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The effects of road pricing on travel behaviour. The case of Milan

The effects of road pricing on travel behaviour. The case of Milan. Paolo Beria Ilaria Mariotti Ila Maltese Flavio Boscacci DAStU , Politecnico di Milano. STRUCTURE. Aim of the work Literature review on Road Pricing Data and methodology Descriptive statistics

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The effects of road pricing on travel behaviour. The case of Milan

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  1. The effects of road pricing on travel behaviour. The case of Milan Paolo Beria IlariaMariotti Ila Maltese FlavioBoscacci DAStU, Politecnicodi Milano

  2. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  3. AIM OF THE WORK Investigating the road pricing impact on travel behaviour at the urban scale. 1,198 Milan citizens have been surveyed (Green Move project).

  4. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  5. Road pricing theoretical literature Acceptability Effectiveness • WHAT: level of acceptability of the regulation and its determinants (Psychological and personal factors; fairness and clarity of the measure; certainty about the use of revenues; alternative travel modes) • WHEN: ex-ante for testing the feasibility of a toll introduction • WHAT: effectiveness of the toll in terms of congestion (congestion charge) and/or pollution (pollution charge) decreasing. • WHEN: ex-post in the few cities where it has been introduced: Singapore (1975); Bergen (1986), Oslo (1990) Trondheim (1991) and Stavanger (2001); London (2003); Stockholm (2006) and Gothenburg (2013); Milan (2008 pc, 2011 cc).

  6. Road pricing empirical literature Acceptability Travelchanges

  7. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  8. Methodology 1. Descriptive statistics 2. Multinomial logit model Three kind of explanatory variables: • Socio-demographic (individual and car fleet); • Travel behaviour; • Green Attitude.

  9. Explanatory variables Socio demographic Travelbehaviour Green Attitude

  10. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  11. Source: www.areac.it. Road pricing (AreaC) impact in MILAN LEV 0€ Source: www.areac.it.

  12. Socio – demographic variables Oil price sensitiveness Milan neighbourhoods

  13. Travel behaviour Carusefrequency Travelmotivation/matter Travelmodes

  14. Green attitude Carsharingmembership Carsharing peer-to-peer (attitudetowards) Nextcarchoice Carfleetfuel

  15. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  16. Results Group 1 • GROUP 1 reduced the use of the car to enter Area C zone • GROUP 0 • Thosewhohavenotreduced the useoftheircarsbecause: • they are notaffectedbyAreaC; • theypay the toll. SD TB GA

  17. Results Group 2 SD • GROUP 2 reduced the use of the car • GROUP 0 • Thosewhohavenotreduced the useoftheircarsbecause: • they are notaffectedbyAreaC; • theypay the toll. TB GA

  18. Gender is not always significant Permanent job (proxied by using the car to reach the work place) makes respondents less flexible Age proved to be significant Groups 1 and 2 tend to prefer LPT, and to use the car to reach the LPT stop The two groups share some features like price-sensitiveness, travel behavior, and green attitude. Owning Low Emission Vehicles is always negative and significant. COMMENTS

  19. STRUCTURE • Aim of the work • Literature review on Road Pricing • Data and methodology • Descriptive statistics • Multinomial logit results • Conclusions

  20. EFFECTIVENESS of the Area C program in car use reduction. The impact is not homogeneously distributed among users: Weaker groups tend to be more affected due to their price sensitiveness. LPT users as well are more likely to reduce their car use. EXOGENOUS factors (not investigated) A clear communication of the policy goals the use of the toll revenues The presence of a good LPT service The involvement of the citizens. CONCLUSIONS

  21. Thank you for your attention! Questions and suggestions are welcome. Ila Maltese DAStU – Politecnico di Milano ila.maltese@polimi.it

  22. Appendix • Q29. Le sue abitudini di mobilità sono state influenzate dall’introduzione a Milano dell’Area C? • Si, uso meno l’auto per entrare nell’area C • Si, uso meno l’auto per tutti gli spostamenti • Si, non uso più l’auto per i miei spostamenti • No, pago il ticket e non ho modificato per nulla le mie abitudini di spostamento • no, non sono influenzato se non marginalmente dall’area C • Q29.1 Lei ha detto che utilizza meno l’auto/ non utilizza più l’auto. Come si muove in città? Indichi una sola risposta • Mi muovo con i mezzi pubblici • Mi muovo con la bici • Mi muovo con la moto • Utilizzo una combinazione tra mezzi privati (bici-moto) e mezzi pubblici • Mi muovo a piedi

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