Contribution of public transport to urban accessibility in the Netherlands

Transcription

1 Contribution of public transport to urban accessibility in the Netherlands Ambrosius Baanders ECORYS, Rotterdam Paul van Beek & Sander van der Eijk Goudappel Coffeng, Deventer

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3 increasing congestion decreasing accessibility of economic centres

4 increasing congestion decreasing accessibility of economic centres Q: What is the present role of public transport in serving the important economic centres and how can public transport help to alleviate car congestion problems?

5 study commissioned by NL Ministry of Transport to ECORYS and Goudappel Coffeng objective: make photo of current contribution of PT estimate potential to increase contribution of PT

6 method [1] existing modelling tools insufficient combination of modelling tools and local expertise

7 method [2] preliminary choices: current situation transport model base years morning peak: 07:00 09:00 twelve regions focus on economic centres in urban areas trips relevant for public transport

8 method [2] preliminary choices: current situation transport model base years morning peak: 07:00 09:00 twelve regions focus on economic centres in urban areas trips relevant for public transport

9 method [2] preliminary choices: current situation transport model base years morning peak: 07:00 09:00 twelve regions focus on economic centres in urban areas trips relevant for public transport

10 The twelve urban regions studied

11 method [2] preliminary choices: current situation transport model base years morning peak: 07:00 09:00 twelve regions focus on economic centres in urban areas trips relevant for public transport

12 Levels of the analysis and relevant trips 100% Total number of arrivals per region 50-80% Dispersed trips (not linked to the cities) Arrivals in the cities 20-50% Arrivals outside the Economic Centres Arrivals in the Economic Centres 10-45% Trips of < 2,5 km and streams of <20 trips Arrivals relevant for public transport Estimation of potential

13 method [2] analysis by: clusters of cities by size 300, ,000 50,000 14,000 inhabitants market segments

14 The market segments within the urban area from another region 4

15 method [3] workshops: participants: experts from local / regional stakeholders making estimates of effects with the help of an interactive spreadsheet

16 method [3] steps in the workshops: 1. verify the data 2. select the measures ( policy dials ) 3. estimate the potential growth relative to current PT volume 4. feedback on the results

17 method [3] Origins of morning peak trips to Utrecht Centre-North number of trips > % share PT

18 method [3] Input data per economic centre

19 method [3] steps in the workshops: 1. verify the data 2. select the measures ( policy dials ) 3. estimate the potential growth relative to current PT volume 4. feedback on the results

20 The policy dials Quality of public transport Parking policy Public transport fares Mobility management Intermodal chaining Marketing and image

21 method [3] Selecting the policy dials

22 Mixing console policy dials method [3] Tuning the policy dials PT Quality Parking restr. PT Fares Mob. manag, Marketing Interm. chains Image Spatial pol.

23 method [3] steps in the workshops: 1. verify the data 2. select the measures ( policy dials ) 3. estimate the potential growth relative to current PT volume 4. feedback on the results

24 method [3] steps in the workshops: 1. verify the data 2. select the measures ( policy dials ) 3. estimate the potential growth relative to current PT volume 4. feedback on the results

25 method [3] Current PT share and potential for growth

26 method [3] PT trips affected by each of the measures

27 method [3] Contribution of each of the measures to potential PT share growth

28 results: the photo level of the regions % of trips have destination in urban area all modes: work trips % education trips % other trips % public transport: work trips %, large cities ~ 62 % education trips %, large cities ~ 33% other trips 3 5 %

29 level of the cities: shares of the market segments and shares of PT other city outside within urban area in region regional region City cluster 1 results: the photo PT 23% PT 33% PT 21% PT 34% City cluster 2 PT 7% PT 18% PT 12% PT 23% City cluster 3 PT 8% PT 23% PT 18% PT 28% City cluster 4 PT 2% PT 11% PT 7% PT 13%

30 results: the photo level of the economic centres share of the market segments by economic centre of trips relevant for PT (> 2.5 km) Market Market Market Market Total all segment 1 segment 2 segment 3 segment 4 segments within urban from other from within from another area city in region region region City centre in cluster 1 69% 12% 6% 13% 100% City centre in cluster 2 49% 13% 27% 11% 100% City centre in cluster 3 45% 11% 33% 11% 100% City centre in cluster 4 34% 13% 29% 24% 100% Office parks 44% 13% 28% 14% 100% Commercial estates 58% 11% 18% 13% 100%

31 results: the potential Importance attributed in the workshops to the policy dials City centre Office park Commercial estate Large city Small city Quality of public transport supply Parking regime Public transport fares Mobility management 3 3 Intermodal chaining 2 3 Marketing and image

32 results: the potential Potential for PT share increase

33 results: the potential Contribution of the policy dials to the potential

34 conclusions current contribution What is current role? Flows within the cities / urban areas Flows from other regions What is explanation of differences? Differences in local circumstances Influence of land use patterns? Role increases with size of the urban area Which travel purposes? Work = 50%+, education = 50%-. Largest cities: work = larger share

35 conclusions estimation of the potential What is expected potential? Between 1 % and 10 % of total trips to economic centres Increase at the expense of which mode? The car (bicycle > 2.5 km?) What measures contribute? Improvement of PT supply quality Makes tightening of parking regime possible Mobility management, intermodal chaining, marketing Fares not important Relationship between the measures? Dials cannot be turned independently Tuning Role of the train? larger in largest cities varies elsewhere due to local network configuration

36 conclusions the method: combining models and expert knowledge Worked well Was a combination of several benefits: models used that were owned by the regions = own tools expertise in the regions used: clear added value to model results outcomes were trusted, because not a black box

37 conclusion for AMTU: continue to study

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