Modelling the Choice of Car Parks in Urban Areas and Managing the Demand for Parking.

Car parks are an essential piece of infrastructure associated with the road networks, yet commonly available traffic assignment models do not to explicitly integrate them into the modelling process. This research attempts to integrate the choice of car parks in urban areas into the travellers’ route choice and incorporates both the route and car park choice in a joint modelling framework of traffic assignment based on equilibrium approach. This paper illustrates the implementation of the model in a commonly used standard suite of traffic assignment software. The proposed method considers multiple user classes - commuter and non-commuter flows, and involves modelling the demand for short stay and long stay car parks over multiple departure periods. A special search time delay function has been developed to represent the disutility in searching for a place in a car park, which is integrated further into the function of generalised cost of travel. This technique has been successfully applied to study the choice of car parks in the case of a simple hypothetical network. Another larger numerical example illustrates the case of managing the demand between two car parks in Leeds, England

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