contribution of public transport to urban accessibility in the netherlands
TRANSCRIPT
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Contribution of public transport to urban accessibility in the Netherlands
Ambrosius Baanders
Paul van Beek & Sander van der Eijk
ECORYS, Rotterdam
Goudappel Coffeng, Deventer
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increasing congestion
decreasing accessibility of economic centres
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increasing congestion
decreasing accessibility of economic centres
Q: What is the present role of public transportin serving the important economic centres
and how can public transport help to alleviatecar congestion problems?
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objective:
� study commissioned by NL Ministry of Transportto ECORYS and Goudappel Coffeng
� make “photo” of current contribution of PT
� estimate potential to increase contribution of PT
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method [1]
existing modelling tools insufficient
combination of � modelling tools and � local expertise
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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� focus on “economic centres” in urban areas� trips relevant for public transport
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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� focus on “economic centres” in urban areas� trips relevant for public transport
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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� focus on “economic centres” in urban areas� trips relevant for public transport
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The twelve urbanregions studiedregions studied
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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� focus on “economic centres” in urban areas� trips relevant for public transport
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Total number of arrivals per region
Dispersed trips (not linked to the cities) Arrivals in the cities
100%
50-80%
Levels of the analysisand relevant trips
Arrivals outside theEconomic Centres
Arrivals in the Economic Centres
20-50%
Trips of < 2,5 km and streams of <20 trips
Arrivals relevant for public transport
10-45%
Estimation of potential
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method [2]
analysis by:
� clusters of cities by size� clusters of cities by size
� market segments
300,000 100,000 50,000 14,000
1 2 3 4
inhabitants
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The market segments
within the
urban area
from another
region
1
23
4
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method [3]
workshops:
� participants: experts from local / regional stakeholdersstakeholders
� making estimates of effects with the help of an interactive spreadsheet
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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
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method [3]
Origins of morning peak trips to Utrecht Centre-North
number of trips >100
23 % share PT
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Input data per economic centre
method [3]
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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
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The “policy dials”
• Quality of public transport• Parking policy• Parking policy• Public transport fares• Mobility management• Intermodal chaining• Marketing and image
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Selecting the “policy dials”
method [3]
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Mixing console policy dials
PT Quality Parking restr. PT Fares Mob. manag, Marketing Interm. chains Image Spatial pol.
“Tuning” the “policy dials”
method [3]
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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
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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
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Current PT share and potential for growth
method [3]
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PT trips affected by each of the measures
method [3]
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Contribution of each of the measures to potential PT share growth
method [3]
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results: the “photo”
level of the regions
90 – 50 % of trips have destination in urban area
all modes:work trips 50 – 58 %work trips 50 – 58 %education trips 22 – 26 %other trips 20 – 23 %
public transport:work trips 56 – 53 %, large cities ~ 62 %education trips 43 – 44 %, large cities ~ 33%other trips 3 – 5 %
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within urban areawithin urban areaother cityother city
in regionin regionregionalregional
outsideoutside
regionregion
City cluster 1
PT 23% PT 33% PT 21% PT 34%
PT 7% PT 18% PT 12% PT 23%
level of the cities: shares of the market segments and shares of PT
results: the “photo”
City cluster 2
City cluster 3
City cluster 4
PT 7% PT 18% PT 12% PT 23%
PT 8% PT 23% PT 18% PT 28%
PT 2% PT 11% PT 7% PT 13%
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results: the “photo”
Market Market Market Market Total all
level of the economic centres
share of the market segments by economic centre oftrips relevant for PT (> 2.5 km)
Market segment 1
within urban area
Market segment 2 from other
city in region
Market segment 3 from within
region
Market segment 4
from another region
Total all segments
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%
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City centre Office park Commercialestate
Large city Small city
Quality of public transportsupply
1 2
4
3
Importance attributed in the workshops to the “policy dials”
results: the potential
Parking regime
Public transport fares
Mobility management
Intermodal chaining
Marketing and image
432 3
3
3 3 4
2 3
4 4 4 4
3
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Potential for PT share increase
results: the potential
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Contribution of the “policy dials” to the potential
results: the potential
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conclusions
current contribution
What is current role?� Flows within the cities / urban areas� Flows from other regionsWhat is explanation of differences?� Differences in local circumstances� Differences in local circumstancesInfluence of land use patterns?� Role increases with size of the urban areaWhich travel purposes?� Work = 50%+, education = 50%-.� Largest cities: work = larger share
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conclusions
estimation of the potential
What is expected potential?� Between 1 % and 10 % of total trips to economic centresIncrease at the expense of which mode?� The car (bicycle > 2.5 km?)What measures contribute?What measures contribute?� Improvement of PT supply quality� Makes tightening of parking regime possible� Mobility management, intermodal chaining, marketing� Fares not importantRelationship between the measures?� “Dials” cannot be turned independently � “Tuning”Role of the train?larger in largest cities� varies elsewhere due to local network configuration
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conclusions
the method: combining models and expertknowledge
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
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conclusion for AMTU:continue to study