![CALCULUS
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
Temporal dimension
Travel time varies temporally -> temporal variability in accessibility
• Dynamic accessibility
• Time-continuous accessibility
(Owen & Lewinson, 2017)
(Moya-Gómez et al., 2017)
Owen & Lewinson (2014): improvement
of the [accessibility] model due to
application high-temporal resolution
Boisjoly & El-Geneidy (2016): high
correlation between all tested models
no significant improvement of a model
≠
Kaza (2015): advocates for systematic study of the time resolution
?
19/06/2018](https://image.slidesharecdn.com/m201806nectarlyon-190815184424/85/The-impact-of-temporal-resolution-on-the-precision-of-accessibility-measurement-4-320.jpg)
The impact of temporal resolution on the precision of accessibility measurement
- 1. The impact of temporal resolution on the precision of accessibility measurement CALCULUS 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 Marcin Stępniak John P. Pritchard, Karst T. Geurs & Sławomir Goliszek 19/06/2018
- 2. CALCULUS 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 CAlCULUS project Causes and Consequences of low urban accessibility. Defining proper policy responses CAlCULUS project Causes and Consequences of low urban accessibility. Defining proper policy responses Introduction 19/06/2018
- 3. CALCULUS 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 Temporal dimension Travel time varies temporally -> temporal variability in accessibility • Travel time to city centre • Morning peak-hours (6:30 – 8:30) • Starting time: every 5 minutes 19/06/2018
- 4. CALCULUS 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 Temporal dimension Travel time varies temporally -> temporal variability in accessibility • Dynamic accessibility • Time-continuous accessibility (Owen & Lewinson, 2017) (Moya-Gómez et al., 2017) Owen & Lewinson (2014): improvement of the [accessibility] model due to application high-temporal resolution Boisjoly & El-Geneidy (2016): high correlation between all tested models no significant improvement of a model ≠ Kaza (2015): advocates for systematic study of the time resolution ? 19/06/2018
- 5. CALCULUS 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 Temporal dimension of accessibility Temporal dimension Temporal variability Temporal resolution 19/06/2018
- 6. CALCULUS 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 Literature review: temporal resolution Temporalresolution Single departure time Several departure times Temporal resolution • El-Geneidy et al. 2016 • Guthrie et al. 2017 • Widener et al. 2015 Variability Average • Jäppinen et al. 2013 (9:00, 20:00) • Boisjoly & El-Geneidy 2016 (8:00, 9:00, 10:00, 11:00) • Kerkman et al. 2017 (8:00, 8:07, 8:18 am) • Salonen & Toivonen, 2013 (2 peak + 2 peak-off) • El-Geneidy et al. 2015 (1-hour resolution) • Legrain et al. 2016 (1-hour resolution) • Stępniak & Goliszek 2017 (15´ resolution) • Järv et al. 2018 (12’ resolution) • Fayyaz et al. 2016 (10´ resolution) • Fransen et al. 2015 (5´ resolution) • Farber et al. 2014 (1´ resolution) • Owen & Lewinson 2015 (1’ resolution) 19/06/2018
- 7. CALCULUS 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 Research questions 1. What is an impact of the decrease of temporal resolution on the precision of travel time measurement? 2. How (to what extent) the decrease of temporal resolution influences results of accessibility analysis? 3. To what extent the decrease of temporal resolution distorts conclusions derived from accessibility analysis? Temporal resolution Public transport (GTFS) car public transport 19/06/2018
- 8. CALCULUS 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 Case study: Szczecin (Poland) 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 Low regularity of public transport schedules Correlations of travel times between subsequent departure times Szczecin The Netherlands 19/06/2018
- 9. CALCULUS 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 Data: schedule-based travel time information • calendar_dates.txt • fare_attributes.txt • shapes.txt • frequencies.txt • transfers.txt ArcGIS® Network Analyst + ArcGIS® Network 19/06/2018
- 10. CALCULUS 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 Data: GTFS (public transport) ArcGIS Network 2145 OD nodes PT & walking network 287 026 edges Public transport network • 88 PT routes: • 12 tramway routes • 16 night-bus routes • 7 express routes • 1395 stops • Schedule for typical week-day (June, 2015) -> real travel time study walking speed (km/h) comment (Reyes et al., 2014) 3.2 Minimum typical speed for children aged 5-11 (Fransen et al., 2015) 4.0 Adult's average (Ritsema van Eck et al., 2005) 4.0 Distance as the crow flies (Hadas, 2013) 4.0 - (Nettleton et al., 2007) 4.8 - (Farber et al., 2014) 4.8 - (Willis et al., 2004) 5,3 mean walking speed of individuals (Reyes et al., 2014) 5.4 Maximum typical speed for children aged 5-11 (Krizek et al., 2012) 5.4 average walking speed for 14-64 year old Walking speed: 4.5 km/h 19/06/2018
- 11. CALCULUS 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 Travel time measurement & aggregation Benchmark value: 1-minute temporal resolution 1-hour long period of time (61 measurements): average / harmonic mean aggregation 4 cases: different frequency: 1) Very low frequency – during the night (2-3am); 2) High frequency during the morning peak hours (7-8am); 3) Daily low frequency during peak-off period (10-11am); 4) Evening low frequency (10-11pm). Applied lower temporal resolutions: - Every 2, 3, 4, 5, 10, 15, 20, 30 & 60 minutes 19/06/2018
- 12. CALCULUS 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 • Relation between frequency and precision • No visible change up to 5 minutes (MAE <0.8 min., MAPE < 1.8%) • Low impact up to 15 minutes (MAE < 2 min., MAPE < 3.5%) • High correlation (0.99 at 15 minutes) RQ1: Travel time comparison 19/06/2018
- 13. CALCULUS 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 RQ2: Accessibility comparison (1) Different weight of travel time: • travel-time-to-the-closest-facility • Cumulative opportunities • Potential accessibility Public services of different level of centrality: • High centrality: low number of providers, highly concentrated • Low centrality: high number, evenly distributed across the space 19/06/2018
- 14. CALCULUS 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 RQ2: Accessibility comparison (2: services) Type of nodes Spatial accuracy Accessibility measure Centrality level Data Origins* Centroid OD travel time NA Census tracks (1745) Destinations Address points travel time to the nearest provider High City council (1) Low Nurseries (30) Isochrone measure High Theatres (21) Low Specialized health care (169) Potential accessibility measure High Hospitals (9) Low Secondary schools (68) 19/06/2018
- 15. CALCULUS 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 RQ2: Accessibility comparison (3: measures) MAPE (%) MAE max diff. Corr. MAPE (%) MAE max diff. Corr. MAPE (%) MAE max diff. Corr. Temporalresolution Highcentrality Administration centre travel-time-to-the-closest- facility Theatres contour measure Hospitals (no. of beds) potential accessibility 5 min 1.3 0.5 5.6 0.999 3.7 0.2 7.0 0.995 0.9 10.8 70.3 0.999 10 min 2.3 0.8 12.1 0.997 6.6 0.4 16.0 0.988 1.7 19.8 143.2 0.996 15 min 2.7 1.1 14.2 0.996 8.6 0.5 16.0 0.980 2.1 24.6 177.2 0.994 20 min 3.8 1.5 22.6 0.993 12.1 0.8 17.0 0.971 2.8 32.1 217.8 0.991 30 min 4.3 1.7 25.5 0.990 13.9 0.9 17.0 0.964 3.5 40.8 276.7 0.985 60 min 6.0 2.5 39.7 0.980 20.3 1.1 17.0 0.947 5.0 55.6 383.9 0.974 Lowcentrality Nurseries travel-time-to-the-closest- facility Specialized health care contour measure Secondary schools (no. of classes) potential accessibility 5 min 0.8 0.2 6.8 0.999 4.4 1.7 28.0 0.996 1.0 2.1 13.7 0.999 10 min 1.4 0.3 13.6 0.997 9.8 2.8 42.0 0.992 1.7 3.8 26.5 0.997 15 min 1.6 0.4 15.1 0.997 10.4 3.5 41.0 0.990 2.3 5.0 35.3 0.995 20 min 2.0 0.5 21.0 0.995 16.2 4.6 53.0 0.985 2.9 6.3 43.7 0.993 30 min 2.5 0.6 22.1 0.991 16.8 5.2 58.0 0.981 3.8 8.1 65.2 0.988 60 min 3.0 0.7 19.9 0.989 23.6 7.0 73.0 0.967 5.4 11.5 97.8 0.978 19/06/2018
- 16. CALCULUS 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 RQ2: Accessibility comparison (4: measures) • The most affected: cumulative opportunity • Differences between resolutions: 10’-15’ << 15’-20’ • No visible impact of the level of centrality of services • Very high max differences (risk when looking for extreme cases) • High correlation (~0.99) 19/06/2018
- 17. CALCULUS 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 RQ2: Accessibility comparison (5: frequency) • Closest facility: low frequency (night period) is biased by walking time • Potential accessibility: direct relation between frequency and precision • Cumulative accessibility: low centrality biased by walking time; high centrality: direct relation between frequency and precision 19/06/2018
- 18. CALCULUS 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 RQ3: Interpretation (1: Ethical theories) Egalitarianism: Gini Sufficientarianism threshold 19/06/2018
- 19. CALCULUS 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 RQ3: Interpretation (2: Gini) 5 10 15 20 30 60 GINI Administration 0.000 0.000 0.000 0.001 0.001 0.003 0.287 Nurseries 0.000 0.000 0.000 0.001 0.002 0.003 0.396 Theatries 0.002 0.006 0.005 0.009 0.010 0.015 0.241 Health Care 0.000 0.001 0.001 0.003 0.000 0.001 0.444 Hospitals 0.001 0.001 0.001 0.001 0.002 0.005 0.130 Schools 0.000 0.001 0.001 0.001 0.003 0.007 0.151 • No significance difference 19/06/2018
- 20. CALCULUS 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 RQ3: Interpretation (3: threshold) • 15’ resolution – error ≤ 2.5% • No clear pattern Public service Accessibility measure Threshold Temporal resolution 5 10 15 20 30 60 Administration Travel-time- to-the-closest- facility 30 minutes 21 40 40 47 67 94 Nurseries 7 14 16 18 16 18 Theatries No facilities within 30 minutes 0 (no access within 30 minutes) 7 15 12 21 28 25 Health Care 17 25 40 33 49 57 Hospitals potential accessibility 20% the lest accessible units 16 33 37 39 47 65 Schools 26 34 44 47 46 60 19/06/2018
- 21. CALCULUS 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 RQ3: Interpretation (4: spatial distribution) • Proximity & high centrality: clear transition zone • No clear spatial pattern (random distribution) • Different patterns for all scenarios – random distributions 19/06/2018
- 22. CALCULUS 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 Conclusions • Very high correlations between benchmark and tested values (travel times & accessibility) • Frequency has an impact on the loss of the precision. • Accessibility measures: • Significant impact on contour measure; • hardly visible impact in case of proximity and potential accessibility. • Up to 5 minutes of temporal resolution – no significant impact on precision. • 15 minutes temporal resolution: seems to have the best trade-off between computational and precision: • < 1.8% in case of travel time; • <2.5% in case of accessibility measures (except contour measure); • < 1% in case of Gini and ~2.5% on average of thresholds • Hardly affected interpretation of accessibility analysis. • Except: extreme cases (maximum differences). 19/06/2018
- 23. CALCULUS 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 Thank you for your attention! 19/06/2018 marcinstepniak@ucm.es @marcin_stepniak ● @tGIS_ucm