13 of FY12/13, nine
jurisdictions had local
master plans that
were adopted within the within the last five
years, and three more have a plan or update underway.
17
33Bicycling: Network Completion
Jurisdictions reported installing more than 25 miles of bikeways in FY12/13, and several reported installing upgraded bicycle lane
f iliti th t i ti d i ibilit f li t
5
10
15
20
Miles of Bikeway Installed by Facility Type
facilities that improve separation and visibility of cyclists
0
5
Class I Class II Class III
Multi-use trail (paved)Bike lane (not upgraded*)Bike lane (upgraded*)Bike route (route with shared lane markings)Bike route (bicycle boulevard)
Multi-Use Trail Bike Lane Bike Route
Source: Survey of Local Jurisdictions
34Bicycling: Programs and Education
120140160
14 00016,00018,00020,000
ons
nerg
izer Bicycle safety education
classes, attendance, and
20002500300035004000
60
80
100
f Atte
ndee
s
of C
lass
es
020406080100
02,0004,0006,0008,000
10,00012,00014,000
2006
2007
2008
2009
2010
2011
2012
2013
Ener
gize
r Sta
ti
Peop
le Ta
llied
at E
nSt
atio
ns
Energizer station participantsNumber Energizer Stations
attendance per class have all increased in consecutive years.
0500100015002000
0
20
40
FY09/10 FY10/11 FY11/12 FY12/13
Num
ber o
f
Num
ber
Classes Attendees
Number Energizer Stations
Bike to Work Day energizer stations and
participants tallied have grown since 2006.
Sources: Bicycle Safety Education Grant Program Progress Reports, Bike to Work Day Annual Report
18
35Walking: Counts
Count data collected through the Alameda CTC 20,000
Number of pedestrians counted (62 locations countywide)
count program suggests that walking increased in 2012
and has increased over the long-term
2500
Number of pedestrians counted (6 long-term monitoring locations)
-
5,000
10,000
15,000
2010 2011 2012Year-over-year percent
change
0500
1000150020002500
2002 2003 2010 2011 2012 -10%0%
10%20%30%40%50%
North Central South East
20112012
Source: Alameda CTC Bicycle and Pedestrian Count Program
36Walking: Collisions
Collisions involving pedestrians have declined by nearly one-fifth even as pedestrian counts have
15
20
25
30
35
400500600700800900
1000
of F
atal
Col
lisio
ns
ber o
f Col
lisio
ns
10%20%30%40%50%60%
Percent Change (2002 to 2011)
y pincreased by nearly fifty percent.
0
5
10
0100200300
Num
ber
Num
b
Property Damage Only Injury & FatalFatal Collisions
-30%-20%-10%
0%10%
Injury and Fatal Collisions
Pedestrians Counted
Sources: Statewide Integrated Traffic Reporting System, Alameda CTC Bicycle and Pedestrian Count Program
19
37Walking: Local Master Plan Completion
At the conclusion
f FY12/13 of FY12/13, eight
jurisdictions had local
master plans that
were adopted within the within the last five
years, and four more
have a plan or update underway.
38Walking: Network Completion
Jurisdictions reported completing 30 major pedestrian capital projects in FY12/13.
Widened sidewalk
Crossing improvements
Traffic calming elements
Major trail/pathway maintenance
Total
Note: categories defined by Alameda CTC staff based on responses from local
jurisdictions staff. A project
0 5 10 15 20 25 30 35
New trail
Sidewalk gap closure
Widened sidewalk
Number of projects completed
may fall in multiple categories. Chart does not
include improvements including signal timings or
detection to improve crossing safety, curb ramp installations, or installation
of standalone traffic calming elements (e.g.
single speed bump)
Source: Survey of Local Jurisdictions
20
39Walking: Programs and Education
Safe Routes to School has expanded rapidly into 147 schools countywide.
6890
30
454
66
5670
8840
60
80
100
120
140
160be
r of P
artic
ipa
ting
Scho
ols
(at e
nd o
f sch
ool y
ear) 102
total
147 total
240
56
0
20
2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13
Num
School year
Comprehensive ProgramTechnical AssistanceHigh School PilotSan Leandro Pilot (Schools added to program)Comprehensive/Technical Assistance Combined
Source: Safe Routes to School Program Annual Reports