Erfurt, April

Transcription

1 Erfurt, April

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3 OVERALL GOAL: Increase & improve cycling in Central Europe Scope: Seven countries, 16 areas (14 cities), 3 years Diverse Strategy: Media, Resources, Events, Trainings; Pilot Project Investments, Strategies; Engaging political process, creating dialogue & understanding; Data Gathering & Scientific Analysis» Policy Making

4 The analysis consists of three primary components: SWOT analysis (Strengths, Weaknesses, Opportunities and Threats); Detailed Mobility Street Survey Indicators, consisting of official data and their relationships, correlated with observed cycling levels Outputs include: Key findings include modal share and cycling index Cyclists and Public Transport users experiences Future modal change by scenarios

5 Our top findings

6 More bikeways = MORE CYCLING Based on official indicator data, and modal split from survey.

7 The message is clear: Building more bikeways is required for creating more cycling. No matter the causality, to ignore bikeways is a HUGE mistake.

8 Goal of low-cost, easily replicable method Detailed mobility survey (Mode share and more from quick one-page, survey, 4-6 min. w/guide. Many cities need this!) SWOT based on BYPAD (Gets stakeholders talking, a key step) Spatial GIS analysis with OpenStreetMap (Free global geographic data in constant development by hundreds of contributors)

9 Survey Implementation Characteristics Cost per survey < 2 euros Including gadgets and shirts (35%) Can be done by volunteers Time to record approx 4.5 minutes Minimum 48 hours field presence, 3 staff Target of 1500 surveys for > 1000 usable Ensure 2%precision

10 Survey can be replicated many places Benefit of consistent method (Allows unified approach, more reliable comparisons and scientific findings) Low-cost and quick (Even volunteers can conduct this, if they are committed to following the methodology)

11 Corrections required A survey must be representative of the population. An extensive effort was made to adjust the survey where necessary. Weighting assumed that the demographics of the traveling public are proportional to population demographics. The age groups are important (young, adult, older). Female to Male ratio is important. How many surveys: more makes it better. Where were they asked, and who was asked? And what do we know about how many drivers, cyclists, etc.

12 Bias minimized, directed against cycling Detailed methodology manual to prevent bias Coverage Errors Nonresponse Errors Measurement Errors Question wording errors Question ordering errors Interviewer Effect Errors Incentivization Errors Failed Reporting of Location/Time Assumptions and Algorithms

13 Sometimes there was a big difference Not enough seniors.

14 Another example, one step closer.. Not enough minors.

15 Female to male ratio was relatively good..

16 Components of Survey: Residence Block Customised to city.

17 Components of Survey: Travel Type Block

18 Components of Survey: General Mobility Block

19 Components of Survey: Future Transport Block Option to customise based on nature of inquiry.

20 Components of Survey: Personal Demographics Block Not asked, simply recorded by survey administrator as perceived. Note economic status ignored (cyclists are generally economically diverse, question would be intrusive, but lose a dimension).

21 Survey Modal Split

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23 Comparing survey cycling with official This is a big difference! Only Partner Places with both survey and official data are shown.

24 Confidence of preliminary results?

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26 So, who were these cyclists? Typology by frequency & potential: Regular cyclists All cyclists Potential Regular cyclists

27 What is a regular cyclist? Regular cyclists are the share of cyclists who use the bicycle regularly for any reason, or who use it sometimes for a regular purpose (work or shopping). Different from modal split here we are counting bicyclists, not bicycling. Modal split typically only uses an individual's largest trip.

28 Regular cyclists: Higher than modal split because we are looking at travelers, not trips

29 What are our cyclists experiences? Safety? Weather? Hills? Bike theft? Good bike routes?

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31 Do we cycle in the cold and rain?

32 Do we cycle in the cold and rain?

33 Yes, we can cycle in cold and rain.. Photo of a cyclist, by a cyclist. Bologna, Italy: blizzard, winter Photo by Jason Meggs.

34 Do we cycle with hills? Is cycling of hills cultural, like cycling in the rain? San Francisco has a booming culture of cycling despite steep hills. Despite its hilly terrain, San Francisco has the fourth highest share of commuters who bike to work among major U.S. cities. Photo by Frank Chan, San Francisco Bicycle Coalition. (Page 100, Alliance for Walking & Cycling 2012 Benchmarking Report.)

35 Yes, but we cycle less with hills..

36 Put another way, cycling climbs a hill..

37 Can we find parking?

38 Do we find a good daily bicycle route?

39 Potential Cyclists

40 What is a Potential Regular Cyclist? Potential Regular Cyclists are those people who don t ride regularly, but COULD ride because their regular trip distance is small enough. (All walkers are potential regular cyclists.)

41 Based on distance to work and not refusing the cycle.

42 Predictions

43 Predictions

44 Predicting Future Cycling: Survey Scenarios (Stated Preferences) Modeled Relationships

45 Survey preferences: Admittedly predicting behavior based on respondents' beliefs is unreliable. However, potential is likely under-reported for any who have not experienced a cycling culture and city.

46 Survey scenarios: Based on what respondents say would get them cycling regularly Scenario 1 Cycle ways / traffic limitations, ALL regular travel path; Secure bicycle parking at all destinations Scenario 2 All of the above, and: Cycle hire facilities at all destinations Scenario3 All of the above, and: Bike path with sun, wind and rain protection

47 Increased Cycling, per Scenario

48 Predictions by Indicator Relationships More bikeways, more bikers.

49 LARGER CITIES: a stronger relationship (Cities defined as population >= 100K)

50 TOWNS: also stronger, different slope (Towns defined as population < 100K) More bang for the buck in larger cities but still cost-effective for towns.

51 Projected Benefits Carbon Reductions Health Economic Benefits Local economic benefits And many more to be explored!

52 Carbon reductions, three scenarios

53 Health Economic Benefits Indicator & Survey Data Target Bikeways for 15% Cycling Foundational Data Košice Michalovce SNV Prague 5 Koper Velenje Budaörs Population Bikeways km Cycling Index (Raw) E E E Fit Line Slope (city & town) Marked Bikeway 84,000 66,000 60,000 91,000 13,000 13, ,000 Physical Bikeway 200, , , , , , ,000 Share Adult Workers 64.30% 64.50% 55.10% 62.70% 42.30% 50.10% 75.80% Population Adult Workers Share Biker and Worker 4.00% 5.70% 4.60% 7.30% 10.60% 17.90% 5.50% Share Regular Bike-Work 2.30% 3.40% 2.70% 3.00% 2.10% 3.30% 1.90% Target 15% Košice Michalovce SNV Prague 5 Koper Velenje Budaörs Pop. Reg. Bike Workers Target Cycling Index (Raw) Note: assumptions were made for Prague, Koper and Budaörs to correct/provide their cost data Target Total Bikeway km Note: only adult workers and cyclists (age 17-59) are counted here; work includes commuting to study (school) New km needed Cost, Marked Bikeways 9,799,811 1,910,414 1,774,703 3,390, , ,362 3,281,699 Cost, Physical Bikeways 23,332,883 4,341,851 6,625,558 14,901,115 5,765,137 2,947,956 3,750,513 HEAT (Target 15%) Košice Michalovce Middle SNV cost (half each) Prague 16,566,347 5 Koper 3,126,132 Velenje 4,200,131 Budaörs 9,145,560 3,155,102 1,633,659 3,516,106 Current Bike Commuters Future Bike Commuters Formula: x2 = (y2-y B*x1)/B where x1 is initial 4976 Cycling Index, x2 is 4241 target CI, y1 is initial cycling %, B is slope, y2 is target = 15% Average Cycling/Day (hours) Note: all these calculations assume that marked and physically separated bikeways have the same effect on cycling levels Average Cycling (minutes) Time to Max Uptake Mortality Rate (country) Local Value of Statistical Life 1,574,000 1,574,000 1,574,000 1,574,000 1,574,000 1,574,000 1,574,000 Time period for benefits Discount Rate 5.00% 5.00% 5.00% 5.00% 5.00% 5.00% 5.00% Average Annual Benefit 35,387,000 6,421,000 5,185,000 6,591,000 4,247,000 3,406,000 2,002, ,092,000 8-yr Total Benefit 51,366,000 41,481,000 52,730,000 33,974,000 27,247,000 16,017,000 Max annual benefit (yr 11) 81,583,000 14,803,000 11,954,000 15,196,000 9,791,000 7,852,000 4,616,000 Current Value, 8-yr avg Benefit 4,759,000 3,843,000 4,885,000 3,147,000 2,524,000 1,484, ,808,000 38,069,000 30,743,000 39,080,000 25,179,000 20,193,000 11,871,000 Total 8-yr savings (current val) Benefit-Cost Ratio 9.91: :1 7.32:1 4.27:1 7.98: :1 3.38:1 Health Economic Benefits of Lives Saved Using WHO Europe's HEAT tool,

54 Bikeways for 15% target already VERY cost effective!

55 This was a very conservative scenario: Only regular commuters, ages years Assumed 5 years to build bikeways! (we can do better!) Only counted benefits for 8 years (for 2020, based on Charter of Brussels - yet maximum benefits reached in year 11) Only for economic value of life ( all cause mortality ) ignoring MANY other benefits: health, social, economic, environmental, etc.,

56 Bikeways for 30% target even better!

57 Other findings: effects of investments What s the right balance: PT, Cycling and Walking? Very important for modeling future scenarios, e.g., GHG emissions as well.

58 Dream Goals: Online Tool produces BICY report Automatically, any city Influence policy, real results OpenSource code freely available Survey Analysis OSM processing Method replicated widely, helps fill bicycle data vacuum

59 Publications Unified, Low-Cost Analysis Framework for the Cycling Situation in Cities. Joerg Schweizer, Jason N. Meggs, Nazanin R. Dehkordi, Frederico Rupi, Anton Pashkevich. International Journal of Civil and Environmental Engineering An Analysis Framework to Assess Automobile, Public Transport and bicycle usage between West and East Europe: A Comparative Survey. Joerg Schweizer, Jason N. Meggs, Nazanin R. Dehkordi, Federico Rupi, Anton Pashkevich Can PRT overcome the conflicts between public transport and cycling? J. Meggs, F. Rupi, J. Schweizer Results of the BICY project: modeling cycling response to infrastructure investments. Joerg Schweizer, Jason N. Meggs, Nazanin R. Dehkordi, Federico Rupi, Anton Pashkevich. Cycling Research International, Vol 2 (2012), (forthcoming). Bicycle City or Transit City? Effects and Limits of Sustainable Transport Investment Choices. Meggs, J, Schweizer, J (forthcoming) Cost-Benefit Analyses of Prospective New Bikeways in Central Europe: Applications of the BICY Methodology. Meggs, J, Schweizer, J (forthcoming)

60 Our reports will be online!

61 CONCLUSION: Build it and they will come.

62 CONFERENCE FINALE: Prague, January 17, 2013 CULTURE CHANGE: INCREASING CYCLING IN CENTRAL EUROPE

63 Current Focus: TRANSNATIONAL STRATEGY THANK YOU! Questions welcome, now and in the future: Jason N. Meggs (presenting), Joerg Schweizer DICAM Transport Engineering Group University of Bologna joerg (office) (mobile) skype: jasonmeggs joerg.schweizer.distart