Archive:Hong Kong Mass Transport Study/Chapter 5

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Chapter 4 — Planning Characteristics and Projections

Hong Kong Mass Transport Study, Chapter 5 Travel Characteristics and Projections

Chapter 6 — Recommended System

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TRAVEL CHARACTERISTICS AND PROJECTIONS

1. A superficial inspection might give the impression that urban traffic movement is entirely random in character. However, consistencies are revealed when large numbers of journeys are reduced to such basic components as trip purpose, travel mode and trip length. All movement expresses the social and economic activities of the community and, once the relationship between travel and these activities is established, a mathematical evaluation of traffic flow can be made. Existing travel patterns in Hong Kong have been analysed intensively to derive these mathematical relationships.

HOME-INTERVIEW SURVEY

2. Two complete home-interview surveys were conducted by the Passenger Transport Survey Unit. One was based on a selective sample of households obtained from Government building and housing records. The other was based on a sample of car and motor cycle-owning households, taken from motor vehicle registration data. A total of 7,853 households was included in the former and 4,161 in the latter. The car-owning households included in the building-unit survey were later removed, to avoid duplication when the data from the two surveys were combined.
3. The home-interview survey data provided most of the in formation upon which this Study is based. A great deal of information about household characteristics, in addition to travel information concerning the members of the households, was gathered.
4. The Passenger Transport Survey Unit applied the initial expansions to the basic data. Additional expansions, adjustments and corrections were then made based on comparisons with other data, including all cross-harbour travel as measured in the ferry surveys. Analysis began after comparison with known full-scale data revealed sufficient correlation to proceed with confidence.

TRIP GENERATION (HOME-BASED)

5. Trip Generation is a term used to describe the number of journeys starting or ending in a zone, in relation to its social and economic characteristics. A study of trip generation does not attempt to cover all the characteristics of trips—direction, length, duration, etc.—but simply to quantify and classify the trip-ends in each zone.
6. Since home-based trips constitute more than 80 per cent of the total and can be related to household characteristics, they are analysed separately from those which are non-home-based. The home-based trip generations from the expanded home-interview survey were stratified according to trip purpose and related to various categories of households. Many categories were considered before settling on house type, car ownership, and family income as the variables to be used. The generations were converted to trip rates per person, as summarized in Tables 38, 39 and 40.
7. The actual trip rates used in the survey were different for each of the 10 primary traffic zones, and those presented in the tables are the Colony averages. The trip rates for squatter households were also produced as part of the process, but since it is assumed that all squatter households will have been relocated in permanent housing by the design year (1986), they are not included as a separate category. The trip rates used in the projections were for total transport, and the public transport portion was obtained from the modal split process described later in this chapter. However, for comparative purposes, Table 41 shows the public transport trips and the trip rates per household as obtained from the home-interview survey. It should be noted that the term "trip" as used in this chapter refers to the entire journey from origin to destination regardless of the number of modes used. Therefore, the totals quoted herein for the base year do not compare with the totals derived from the records of the public transport companies. Public transport and total trip generations, and generations per household are tabulated in the appendix of this report.
8. New Territories Travel — As the home-interview survey was only conducted within the urban area, it was necessary to synthetically calculate data for the New Territories. As primary Zone 8 is the urban area most closely resembling the New Territories, having some concentrations of urban development though primarily rural, the trip generation rates obtained in this zone were used to represent conditions in the New Territories. A completely independent analysis of New Territories travel was also made based on survey information gathered there as part of this Study. A comparison of the results obtained by these two methods revealed very similar trip patterns. (Overall, the independent analysis resulted in 5 per cent more trips; but in the largest zone, Tsuen Wan, it was within 3.6 per cent.) Therefore, the simulated New Territories data based on primary Zone 8 were used for the projections, as they provide more detailed information that can be of value later.

TRIP ATTRACTION (HOME-BASED)

9. An analysis of the various attracting influences exercised by different activities throughout an area becomes quite complex due to their interaction. A person about to make a trip is influenced by many different considerations in his choice of destination. The location cf available jobs, shopping centres, schools, recreational facilities and other activities, largely determines the number of trips attracted to the various zones. Therefore, trip attraction has been developed by regression analysis, using the parameters available for each zone. The best correlation between trip attractions and planning parameters was found in the following equations:

$\begin{array}{l}\text{Attractions from Car-owning Households}\\ =0.416X_1+24.522X_2-37.036& \text{for Manual Work Trips}\\ =2.381X_3-156.276& \text{for Non-manual Work Trips}\\ =1.379X_4+0.070X_5+0.389X_6-218.954& \text{for Other Home-based Trips}\\ \text{Attractions from Non-car-owning Households}\\ =1.392X_7-663.386& \text{for Manual Work Trips}\\ =2.403X_8-1,561.602& \text{for Non-manual Work Trips}\\ =4.235X_4+2.723X_5+0.860X_6-478.547& \text{for Other Home-based Trips}\end{array}$$\begin{array}{l}\text{where:}\\ X_1=\text{Number of manual employees who are residents of households with cars}\\ X_2=\text{Attraction index (attraction rating for each zone)}\\ X_3=\text{Number of non-manual employees who are residents of households with cars}\\ X_4=\text{Cars available}\\ X_5=\text{Retail employment}\\ X_6=\text{Other employment}\\ X_7=\text{Number of manual employees who are residents of households without cars}\\ X_8=\text{Number of non-manual employees who are residents of households without cars}\end{array}$

10. To provide an additional parameter for use in this analysis, each zone was rated with an attraction index number based on the amount of activity in each zone. This parameter was found to be significant in the attraction of manual work trips. Public transport and total attractions by sectors are tabulated in the appendix along with the subjective attraction points for each zone in the base and design years.

NON-HOME-BASED TRIPS

11. Non-home-based trips, like attractions, cannot logically be equated to household characteristics. The factors that motivate this type of trip are varied and complex. Therefore, these trips were developed by regression analysis, and non-home-based origins and destinations were found to correlate with the number of total home-based trip attractions. The following equations were used:

$$\begin{gathered} \begin{array}{l}\text{Non-home-based trip origins} \\ =\\ 0.220 \\ \text{home-based attractions}-390.368\\ \text{Non-home-based trip destinations} \\ =\\ 0.232 \\ \text{home-based attractions}-726.831\end{array} \end{gathered}$$