Slides presented at the 2019 RSA Annual Conference Pushing Regions beyond their Borders in the session Transport Infrastructure Planning.

1. New data sources,
temporal variability and
identification of causes
of low urban accessibility
RSA Conference • Santiago de Compostela #RSASdC
Marcin Stępniak • Borja Moya-Gómez • Javier Gutiérrez Puebla • Amparo Moyano 07/06/2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761

2. Accessibility
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
• Accessibility is the potential of oportunities for interaction Hansen (1959)
• Accessibility is the extent to which land use
and transport systems enable (groups of) individuals or goods
to reach activities (or destinations)
by means of (a) transport mode(s)
• at various times of the day. Geurs & van Wee (2004)
• Accessibility as a freedom
• Accessibility as a livability Appleyard (2014)

3. Accessibility
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Limited
accessibility
social
exclusion
quality of
life
economic
activity
utilisation
of public
services
Sustainable
developme
nt
Air & noice
pollution
Urban Agenda
White Paper on Transport
5th Cohesion Report
Challenges for urban areas:
• sustainable development
• improvement of the quality of life
• reduction of transport-related air and
noise pollution
• social and spatial inequalities
Transport planning: shift from mobility-centered to accessibility-centered

4. Knowledge gap
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
accessibility
New data
New methods
Group 1: new
Group2:outcomes
Spatial patterns
Evaluation of transport investments
Equity
?
Aim:
to identify the (transport-related) mechanisms that underlie
disparities in accessibility level across the urban space

5. Accessibility constraints
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
jobs distribution
geographical constraints
quality of road network
congestion
routing scheme
frequency
vulnerability
Scenarios:
Euclidean distance
Network distance
Free flow speed
Average congestion
No waiting times
Average travel time
Travel time variation
best-case scenario
worst-case scenario
best-case scenario
worst-case scenario

6. Door-to-door approach
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
simple
•Road geometry
•Speed limits
intermediate
•Road geometry
•Speed limits
•Congestion
advanced
•Road geometry
•Speed limits
•Congestion
•Parking & walking
simple
•Route geometry
•Estimated speed
intermediate
•Route geometry
•Estimated / real in-vehicle time
•Estimated transfer & waiting time
advanced
•Route geometry
•Schedule-based in-vehicle time
•Schedule-based waiting time
•Walking (access / egress)
Publictransport
Based on: Salonen & Toivonen, 2013
Privatecar

7. Data sources (1): Madrid case study
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
• Accessibility calculated for all the metropolitan
area, but interpretation limited to the city
(avoid border effect)
• 584 transport zones (out of 1171 in metropolis)
• Area: 604 km2 population: 3.4 M
• Job distribution: central-peripheral division
Madrid case study

8. Potential accessibility
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Östh et al. (2014)
𝑓 𝑡𝑖𝑗 = exp (−𝛽𝑡𝑖𝑗)
Distance decay function: ’half-life’ approach:
• destination loses half of its attractiveness
at the observed median travel time
• OD matrix (trip purpose: commuting)
• Negative exponential function
•
• 𝛽 = 0.02230 (~31 minutes)
Accessibility to jobs:
• Travel time between all pairs of origin-destination nodes
• Greater impact of larger centres than smaller ones
• Diminishing importance of more distantly located destinations

9. Data sources (2): TomTom speed profiles
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
• Each edge has its individual speed profile
• For each departure time: origin-destination matrix
• Temporal resolution of speed profiles: 5 minutes
• Temporal resolution of origin-destination matrices: 15
minutes
• Free flow travel time
(benchmark to evaluate an impact of congestion)
• Door-to-door approach: in vehicle time +
10 minutes handicap (parking, walking etc.);
not applicable if walking is faster than car
Speed profiles (private cars)

10. Data sources (3): GTFS (public transport)
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Public transport network (5 modes):
• Metro (12 lines)
• Commuter trains (Cercanias: 10 lines)
• Light metro (tramway: 3 lines)
• EMT (Buses urbanos > 200 lines)
• Buses interurbanos (> 400 lines)
Schedule for typical week-day;
Temporal resolution: 5 minutes
No waiting time scenario: pseudo-GTFS
GTFS (General Transit Feed Specification)
http://datos.crtm.es/

11. Results (1): global
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761

12. Results (1): global
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Distance Car Public transport
Euclidean Network
Free
flow
Best Avg Worst
Max.
Freq
Best Avg
Network 97.4
Car
Free flow 66.8 68.6
Best 63.8 65.5 95.5
Avg 60.4 62.0 90.4 94.7
Worst 57.9 59.4 86.6 90.7 95.8
Publictransport
Max.Freq 56.6 58.1 84.6 88.7 93.7 97.7
Best 48.3 49.6 72.4 75.8 80.1 83.6 85.5
Avg 41.7 42.8 62.4 65.4 69.1 72.1 73.7 86.2
Worst 35.8 36.8 53.6 56.1 59.3 61.9 63.3 74.1 85.9

13. Results (2): spatial patterns
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Impact of congestion
• Inhabitants of which areas face reduced
accessibility due to congestion?
• Average car accessibility (7-10am)
vs Free flow accessibility (90.4%)
• Clear south/north division
• South: farther periferies – higher reduction
• North – partly mozaic pattern

14. Results (2): spatial patterns
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Public transport: routing scheme
• To what extent lack of direct connections
reduces accessibility by public transport?
• No waiting-times scenario
vs Euclidean distance-based accessibility
• No waiting-times scenario: 84.6% of Free flow
accessibility
• Central-periperal division
distorted by an existence of radial rail transport
(suburban trains)
• Visible node-effect around suburban
rail stations

15. Results (2): spatial patterns
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Public transport: intermodal disparities
• Inhabitants of which areas face reduced PT
accessibility in comparison to car accessibility?
• Average PT accessibility vs average car
accessibility (average: 69.1%)
• Mirrors the spatial pattern of PT routing
structure (correlation: 0.9)
• Visible impact of suburban rails & metro
(in particular: southern & western part of the
city)

16. Results (2): spatial patterns
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Impact of frequency
• Inhabitants of which areas have to adapt their daily
routines to PT schedules?
• PT worst-case scenario (7-10am)
vs PT best-case scenario (average: 74.1%)
& coefficient of variation (inversed for the sake of comparability)
• Center-peripery division
+ impact of metro (high frequency)

17. Results (2): Spatial patterns
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
Impact of congestion &
public transport alternative
• Only in some congested areas public transport
might be considered as an alternative
• Visible: central / periphery (congestion impact) &
south / north (public transport as an alternative)
• Importance of suburban rails
(in southern part, in particular)

18. Results (3): towards typology: clusters
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
variables
accessibility
FreeFlow Free-flow accessibility
impacts: private transport
congestion impact of congestion: Car_Avg / FreeFlow
Impacts: public transport
routing imppact of routing: FullFreq / Euclidean distance
mode_change impact of change of transport mode: PT_Avg / Car_Avg
frequency impact of frequency: PT_Worst / PT_Best
PT_VarCoeff variability of the accessibility by public transport

19. Results (3): towards typology: clusters
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
clusters
• 5 clusters delinieated based on 4 variables
• South (1 & 3): high congestion; moderate public transport;
differences: impact of frequency and accessibility level
• City centre (2): highest accessibility, limited impact of
congerstion and relatively good quality of public transport
• Periferies (4): moderate accessibilty and congestion
impact; poor quality of public transport
• North (5): low congestion, moderate accessibility and poor
quality of public transport (even though limited impact of
frequency)

20. Conclusions
RSA Conference 2019
This project has received funding from the European Union’s Horizon 2020 research and
innovation Programme under the Marie Sklodowska-Curie Grant Agreement no 749761
• Aplication of new data sources: speed profiles (cars) and GTFS (public transport)
to adress temporal dimension of accessibility
• Comparison of several scenarios of accessibility level to identify accessibility constraints
• The most important factor of limited accessibility:
intermodal disparties;
• Clear center-periphery and south-north division;
• High variability of public transport accessibility,
in particular in the peripheries
• Lower disparities: due to suburban trains and metro

21. http://www.ucm.es/tgis
Twitter: @tGIS_ucm
Thank you for your attention!
Marcin Stępniak
marcinstepniak@ucm.es • @marcin_stepniak