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Transport, Travel and SHS Data

Transport, Travel and SHS Data. SHS Topic Report: Modal Shift. SHS Topic Report – Modal Shift. Aims of the research are: summarise key statistics on current ‘mode choice’ and perceptions of alternative modes Identify factors which affect behaviour of travellers in making mode choice.

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Transport, Travel and SHS Data

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  1. Transport, Travel and SHS Data SHS Topic Report: Modal Shift

  2. SHS Topic Report – Modal Shift • Aims of the research are: • summarise key statistics on current ‘mode choice’ and perceptions of alternative modes • Identify factors which affect behaviour of travellers in making mode choice. • The topic report will cover: • Car Ownership • Car vs Public Transport • Motorised vs Non Motorised Modes • Travel to School

  3. SHS Topic Report. Background • Traffic and congestion are growing. This has implications for economic, environmental and social costs, including longer journey times for people and products, reduced air quality, road accidents, impacts on health and contribution to climate change. • The Scottish Executive recognises that more needs to be done to encourage modal shift. • Scottish Household Survey data shows that among those who travel to work by car, 47% could use PT, but choose not to. The main reasons are Inconvenience, journeys take too long, lack of direct routes, the need to have a car at work and the cost.

  4. Car Ownership • Travel Diary Data (1999 to April 2003) shows car mode share is: • 20% from non-car owning household • 76% from households with one car • 86% from households with two or more cars • Using the SHS data it is possible to define car ownership in three ways: • Household Car Ownership • Car competition between adults in household • Car competition between licence holders in the household • The two forms of car competition, ‘Adults versus car’ gives a better (i.e. wider) partition than ‘Licence holders versus cars”, but neither are significantly different from the simple car ownership (C0, C1 and C2+) partition.

  5. Car Versus PT • The attitudes and attributes of travellers with a realistic choice exists are key to understanding and explaining car vs PT mode choice • Our approach is to identify the set of SHS Travel Diary journeys where there is a ‘realistic’ choice. This combines the following data: • Distance from nearest bus stop (SHS data) • Journey length (SHS data) • Car ownership (SHS data) • Car/PT Generalised costs (TMfS) • Parking charges by journey purpose (TMfS)

  6. Car versus Public Transport • A ‘relative cost’ variable (PT/Car generalised cost) has been attached to each record in the travel diary data set • PT Generalised costs include: • walk time, • effective wait time, • in vehicle run time, • boarding/transfer penalties, • fares • Car Generalised costs include: • in-vehicle time, • Vehicle Operating Costs (fuel and non-fuel) and • tolls

  7. Car Versus Public Transport • The extended SHS Travel Diary data set would be partitioned on the basis of variables strongly correlated with mode choice. • CHAID will be used (Chi Squared Automatic Interaction Detection) • Partition could include • Car ownership; • Relative cost of PT; • Purpose; • Age; • Income; • Day of week.

  8. Non-Motorised Modes • Analysis will focus on short trip lengths where walking and cycling offer significant alternative modes

  9. Non-Motorised Modes • CHAID analysis will partition the set of short trips. • Variables expected to be included in the partition are: • Car ownership; • Age; • Day of week; • Month (surrogate for weather effects); and • Journey purpose.

  10. Travel to School • Travel to School is an important area of cross cutting policy research involving education, health, environmental, road safety and transport. • It has been estimated that one in five cars in the AM week day peak is taking children to school • SSTAG (Scottish Schools Travel Advisory Group) is already carrying out research on mode choice for trips to school • The SHS data provides a number of questions about the usual means of travel to school, reasons for choosing this mode and availability of public transport.

  11. Other recent uses of SHS data • CEC Land Use and Transport Interaction Model (CEC LUTI) • Return home proportions by time of day; • Cycling and Walking demand matrices; • Trip lengths by journey purpose • Analysis of simple tours. • Transport Model for Scotland (TMfS) • Inputs into the demand matrices (mode * purpose * time for HB/NHB trips)

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