Institute for Transport Studies - OPTIMA Technical Approach

Technical Description

Theses objectives were achieved by carrying out the following tasks:

specify two objective functions, one each for economic efficiency and sustainability, which are acceptable to, and can be applied in, all the cities being studied;
identify, separately for each city, an acceptable set of transport and land use policy instruments, and to extend this list to cover measures in use elsewhere in the EU;
conduct a series of tests of combinations of policy measures, in each city, using currently available transport models of these cities;
use the optimisation methodology, separately for each city, to identify strategies which are optimal in terms of economic efficiency and sustainability in each city.
draw policy conclusions for each city on the differences between the efficiency-optimal and sustainability -optimal strategies, the justification for those strategies, and the feasibility of implementation, in discussion with the city authorities;
draw project-wide conclusions by comparing the results for the different cities, explaining the differences between them, and discussing their applicability in other EU member states.

Definition of objective functions (Task 1)

The Economic Efficiency Function (EEF) reflects the cities’ objectives of overall efficiency of the transport system, economising the use of resources, accessibility within the city and at least the possibility of economic regeneration. Essentially, the EEF performs a cost benefit analysis of the tested policy, while also imposing a shadow price on the financial support required.

The Sustainability Objective Function (SOF) differs from the EEF in that the exhaustible resource of fossil fuel is valued more highly than its market price, and that a penalty is incurred for those policies that do not meet a certain minimum requirement on fossil fuel savings. These features of the SOF reflect the aim to reduce CO2 emissions. Also, costs and benefits are only considered for the horizon year, representing the interests of future generations.

Common set of measures

Based upon an inventory of measures carried out by the project (Task 2), a set of common measures was selected for use in the optimisation process. Table 1 shows these measures and the maximum ranges considered (some cities used narrower ranges where it was felt that the maximum range was simply infeasible).

**Table 1: Measures tested**
Abbreviation	Name	Minimum Value	Maximum Value
IH	High public transport infrastructure investment	0	1(dummy)
IM	Medium public transport infrastructure investment	0	1(dummy)
CAP	Low cost increase/decrease of road capacity (whole city)*	-20%	+20%
FREQ	Increasing/decreasing public transport frequency (whole city)	-50%	+100%
RP	Road pricing# (city centre)	0	10.0 ecus
PCH	Increasing/decreasing parking charges(city centre)	-100%	+500%
FARE	Increasing/decreasing public transport fares (whole city)	-100%	+100%

* Road capacity measures include various types of traffic management and transport telematics, but do not include road building.
# The value of the measure Road Pricing refers to the cost per trip incurred by the car driver.

Optimisation process

Once measures and their ranges were defined, transport model runs were carried out (Task 3) to test an initial set of combinations of transport measures (packages). The number of packages in this set was the minimum number required to start up the optimisation process. The optimisation process (Task 4) was then applied to find the optimum set of values of these measures for each city, separately for each objective function.

Consultation process

Based on the initial review of the results, consultations were held with officials in each of the nine cities (Task 5). They were presented with the results, and invited to assess them against a set of criteria which focused on issues of feasibility and acceptability. Inevitably there was some overlap between the concerns under these two headings. The officials were also invited to suggest alternative strategies which they would wish to have tested. When these alternatives were tested, none of them performed better than the predicted optima (with respect to the objective functions), and the opportunity was taken to discuss these results. The output of these consultations was discussed with two other cities to test transferability, and then used to develop the conclusions specified in the "Results and conclusions" section (Task 6).