1. Department of Transport Presentation Dr. Aoife Ahern School of Architecture, Landscape and Civil Engineering University College Dublin “Perceptions of Inter-urban Public Transport in Ireland”

2. Project Description 2 elements to this project and 2 students funded: –Nigel Tapley: Using stated preference techniques in modal choice modelling –Gabrial Anandarajah: Developing Optimisation Models to Prioritise Transportation Projects for Investment

3. Stated Preference and Modal Choice – the Objectives To analyse the use of stated preference models to look at people’s travel choices and preferences. Determine passengers’ preferences and desires on inter-urban public transport.

4. Stated Preference Studies SP studies are used extensively in the UK to look at value of time. Prior to 1987 RP was more popular. Very few studies of value of time and passenger perceptions in Ireland.

5. Routes Chosen Dublin – Galway Dublin - Sligo

6. Survey Design Each survey had 2 parts: –RP and SP. –Passengers were asked to complete both sections. –Pilot study was carried out to choose variables and refine the survey design.

7. Main Study 2 types of SP questionnaire. –Ranking and the stated choice questionnaire. –3 forms of stated choice questionnaire: 5 choice set. 10 choice set. Wide-attribute questionnaire. –The 5 choice set questionnaire was distributed on the Sligo train, the Sligo bus and the Galway train. –The 10 choice set questionnaire was only issued on the Sligo train as was the wide-attribute questionnaire.

8. Choice Attributes Cost. Journey length.

9. Choice Attributes Frequency. Reliability. Presence of toilet facilities.

10. Results Most important attributes: –Journey length and cost. –Frequency and reliability had expected signs but were not significant in modal choice. Modal attribute was significant only once.

11. Value of Time SRR - €6.63/hour. €10.67/hour – €15.87/hour for train users. €11.30/hour for bus users.

12. Do People Respond in the Same Way to Questionnaires? 4 SP models from Sligo train route. Differences in models. SP data from 2 different routes and modes also pooled.

13. Results Data from 5 choice and 10 choice set could be pooled. Answered questionnaires in same way. Sligo wide-attribute and 5 choice se could be combined. Galway and Sligo routes could be combined. Train and bus users also found to have similar decision-making processes.

14. Choice/ranking The choice and ranking models could not be pooled.

15. Developing Optimisation Models to Prioritise Transportation Projects for Investment To develop investment-planning models to allow prioritisation of funds for improving city rail networks.

16. Models Used Optimisation models using Goal Programming Techniques. Multi-objective optimisation model to allow more than one optimal solution. These could then be ranked using the concept of an ideal solution.

17. Steps Involved Linear Program. Goal Program. Goal Programming Square Method. Multi-objective optimisation model.

18. Model 5 Multi-objective optimisation model developed using the concept of the ideal solution for getting more than one optimal solution and can be used when the weights for attributes are known and not known.

19. Method The developed models were applied to prioritise the railway projects which were identified and analysed by Department of Transport (DOT), Ireland and were ranked for investment based on net present value criteria by DOT.

20. Performance of Model 5 Matlab Easy for decision-makers to use. Only needs input data such as costs, constraints, attribute weights and number of optimal solutions needed.

21. Sensitivity Analysis Sensitive to user assigned weights of the attributes.

22. Advantages of Model 5 More than one solution: –First best, second best etc. Fulfil the search for balanced solutions.