Case studies
Managing Uncertainties through Learning Objectives
The key uncertainties in the Gateway Programme concern the behavioural response of vehicle users. Reduced congestion as a consequence of the road and bridge building strategy depends on the effectiveness of congestion management measures (e.g., tolling or High Occupancy Vehicle (HOV) lanes), overall demand for mobility, and the uptake of mode switching (see Figure 3).
Explicitly including learning objectives (see Figure 4) would provide for an initial phase of the Gateway Programme, perhaps geographically localized, to help parameterize these uncertainties, and so allow greater confidence in longer term expected outcomes. Should the forecasts of outcomes no longer reflect the stated objectives, components of the strategy could be modified.
Figure 5 integrates the sustainable development (SD) objectives for the Gateway Programme (Figure 3) with the adaptation and mitigation (AM) objectives from an earlier study of personal transportation in the Greater Vancouver region. Figure 5 takes the form of an influence diagram which characterizes the key uncertainties mediating the outcomes of the Gateway Programme (as the selected alternative) on the stated objectives. These uncertainties and other influences are based on Gateway Programme documentation.The top third of Figure 5 shows the fundamental objectives as calculation nodes (rounded rectangles), leading to the final consequences (diamond nodes). A calculation node is a decision element whose outcome can be resolved when the influences on it become known. The AM objectives are on the left and the SD objectives are on the right. The middle third of Figure 5 shows how the Gateway Programme's fundamental objectives are contingent on three key uncertainties: 'modal choices and switching', 'movement of people', and ‘movement of goods'. These latter two comprise the overall demand for transport, which is a function of socio-demographic and other trends (according to Gateway Programme documentation). These are represented in the calculation nodes in the bottom right of Figure 5 (e.g., 'change in socio-demographics' and 'change in patterns of job creation'). These and other influences on overall demand are treated as exogenous parameters in the Gateway Programme documentation, and so are included as calculations or known outcomes. Finally, the Gateway Programme itself is shown in italics as the two decision notes (rectangles) in the bottom left-hand corner, comprising road and bridge building and congestion management.
Figure 5 helps to emphasize various important points. The first is that the lack of influence of 'available transport infrastructure' (see box W in Figure 5) on 'movement of people' (see box X in Figure 5) reflects the reasoning behind the Gateway Programme that the demand for movement by road is a function of underlying socio-demographics and population rather than the availability of road infrastructure per se. While the Gateway Programme aims to affect people's choice of transport mode by encouraging HOV and non-vehicle modal choices (see box Y in Figure 5), its expected influence on overall demand (total km travelled) is less clear.
The second point to note is that 'modal choices and switching' (see box Y in Figure 5) is the key determinant of whether the Gateway Programme achieves its objectives. Learning about the influence of the Gateway Programme's new road infrastructure and congestion management measures on people's modal choices is therefore essential to evaluating its performance against its own stated objectives. 'Learning on mode-switching' could therefore serve as an intermediate node between the Gateway Programme and its final consequences, as well as a connection between initial and subsequent outcomes along a trajectory or consequence pathway, as suggested earlier in Figure 4.
Finally, the inclusion of the climate change objectives on the left side of Figure 5 (see box Z) shows the influence of the road and bridge building component of the Gateway Programme on the exposure of the region's transportation infrastructure to the impacts of climate change (in this case, storms and sea-level rise). The low adaptability of infrastructure investments with long capital turnover cycles to future change indicates the importance of considering these influences at the design phase of the Gateway Programme through, for example, storm water drainage or sea-level buffering.