big data and transportation solutions in northern virginia · big data and transportation solutions...

Big data and transportation

solutions in Northern Virginia

Chris McCahill, Senior AssociateState Smart Transportation Initiative

Keith Jasper, Program CoordinatorNorthern Virginia Transportation Authority

State Smart Transportation Initiative

A network of reform-oriented state DOTs, founded in

2010 and housed at the University of Wisconsin.

5/25/16 Big data and transportation solutions in NOVA 1

• Executive-level

Community of

Practice

• Technical

assistance

• Resource for the

transportation

community

Project overview

• Use “big data” to explore ways to improve access to destinations in Northern Virginia (NOVA):– Traditional TDM

– Connectivity

– First- and last-mile solutions

– Design

– Land use

– Parking

• Not including major capacity projects

Project team:– Virginia Office of Intermodal Planning and Investment

– SSTI

– Michael Baker International

– Streetlight Data


Major initiativesMajor initiatives

in NOVA

Educational programs/events

Expanded transit service

Carpool/ridesharing services

Increased coordination among modes/agencies

Information kiosks/apps

Special event services

Improve transit stations/shelters

Improve access to transit stations

Employer-based economic incentives

Improved road and path connectivity/directness

Bicycle and pedestrian improvements

Park and ride facilities

Transit priority/express lanes

Intelligent Transportation Services

Smart Growth policies

Subsidized transit passes or decrease fares

Bike share programs

Flexible work schedules

On-site transportation coordinators

Bicycle accommodations

Car share programs

Employer-assisted housing/live near work

Guaranteed ride home

HOV/HOT lanes

TMA membership

Toll-managed lanes

Transit-oriented development

Congestion pricing

Demand-responsive transit

Designated carpool/car share spaces

Distance based charges/PAYD insurance

Parking management/pricing

5/25/16 Big data and transportation solutions in NOVA 35/25/2016 3

Somewhat typical

Data

• Anonymous GPS data

from mobile phones and

navigational devices

• Smaller sample but

higher precision than

cellular data

• Added information

compared to traffic

counts and travel

demand modelsStreetlight Data


GPS travel patterns


Analyze To understand

Precise origins and demographics

- Trip generation- Equity- Transit plans

Precise destinations and day/time

- Commuting & work locations- Transportation centers- “Last mile” and parking- Employer partnerships

Actual routes and trip duration

- Travel times- Variations/reliability- Secondary road traffic

Vehicle type and class

- Personal vs. commercial vehicles

- Criteria emissions- Heavy vehicle traffic

Custom dateranges

- Before and after studies- Seasonal variance- Trends over time

$150K and over

$75 - $150K

$30 - $75K

Under $30K

We don’t see this level of detail.

We look at patterns.

Our approach

1. Scan GPS data for short trips, circuitous trips and common origin-destination pairs.

2. Identify case studies showing unique issues and opportunities.

3. Evaluate potential costs and benefits of recommended actions (using GPS data).

We engaged with local stakeholders throughout the process.

The project evolved to meet the needs of stakeholders (providing access to data).



Scan – Common OD pairsOrig.

TAZ

Dest.

TAZ

Flow

(000) Circ.

Dist.

(mi)

Dur.

(min)

VMT

(000)

VHT

(000)

591 604 4.66 1.50 5.2 11 24.2 0.85

604 591 2.96 1.36 4.7 10 14.0 0.49

576 565 2.84 1.48 2.9 9 8.2 0.43

824 828 2.74 1.29 1.8 22 5.0 1.00

695 618 2.64 1.21 2.1 11 5.4 0.48

834 828 2.56 1.41 3.1 18 7.8 0.77

591 601 2.50 1.79 3.3 12 8.2 0.50

565 576 2.42 1.50 2.9 8 7.0 0.32

576 591 2.17 1.56 3.7 13 8.1 0.47

591 576 2.05 1.58 3.8 13 7.7 0.44

576 585 2.00 1.66 1.8 11 3.7 0.37

618 695 1.92 1.22 2.1 10 4.0 0.32

735 725 1.88 1.48 2.0 18 3.7 0.56

588 591 1.86 1.37 3.4 13 6.4 0.40

219 238 1.84 1.60 1.1 8 2.1 0.25

478 467 1.83 1.39 3.3 9 6.1 0.27

295 282 1.79 1.26 1.1 8 1.9 0.24

220 218 1.76 1.35 0.9 7 1.5 0.21

834 819 1.72 1.26 2.9 19 4.9 0.54

725 737 1.71 1.29 1.7 9 3.0 0.26

542 540 1.62 1.42 1.2 8 1.9 0.22

220 242 1.61 1.18 1.6 7 2.5 0.19

282 295 1.60 1.42 1.2 8 1.9 0.21

282 297 1.54 1.42 0.8 8 1.3 0.20

618 725 1.52 1.52 10.3 28 15.6 0.71


Scan – Short, circuitous trips

Orig.

TAZ

Dest.

TAZ

<5 miles <2 miles <1 mile

Flow Circ. Flow Circ. Flow Circ.

32 32 2,351 2.48 1,957 1.86 1,069 1.42

559 559 716 2.40 570 1.57 254 1.32

843 843 711 2.20 476 1.84 265 1.31

238 238 682 2.40 609 1.86 514 1.48

52 52 546 2.58 395 1.49 320 1.23

457 457 491 3.00 487 2.98 65 1.87

449 449 477 3.54 288 2.02 95 1.69

76 76 474 2.27 436 2.05 280 1.51

130 121 434 2.55 376 2.33 0 -

107 115 392 2.21 315 1.45 248 1.26

115 107 373 2.80 278 1.79 149 1.39

707 732 358 2.26 113 1.73 8 1.03

308 323 333 2.48 275 1.90 80 1.56

121 130 290 3.11 228 2.87 0 -

70 76 276 2.34 248 2.15 145 1.51

323 308 266 2.22 229 1.84 79 1.43

584 584 266 2.41 224 1.77 127 1.40

326 326 238 2.28 215 1.65 183 1.44

474 474 232 2.40 208 1.84 57 1.31

722 630 221 2.36 69 1.71 34 1.55

186 186 221 2.39 202 1.68 182 1.57

376 394 219 2.38 136 1.91 8 1.11

290 290 216 4.54 130 1.59 85 1.35

350 331 209 2.33 111 1.93 4 1.07

757 757 208 2.30 179 1.97 80 1.29


Scan – Selected linksPercent of flow

Link ID

Flow

(000)

Top O-D

pair

Top five

pairs <5 mi <2 mi <1 mi Link description and direction

1036 67.5 10.7 19.0 2.9 0.7 0.2 Neabsco Mills Rd (US-1 to Opitz Blvd) SB

1018 60.3 1.4 4.4 3.4 1.1 0.3 VA-28 (I-66 to Westfields Blvd) SB

1012 55.7 2.0 4.4 0.0 0.0 0.0 I-66 (US-29 to VA-120) WB

1106 51.3 1.4 4.4 3.3 1.4 0.4 US-50 (VA-286 to I-66) EB

1006 47.8 10.6 25.1 0.5 0.1 0.0 VA-123 (George Wash. Pkwy to Chain Bridge) NB

2217 47.6 1.5 5.1 5.5 1.5 0.4 US-50 (Stringfellow Rd to VA-286) EB

1049 45.0 1.6 6.0 10.2 4.4 2.0 US-50 (VA-28 to Lees Corner Rd) EB

1217 43.2 1.4 4.1 3.8 1.4 0.3 US-50 (Stringfellow Rd to VA-286) WB

2224 41.0 0.9 4.1 0.4 0.1 0.0 I-66 (I-495 to VA-7) WB

1019 40.7 2.0 7.2 10.2 3.6 1.1 US-50 (VA-609 to VA-28) WB

1224 40.6 1.9 5.6 0.4 0.1 0.1 I-66 (I-495 to VA-7) EB

1010 40.4 2.0 6.5 2.0 0.5 0.3 VA-7 (VA-2400 to Lexington Dr) EB

1201 38.9 4.9 9.2 0.6 0.5 0.4 VA-267 (I-66 to Magarity Rd) SB

2148 38.0 2.2 8.9 6.6 1.0 0.2 VA-7 (Battlefield Pkwy SE to Crosstrail Blvd) WB

1086 37.9 0.7 2.7 0.4 0.2 0.1 VA-286 (VA-123 to Popes Head Rd) NB

2010 37.9 1.8 6.8 2.5 0.4 0.0 VA-7 (VA-2400 to Lexington Dr) WB

1016 37.9 3.4 9.0 5.8 2.5 1.0 George Wash. Pkwy (VA-124 to US-29) SB

1222 37.5 2.9 7.1 15.3 11.1 4.4 VA-7 (VA-123 to I-495) EB

1013 37.5 1.3 5.1 12.0 3.8 1.0 VA-123 (VA-267 to VA-738/VA-309) NB

1148 36.7 2.0 7.9 7.9 0.6 0.1 VA-7 (Battlefield Pkwy SE to Crosstrail Blvd) EB

1102 36.5 1.5 6.4 16.6 11.4 4.4 VA-7 (VA-267 to VA-123) WB

1032 35.3 1.0 4.1 9.1 5.6 1.7 US-1 (VA-7 to East Monroe Ave) SB

2222 35.3 1.2 4.8 14.6 10.1 3.5 VA-7 (VA-123 to I-495) WB

17 case studies


1. Tysons Corner

2. George Mason University

3. Fort Belvoir

4. Van Dorn Metro

5. Rippon VRE

6. Bull Run

7. Fairfax Center / Fair Oaks Mall

8. Merrifield /Dunn Loring

9. Inova Fairfax Hospital

10. Manassas Area

11. Van Dorn – South

12. Inside the Beltway

13. Dulles Town Center

14. Bailey’s Crossroads

15. Goose Creek

16. Dulles Area North

17. Dulles Area West

Example case study: Tysons Corner


Traffic on Rt. 7 westbound (PM) beginning at Tysons


29% of traffic begins at Tysons

22% of trips are < 5 miles

16% of trips are < 2 miles

7% of trips are < 1 mile

Tysons Corner

Opportunities

• Bicycle and pedestrian improvements

• Parking management

• Street and parcel connections

• Other local transportation options


Dulles Toll Road

M

M M

M

Tysons Corner

Benefits

• Enable walkable, transit-oriented development

• Remove 2.0 - 3.8 million vehicle trips per year (up to 1 million hours)

• Save up to $11.5 million in traveler costs per year

• Eliminate up to 8,400 tons of carbon emissions per year

Costs

• $12-14M capital – $3M transit; $9-10M

road/bike/pedestrian

• $1.8M annual operating for transit/TDM

• Includes:– Circulator shuttle

– Street improvements and connections

– Bike share

– TDM and parking management


George Mason University


33% of trips

George Mason University

Opportunities

• Off campus connections by foot, biking and transit

• Parking management

• Walkable development in surrounding area

Remove 250K to 460K vehicle trips per year



Van Dorn Street Metro



Van Dorn Street


Van Dorn St

Metro

M

Opportunities

• Address accessibility needs without adding local traffic

• Limited-use crossings (bikes, pedestrians, etc.)

Remove 100K to 152K vehicle trips per year



Rippon VRE Station

Rippon VRE Station


Farm Creek Dr at RipponBlvd leaving Rippon station

Opportunities

• Bike and pedestrian connections to station

• Bike accommodations at station

Remove up to 150K vehicle trips per year

Rippon VRE Station

Rippon VRE

Station


Opportunities

• Bike and pedestrian connections to station

• Bike accommodations at station

Remove up to 150K vehicle trips per year

Key findings

• Data visualization and trip quantification are

immensely useful.

• Important to consider multimodal connections

to sites and multimodal options at sites.

• Still more work needed in modal recognition,

trip-chaining, automation, and visualization.

Full report available at ssti.us


Big Data and Transportation Solutionsin Northern Virginia: An NVTA Perspective

Keith Jasper

What is the NVTA?

• Created by the Virginia General Assembly in 2002

• Dedicated revenue stream established in 2013

• Working collaboratively to plan, prioritize and fund regional transportation projects in NorthernVirginia

26

The Authority: Working Regionally

27

http://www.loudoun.gov/budget/index.htm

http://www.loudoun.gov/budget/index.htm

http://www.virginiadot.org/news/resources/VDOTLOGOS.zip

http://www.virginiadot.org/news/resources/VDOTLOGOS.zip

Regional Transportation Planning

Long Range Transportation Planning with updates of TransAction 2030 and 2040.

28

TransAction Update

29

Regional Funding Programmed to

Date

70 Projects Approved

Totaling$535 million

30

Draft FY2017 Program

31

• 24 candidate projects

• $668 million

• Estimated $267 million available in PayGo revenues

Big Data – FY2017 Program

32

Big Data – TransAction update

Possible applications:

• Origin-destinations

• Travel behavior in activity centers

• Model validation?

33

Big Data – Long Term ‘Benefit’

• Understanding the regional transportation impact of NVTA-funded projects relative to the jurisdictions from which the revenue can be attributed.

34

Additional Information

• For more information, please visit: www.TheNoVaAuthority.org

• TransAction: www.NVTATransAction.org

• [email protected]

35

http://www.thenovaauthority.org/index.html

http://www.nvtatransaction.org/

mailto:[email protected]

36

THANK YOU!

A recording of this webinar will be on the SSTI web site tomorrow.

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www.ssti.us

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5/25/16 Big data and transportation solutions in NOVA

http://www.ssti.us/

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