Eric Sundquist Managing Director State Smart Transportation Initiative (SSTI) Urban Sustainability Accelerator

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1 New tools for making better transportation system decisions Eric Sundquist Managing Director State Smart Transportation Initiative (SSTI) Urban Sustainability Accelerator

2 Accessibility and trip-making Accessibility = Ease of reaching destinations Trip-making = Actual use of the system to reach destinations 9/21/16 Accessibility and Trip-making 1

3 Accessibility and trip-making Accessibility = Ease of reaching destinations Trip-making = Actual use of the system to reach destinations Both measures are empirical, multimodal and scalable 9/21/16 Accessibility and Trip-making 2

4 Motivation Scan Assess performance Diagnose Assess solutions Communicate 9/21/16 Accessibility and Trip-making 3

5 Problems with conventional approach T4America 9/21/16 Accessibility and Trip-making 4

6 Problems with conventional approach HB 599 (Virginia) 9/21/16 Accessibility and Trip-making 5

7 Problems with conventional approach Bias toward big Bias toward moving vehicles Modeled travel misses idiosyncrasies Design elements not considered Modally siloed Land use an input Unverified black box Some exceptions, e.g. DelDOT s LUTSAM. 9/21/16 Accessibility and Trip-making 6

8 Measuring accessibility The ease (in travel time) by which travelers and shippers can reach their destinations by various modes. Factors: Modal availability Speed (actual or perceived) Distance 9/21/16 Accessibility and Trip-making 7

9 Measuring accessibility The ease (in travel time) by which travelers and shippers can reach their destinations by various modes. Factors: Modal availability Speed (actual or perceived) Distance Vehicle speed (traditional measure) is a factor, but is no longer the primary desired outcome. 9/21/16 Accessibility and Trip-making 8

10 Calculating accessibility Network Land uses Method to calculate times 9/21/16 Accessibility and Trip-making 9

11 Decay factor (Dane County, Wisconsin) Calculating accessibility 100% 90% 80% 70% Auto Transit Walk Other All modes 60% 50% 40% 30% 20% 10% 0% Travel time to work (minutes) 9/21/16 Accessibility and Trip-making 10

12 Calculating accessibility 9/21/16 Accessibility and Trip-making 11

13 Calculating accessibility 9/21/16 Accessibility and Trip-making 12

14 Calculating accessibility 9/21/16 Accessibility and Trip-making 13

15 Calculating accessibility 9/21/16 Accessibility and Trip-making 14

16 Decay factor (Dane County, Wisconsin) Calculating accessibility 100% 90% 80% 70% Auto Transit Walk Other All modes 60% 50% 40% 30% 20% 10% 0% Travel time to work (minutes) 9/21/16 Accessibility and Trip-making 15

17 Decay factor (Dane County, Wisconsin) Calculating accessibility 100% 90% 80% 70% Auto Transit Walk Other All modes 60% 50% 40% 30% 20% 10% 0% Travel time to work (minutes) 9/21/16 Accessibility and Trip-making 16

18 Two primary metrics Non-work: access to groceries, parks, banks, restaurants and other non-work destinations 80 percent of trips, 70 percent of VMT Unit is a score up to 100 Work: access to jobs or a subset of jobs 20 percent of trips, 30 percent of VMT Unit is jobs 9/21/16 Accessibility and Trip-making 17

19 Destination Types Target Weight Restaurants, coffee shops, bars, pubs, wineries, and night life 8 40 General retail, book stores, and department stores 4 15 Groceries 2 15 Errands: Banks, pharmacies, and hardware stores 3 10 Parks, recreational areas, campgrounds, and golf courses 2 10 Schools 2 5 Cultural attractions, entertainment, and museums 1 5 9/21/16 Accessibility and Trip-making 18

20 9/21/16 Accessibility and Trip-making 19

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23 9/21/16 Accessibility and Trip-making 22

accessible by transit Before After 5 min 0 0 10 min 1 1 15 min 1 1 30 min 71 1,183 45

24 accessible by transit Before After 5 min min min min 71 1, min 189 9, min ,184 Decay 114 5,779 9/21/16 Accessibility and Trip-making 23

25 Madison subdivision (approved) 9/21/16 Accessibility and Trip-making 24

26 Madison subdivision (original) 9/21/16 Accessibility and Trip-making 25

27 Station accessibility 9/21/16 Accessibility and Trip-making 26

28 Potential accessibility improvement 9/21/16 Accessibility and Trip-making 27

29 Impact score (based on households + jobs) 9/21/16 Accessibility and Trip-making 28

30 Virginia H.B. 2 (Smart Scale) 9/21/16 Accessibility and Trip-making 29

31 Caltrans Strategic Plan 9/21/16 Accessibility and Trip-making 30

32 Maryland mode share and VMT Transit accessibility for work Transit mode share for work 9/21/16 Accessibility and Trip-making 31

33 Maryland mode share and VMT Mode split prediction Mode choice at origin Auto % = (1.38E-07) MMA-A - (1.45E-06) MMA-T ( 6.71E-07) MMA-W Transit% = (1.23E-07) MMA-A + (1.41E-06) MMA-T + ( 9.48E-06) MMA-W Walk% = (2.98E-07) MMA-T + (1.89E-06) MMA-W Mode choice at destination Auto % = (4.54E-08) MMA-A - (8.45E-07) MMA-T ( 5.77E-06) MMA-W Transit% = (8.63E-08) MMA-A + (7.88E-07) MMA-T +( 4.75E-06) MMA-W Walk% = (1.20E-07) MMA-T +( 1.15E-06) MMA-W Where: MMA-A = Multimodal Accessibility Score for Auto MMA-T = Multimodal Accessibility Score for Transit MMA-W = Multimodal Accessibility Score for Walk 9/21/16 Accessibility and Trip-making 32

Measuring trip-making Anonymous GPS data Precise information not in travel demand models or traffic counts Summary More than 3 million trips per day

34 Measuring trip-making Anonymous GPS data Precise information not in travel demand models or traffic counts Summary More than 3 million trips per day in NOVA 51% < 5 miles 24% < 2 miles 8% < 1 mile 44% of short trips are during peak periods Streetlight Data 9/21/16 Accessibility and Trip-making 33

35 Methods 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). 9/21/16 Accessibility and Trip-making 34

36 Denver: Short trips on freeways 7/29/16 Trip-making and accessibility 35

37 Denver: Potential Light Rail Trips 7/29/16 Trip-making and accessibility 36

38 Denver: Short internal trips 7/29/16 Trip-making and accessibility 37

39 Northern Virginia: Case studies 9/21/16 Accessibility and Trip-making 38

40 Northern Virginia: Tysons Corner 9/21/16 Accessibility and Trip-making 39

41 Northern Virginia: Tysons Corner Dulles Toll Road M M M M Opportunities Bicycle and pedestrian improvements Street and parcel connections Other local transportation options 9/21/16 Accessibility and Trip-making 40

42 Northern Virginia: Tysons Corner Benefits Enable walkable, transitoriented development Remove 3.8 million vehicle trips per year (1 million hours) Save $11.5 million in traveler costs per year Eliminate 8,400 tons of carbon emissions per year Costs $2.7 to 3.2 million (annualized) Circulator shuttle Street improvements and connections Bike share TDM and parking management 9/21/16 Accessibility and Trip-making 41

43 Northern Virginia: George Mason University 33% of trips 9/21/16 Accessibility and Trip-making 42

44 George Mason University Opportunities Off campus connections by foot, biking and transit Parking management Walkable development in surrounding area 9/21/16 Accessibility and Trip-making 43

45 Northern Virginia: George Mason University Benefits Improve multimodal access to campus Remove 460,000 vehicle trips per year (82,000 hours) Save $500,000 in traveler costs per year Eliminate 390 tons of carbon emissions per year Costs $0.9 to 1.0 million (annualized) Bike and pedestrian improvements Local shuttle/transit service TDM and parking management 9/21/16 Accessibility and Trip-making 44

46 Northern Virginia: Van Dorn Street Metro 9/21/16 Accessibility and Trip-making 45

47 Van Dorn Street Metro Van Dorn Street 9/21/16 Accessibility and Trip-making 46

48 Van Dorn Street Metro Opportunities Address accessibility needs without adding local traffic Limited-use crossings (bikes, pedestrians, etc.) M Van Dorn St Metro 9/21/16 Accessibility and Trip-making 47

49 Northern Virginia: Van Dorn Street Metro Benefits Improve multimodal access to station Remove 152,000 vehicle trips per year (24,500 hours) Save $155,000 in traveler costs per year Eliminate 113 tons of carbon emissions per year Costs $0.5 to 0.6 million (annualized) New infrastructure Modest increase in TDM 9/21/16 Accessibility and Trip-making 48

50 Opportunities for development Active transportation trip-making Accessibility and trip-making together Standards and practices Dissemination of tools and data Automation Advanced applications, e.g. modeling 9/21/16 Accessibility and Trip-making 57

51 Equity framework Data / input Accessibility measures (Sugar Access) Access to destinations Unit costs (e.g., auto ownership, transit costs) Affordability Transportation Livability Score Crash data Health / safety 9/21/16 Accessibility and Trip-making 58

52 Transportation Livability Score 9/21/16 Accessibility and Trip-making 59

53 Eric Sundquist SSTI Managing Director /21/16 Accessibility and Trip-making 60

Operationalizing Accessibility

Operationalizing Accessibility March 30, 2017 Chris McCahill State Smart Transportation Initiative Matt Pettit Citilabs State Smart Transportation Initiative A network of reform-oriented state DOTs, founded