Population (trip productions)
Retail floor area (trip attractions)
Employment levels (trip attractions)
linear regression analysis yields the following zone-based equations for the two
relevant dependent variables (zonal trip productions and zonal trip attractions)
as follows:
P=(3 ¥population) - 500 (2.17)
A=(3 ¥number employed) +(75 ¥office floor space, m^2 ) + 400 (2.18)
Table 2.16 gives zonal trip generation factors for the design year, together with
the trip productions and attractions estimated from these factors using Equa-
tions 2.17 and 2.18.
Forecasting Future Traffic Flows 37
Zone Population Office floor Numbers Trip Trip
area (m^2 ) employed productions attractions
A7 500 50 775 22 000 6 475
B4 000 400 3 500 11 500 40 900
C6 000 75 700 17 500 8 125
D5 000 250 4 000 14 500 31 150
E9 000 100 1 000 26 500 10 900
F6 000 50 3 000 17 500 13 150
G4 000 100 800 11 500 10 300
Total 41 500 1025 13 775 121 000 121 000
Table 2.16Trip productions and attractions for the design year (10 years after baseline year)
For example, in the case of zone A:
Trips produced = 3 ¥ 7500 - 500 =22 000
Trips attracted =(3 ¥775) +(75 ¥50) + 400 = 6475
2.8.2 Trip distribution
In order to compile the trip distribution matrix, the impedance term relating to
the resistance to travel between each pair of zones must be established. In this
case, the travel time is taken as a measure of the impedance and the zone-to-
zone times are given in Table 2.17.
Using a gravity model with the deterrence function in the following form
between zone iand zone j:
Fij=t-ij^2
where tijis the time taken to travel between zone iand zone j
The interzonal trips are estimated using Equation 2.3. For example, taking the
trips from zone A to all other zones, it can be seen from Table 2.16 that 6475
