The key elements of strategy
Optimal Transport Strategies
As a generality, some success can be achieved with (3) and (4) alone. But if car use is not reduced, the opportunities for improving the road network will be severely limited, and hence so will the ability to improve bus-based public transport. Such reductions will be needed not only in city centres, on which road pricing is most likely to be focused, but also in inner and outer areas, where reductions will be harder to achieve. Moreover, if the growth in need to travel is not curtailed, improvements achieved in the short term will soon be eroded.
The strategy should thus contain measures to address all four of these elements, and a key element of an integrated strategy is the determination of the way in which these elements are integrated, and the balance between them determined. In particular, some politicians will wish to focus less on control of car use, and will as a result have a lower impact on congestion and generate less revenue. They will hence be able to achieve fewer improvements in public transport and the road network.
Once this highest level strategy is clear, it will be possible to address other key issues. In particular, this second stage can establish the strategy on:
This is not to say that these issues are less important, but simply that their treatment will not significantly influence the balance to be sought between the four key elements. For example, the ability to improve freight access will be determined primarily by the extent to which car use can be curtailed and the road system's performance improved. Within that context steps can be taken to allocate more strategic road space to commercial vehicles, and to control their use in sensitive areas. This in turn will improve the performance of the overall strategy, but it will not affect significantly the overall balance to be struck between restraint and network enhancement. More controversially, while walking and cycling are important modes, whose use is to be encouraged, there is little evidence that, in the short term, steps to improve them will encourage much transfer from car use, and hence reduce the need for other means of controlling it.
The principal transport policy measures can be considered under five broad headings, each of which contributes to one or more of the four key strategy elements listed above:
These and the finance which they generate and require are directly linked through the integrated strategy, as shown below. They each contribute to one or more of the key strategy elements.
The Interaction of Strategy Elements and Strategy Measures
The approach adopted has been to use a relatively simple model to encapsulate the behaviour of the more complex strategic transport model. The objective function is treated as the dependent variable and the specifications of the policy measures are used as the independent variables, thus generating a regression model, or response surface, which approximates the effects of the policy measures on the objective function. Discrete projects such as new roads or rail lines can be input as dummy variables. Continuously variable projects such as fares, service levels and road pricing charges can be expressed directly, though even here dummy variables may be needed to represent, for example, the existence of an off-peak fares reduction or a specific road pricing cordon. Where relationships are not expected to be linear, suitably transformed variables can be input. Interaction terms (such as fare times cordon charge) can be used to represent attributes which generate synergy (or, potentially, dissynergy). The procedure then involves conducting sufficient strategic transport model tests to enable a first response surface to be generated; differentiating the regression equation to identify any optima within the policy space; conducting further runs of the strategic transport model at and around the optimum; using these to enhance the response surface model; and repeating this process as necessary (Fowkes et al, 1998). More recently this approach has been used in two EU funded studies, OPTIMA (Optimisation of Policies for Transport Integration in Metropolitan Areas) and FATIMA (Financial Assistance for Transport Integration in Metropolitan Areas) to identify policy combinations which are optimal in terms of efficiency and sustainability in nine European cities (May et al, 1999, 2000). The results are presented in Level 3.