Travel-time distribution parameters are calculated by fitting the negative exponential trend line to the cumulative distribution function of surveyed travel times. Exponential trend lines can be fitted by many software packages, including Microsoft Office Excel, which enables a visual display of the results and easy calculation of R2 values. Values presented in this report have been calculated using a least squares approximation, part of the Numerical Python computing environment and accessed through the Python programming language. The deterrence function is only calculated based upon the first 95% of data, as attempting to fit sparsely placed higher values can severely distort the resulting curve. An example of walking to home-based employment in MUAs is shown in figure 13.1; in this case the λ parameter is shown to be 0.065
Figure 13.1 MUA employment (home-based) walking travel time distribution function
The raw data (distribution of trip times) shown in figure 14.1 highlights an apparent categorisation of trip times by NZHTS respondents. It reveals the majority of NZHTS respondents have rounded their trip duration to the nearest five minutes, eg ‘my trip took 15 minutes’ rather than accurately recording the trip time to the nearest minute. Accurate recording of trip duration to the nearest minute would reveal a smoother distribution of trip times more akin to the negative exponential trend line fitted to the data.