Data Sources for NZ Transport Models. Nick Sargent Dunedin City Council for MoT/ NZTA and Grant Smith (Traffic Design Group)

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1 Data Sources for NZ Transport Models Nick Sargent Dunedin City Council for MoT/ NZTA and Grant Smith (Traffic Design Group)

2 Outline Preliminary results from an NZTA Research Project to determine whether the New Zealand Household Travel Survey (HTS) can be used as a common evidence base for transport modelling purposes in NZ in the future A review of the new HTS questions Comparing historic HTS data and understand differences by region Some lessons learned from current and historic travel survey experiences

3 The NZ HTS sample National random sample n=2,200 fully completed households per annum (travel days in brackets)

4 Research Project Stage 1 Obtain Data Stocktake P1 Network Models Review HTS Questions Compare against Historic Data Demonstrate Calibration Stage One Report

5 A review of the new HTS questions and techniques 7 days, online travel diary with option of GPS logger Overall data quality is very good, a combination of GPS and interviews produces good data Some small data cleaning issues will be fixed in future data deliveries Originally was not recording start activity at start of day, has been fixed on advice of this project Current sample sizes and under sampling mean some weighting factors are less than optimal, this issue will reduce as sample builds over time.

6 HTS Technique Changes Pen and paper/phone/capi 1day/ 2days Dunedin 2014 GPS only, issues with GPS wake up Canyon effects Accuracy effects Imputation required NZHTS 2015 onwards 7 days, issues with Burden (7 days puts people off) High non-response rate Identifying non-travel vs soft non-response

7 City HTS in NZ Years surveyed Auckland Hamilton /Waikato Tauranga 1996 Heretaunga 1978 Wellington Christchurch Waimakariri 2001 Dunedin Invercargill 1967 NUTS 1978 Ministry of Transport (MoT)

8 Daily trip rates per person for each City Early 1970s 1978 survey Years surveyed Late 80s and early 90s 2001 Mid 2000s Post 2010 Auckland Hamilton /Waikato Tauranga Heretaunga Wellington Christchurch Waimakariri 2.83 Dunedin NUTS (6 city average) 3.36 MoT / 4.21

9 Trips per person by household category MoT and 2016 MoT MoT

10 Trips per person by household category Dunedin 2014 Dunedin

11 Trips per person by household category car ownership/size Trip Rates by car ownership Wgtn Auck Chch Wai Dndn MoT MoT 16 MoT Trip Rate by Household size Wgtn Auck Chch Wai Dndn MoT MoT 16 MoT

12 Trips per person by household category all surveys combined Trips per household - all surveys

13 Trips per person by age - overall and each survey Trips per Person by Age and Gender y = 0.002x x x x x R² = Male Female Total Poly. (Total) Trips per person by age band Wgtn Auck Chch Waik Dndn MoT 03 MoT 16 MoT 17

14 Mode share by survey Mode Share by Survey 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Wgtn Auck Chch Waik Dunedin MoT Car drivers Car passengers Public Transport Other Modes

15 Conclusions from the data Remarkable degree of consistency in the person trip rates per person across all the surveys Generic trips generation models could be built from the national data Very strong relationship between trips per person and age band possible control for total generation Consideration should be given to using trips per person in each category, rather than the more traditional trips per household.

16 Conclusions about method The survey methodology is the most important determinant of data quality The best data comes from the surveys where every member of the household is subjected to a face-to-face interview The issue of under-reporting is significant GPS has the potential to improve data quality note however Dunedin experience MoT survey a good combination with GPS as memory jogger 7 days however appears to be an imposition

17 Calibration The MoT data would enable any of the distribution and mode split model forms used in New Zealand to be calibrated Caveat is that the sample size in the area of the local model must be sufficient for the model builder to have confidence on the observed matrices that are extracted from the data

18 Research Project Next Steps Stage 2 Stocktake P2 Other models Hierarchy of models Capability & Resourcing Stage Two Report

19 Household Travel Knowledge Hub Community interested in household/personal travel data and data sources Not just the Household Travel Survey We are interested in ideas for seminars/people interested in getting more involved Jennifer McSaveney (MoT) if you wish to know more/sign up

20 For more national travel survey information