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UNextEU 21 - PPTFuture of public transport in the era of emerging
modes
NEW MOBILITY IMPACTS
@UrbanismNextEU #UNextEU
1925 1970s 1983 1999 2000s 2014 2016 2019
Private transport
Public transport
SAE automation level 4+
L5 - sharingL3/4 - sharing
Level 5 automationLevel 3/4 automation
Source: KIM, Chaueur aan het stuur? Zelfrijdende voertuigen en het verk,, 2015)
• Modal shift from walking, cycling and public transport to automated private cars, (shared) taxi’s
• User acceptance has a large impact on results
• A strong mix of interventions is needed to keep areas accessible and liveable and to maintain a high share of ‘traditional’ public transport
L3/4 - no sharing L5 - no sharing
L5 - sharingL3/4 - sharing
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
M o
a re
a)
Car driver Car passenger Automated private car Automated taxi Automated shared taxi
Automated shared van Train Bus Tram Metro Bicycle Walking
Car less attractive Road pricing Parking rates Parking capacity → car free cities Higher car ownership tax
Public transport more attractive Higher frequencies Shared cars/bikes Hubs Shuttles
0%
20%
40%
60%
80%
100%
Road pricing 30 ct/km
Road pricing 15 ct/km
Road pricing 5 ct/km
No automated taxi
Mix sharing
M o
d a
l sh
a re
Car Car passenger Automated private car Automated taxi (not shared) Automated shared taxi
Automated shared van Train Bus Tram Metro Bike Walking
0
100
200
300
400
Road pricing 15 ct/km
Road pricing 5 ct/km
No automated taxi
0
Number of vehicles Vehicle kilometres Vehicle hours of delay distributor roads Vehicle hours of delay through roads Parking revenues
Reduced parking capacity in the city centres of Rotterdam (-30%), The Hague (-30%) and Delft (all street parking locations)
Extra hubs Close to the centre + shared bikes Further away from the centre + shared bikes
Modal split Reference Scenario
Egress modes Bike 11% E-bike 8% Traditional PT 82%
Source: TNO, Urban Tools Next, 2021)
1 1 1 2 3 2 1 3 2 2 5
8
18
29
50 55
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
N u
m b
er o
f p
ilo ts
6 8
2 3
Austria Belgium Denmark Estonia Finland France Germany Greece Ireland Italy Luxembourg Norway Poland Spain Sweden Switzerland NL UK
N u
m b
er o
f p
ilo ts
https://www.researchgate.net/publication/339916105_Autom ated_Buses_in_Europe_An_Inventory_of_Pilots_version_10
https://www.researchgate.net/publication/339916105_Autom ated_Buses_in_Europe_An_Inventory_of_Pilots_version_10
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Vehicle automation
Supervision Area Infrastructure Operations
Credit: Irene Zubin, PhD candidate TU Delft
Small scale pilots in protected environments
Focus: accessible, sustainable, safe and livable urban areas
LMS
D2D
UBI
Business models
Technical feasibility
Impact assessment
• Important to steer towards societal goals • From pilots to implementation
• Business/value case • Technical feasibility and monitoring • Mobility and environmental impacts
Snelder, M., Wilmink, Isabel, van der Gun, J., Bergveld, H.J., Hoseini, P., van Arem, B. (2019) Mobility impacts of automated driving and shared mobility – explorative model and case study of the province of north- holland, European Journal of Transport and Infrastructure Research, vol. 19, n. 4 Doi: https://doi.org/10.18757/ejtir.2019.19.4.4282.
Maaike Snelder, [email protected]
NEW MOBILITY IMPACTS
@UrbanismNextEU #UNextEU
1925 1970s 1983 1999 2000s 2014 2016 2019
Private transport
Public transport
SAE automation level 4+
L5 - sharingL3/4 - sharing
Level 5 automationLevel 3/4 automation
Source: KIM, Chaueur aan het stuur? Zelfrijdende voertuigen en het verk,, 2015)
• Modal shift from walking, cycling and public transport to automated private cars, (shared) taxi’s
• User acceptance has a large impact on results
• A strong mix of interventions is needed to keep areas accessible and liveable and to maintain a high share of ‘traditional’ public transport
L3/4 - no sharing L5 - no sharing
L5 - sharingL3/4 - sharing
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
M o
a re
a)
Car driver Car passenger Automated private car Automated taxi Automated shared taxi
Automated shared van Train Bus Tram Metro Bicycle Walking
Car less attractive Road pricing Parking rates Parking capacity → car free cities Higher car ownership tax
Public transport more attractive Higher frequencies Shared cars/bikes Hubs Shuttles
0%
20%
40%
60%
80%
100%
Road pricing 30 ct/km
Road pricing 15 ct/km
Road pricing 5 ct/km
No automated taxi
Mix sharing
M o
d a
l sh
a re
Car Car passenger Automated private car Automated taxi (not shared) Automated shared taxi
Automated shared van Train Bus Tram Metro Bike Walking
0
100
200
300
400
Road pricing 15 ct/km
Road pricing 5 ct/km
No automated taxi
0
Number of vehicles Vehicle kilometres Vehicle hours of delay distributor roads Vehicle hours of delay through roads Parking revenues
Reduced parking capacity in the city centres of Rotterdam (-30%), The Hague (-30%) and Delft (all street parking locations)
Extra hubs Close to the centre + shared bikes Further away from the centre + shared bikes
Modal split Reference Scenario
Egress modes Bike 11% E-bike 8% Traditional PT 82%
Source: TNO, Urban Tools Next, 2021)
1 1 1 2 3 2 1 3 2 2 5
8
18
29
50 55
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
N u
m b
er o
f p
ilo ts
6 8
2 3
Austria Belgium Denmark Estonia Finland France Germany Greece Ireland Italy Luxembourg Norway Poland Spain Sweden Switzerland NL UK
N u
m b
er o
f p
ilo ts
https://www.researchgate.net/publication/339916105_Autom ated_Buses_in_Europe_An_Inventory_of_Pilots_version_10
https://www.researchgate.net/publication/339916105_Autom ated_Buses_in_Europe_An_Inventory_of_Pilots_version_10
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Vehicle automation
Supervision Area Infrastructure Operations
Credit: Irene Zubin, PhD candidate TU Delft
Small scale pilots in protected environments
Focus: accessible, sustainable, safe and livable urban areas
LMS
D2D
UBI
Business models
Technical feasibility
Impact assessment
• Important to steer towards societal goals • From pilots to implementation
• Business/value case • Technical feasibility and monitoring • Mobility and environmental impacts
Snelder, M., Wilmink, Isabel, van der Gun, J., Bergveld, H.J., Hoseini, P., van Arem, B. (2019) Mobility impacts of automated driving and shared mobility – explorative model and case study of the province of north- holland, European Journal of Transport and Infrastructure Research, vol. 19, n. 4 Doi: https://doi.org/10.18757/ejtir.2019.19.4.4282.
Maaike Snelder, [email protected]
