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Contribution of public transport to urban accessibility in the Netherlands
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Transcript of Contribution of public transport to urban accessibility in the Netherlands
Contribution of public transport to urban accessibility in the Netherlands
Ambrosius Baanders
Paul van Beek & Sander van der Eijk
ECORYS, Rotterdam
Goudappel Coffeng, Deventer
increasing congestion
decreasing accessibility of economic centres
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?
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
method [1]
existing modelling tools insufficient
combination of � modelling tools and � local expertise
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
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
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
The twelve urbanregions studiedregions studied
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
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
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
The market segments
within the
urban area
from another
region
1
23
4
method [3]
workshops:
� participants: experts from local / regional stakeholdersstakeholders
� making estimates of effects with the help of an interactive spreadsheet
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
method [3]
Origins of morning peak trips to Utrecht Centre-North
number of trips >100
23 % share PT
Input data per economic centre
method [3]
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
The “policy dials”
• Quality of public transport• Parking policy• Parking policy• Public transport fares• Mobility management• Intermodal chaining• Marketing and image
Selecting the “policy dials”
method [3]
Mixing console policy dials
PT Quality Parking restr. PT Fares Mob. manag, Marketing Interm. chains Image Spatial pol.
“Tuning” the “policy dials”
method [3]
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
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
Current PT share and potential for growth
method [3]
PT trips affected by each of the measures
method [3]
Contribution of each of the measures to potential PT share growth
method [3]
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 %
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%
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%
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
Potential for PT share increase
results: the potential
Contribution of the “policy dials” to the potential
results: the potential
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
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
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
conclusion for AMTU:continue to study