Towards improving resilience of cities: an optimisation approach to minimising vulnerability to disruption due to natural disasters under budgetary constraints

Transportation - In recent years, climate change emerged as a dominant concern to many parts of the world bringing in huge economic losses disturbing normal business/life. In particular cities are...     

A method to assess demand growth vulnerability of travel times on road network links

Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice—whether monitoring the past or planning for the future—a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure.     

Cordon tolls and competition between cities with symmetric and asymmetric interactions

The aim of this paper is to model the impacts of competition between cities on both the optimal welfare generating tolls and upon longer-term decisions such as business and residential location choices. The research uses a dynamic land use transport interaction model of two neighbouring cities and analyses the impacts by setting up a game between the two cities to maximise the welfare of their own residents. The work builds on our earlier research which studied competition in a small network using a static equilibrium approach for private car traffic without accounting for the land use responses to the change in accessibility. This paper extends the earlier work by setting up a dynamic model which includes active modes of travel and the more usual car and public transport in a realistic twin city setting and assesses the longer term relocation responses. This paper firstly sets out the competition between two hypothetical identical cities i.e. the symmetric case; and then sets out the real world asymmetric case in which the cities are of different size representative of Leeds and Bradford in the UK but equally applicable elsewhere too. We found that the level of interaction between the two cities is a key determinant to the optimal tolls and welfare gains. Our findings show that the competition between cities could lead to a Nash Trap at which both cities are worse off in terms of welfare gains. On the other hand, we found that cities, if regulated, would gain in terms of welfare and yet charge only half the toll compared with tolls under competition. We then show that the effect of competition increases with increased interaction between cities. In terms of residential location, cities with higher charges benefit from an increase in residents, though as with other studies, the relative change in population in response to cordon charging is small. The policy implications are threefold—(i) while there is an incentive to cooperate at local authority level, this is not achieved due to competition; (ii) where cities compete they may fall into a Nash Trap where both cities will be worse off compared to the regulated solution; and (iii) regulation is recommended when there is a strong interaction between the cities but that the benefits of regulation decrease as interaction between cities decreases and the impact of competition is lessened.