Paul Timms

OPTIMAL TRANSPORT STRATEGIES FOR EUROPEAN CITIES

A new procedure for generating optimal transport strategies has been applied in nine European cities. A public sector objective function which reflects concerns over efficiency, environmental impact, finance and sustainability is specified and a set of policy measures with acceptable ranges on each, identified. Optimal strategies based on combinations of these policy measures which generate the optimal value of the objective function, are identified, and compared between cities. Resulting policy recommendations are presented. The results demonstrate the importance of an integrated approach to transport strategy formulation. They emphasise the role of changes in public transport service levels and of fares, and of charges for car use. By contrast, new infrastructure projects are less frequently justified. In the majority of cities the revenues from car use charges are sufficient to finance other elements in the strategy. However, private sector involvement either in initial financing or in operation may be desirable. Revised objective functions to reflect private sector involvement are specified, and optimal strategies with private sector operation of public transport are also identified. The requirement to meet private sector rates of return for public transport operation typically results in lower frequencies and higher fares; charges for car use then need to be raised to satisfy public policy objectives, but system performance is reduced.

Imagineering Mobility: Constructing Utopias for Future Urban Transport

Over the past fifty years a growing body of work has sought to address the problem of planning for transportation in the long-term future through scenario building. Such thinking has generally been restricted to issues concerned with environmental sustainability and the ‘images’ of future transport so created are usually weak in terms of their social sustainability content, either treating social issues superficially, or ignoring them entirely, or even creating images that are socially undesirable. At the same time, there has generally been a marked decrease over the past twenty years in socially oriented Utopian thinking. As a direct result of these two factors, hardly any consideration has been given recently to imagining socially sustainable views of transport in a future utopia. The key underlying aim of this paper is to provide some background thinking about how this lack might be addressed. To do so, it examines concepts about utopia in terms of their form, content, and function, and considers possible reasons for the recent decline in Utopian thinking and their ‘replacement’ by a type of futures-thinking that is referred to as dystopian avoidance. It then examines transport characteristics of Utopian thinking in urban planning in the 20th century and considers various ‘antinomies of transport’ with respect to future Utopias. Based upon the insights gained, the paper comments on two existing ‘practical’ sets of transport-related scenarios in terms of their Utopian and dystopian characteristics. One particular result is that the Utopian aspects of these scenario sets in terms of their social content are relatively weak, in line with the hypothesised recent general decline in (social) Utopian thinking. Various conclusions are made which emphasise the usefulness of Utopian thinking in transport planning, particularly in participatory approaches. It is suggested that three elements of the transport system should be separately ‘utopianised’: The mobility of people and goods; physical aspects that facilitate or inhibit such mobility; and the system of governance with respect to formulating and implementing transport policy.

Personal Transport Emissions within London: Exploring Policy Scenarios and Carbon Reductions Up to 2050

ABSTRACT This research explored the possibility of achieving significant carbon reductions from personal land-based transport using London as a case study. A profile of carbon emissions from personal land-based transport modes was derived using Great Britain National Travel Survey (NTS) data and a range of carbon emissions factors. A carbon calculator provided carbon consumption per trip. NTS survey data were grossed up to national level using Census of Population data. A baseline of carbon emissions, based on equal per capita consumption, was projected to 2050 using estimates of future population. Four future scenarios were developed and tested using this data. These were: (a) based on the London Mayors Climate Change Action Plan; (b) a technology focussed scenario; (c) a personal carbon trading scenario; and (d) a radical walking and cycling scenario. Results suggest that the latter two scenarios have the potential to achieve emissions reductions in excess of 80%, while scenarios (a) and (b) are somewhat weaker, though still achieve substantial reductions in carbon emissions compared to business as usual.

Dynamic Bayesian Belief Network to Model the Development of Walking and Cycling Schemes

ABSTRACT This paper aims to describe a model which represents the formulation of decision-making processes (over a number of years) affecting the step-changes of walking and cycling (WaC) schemes. These processes can be seen as being driven by a number of causal factors, many of which are associated with the attitudes of a variety of factors, in terms of both determining whether any scheme will be implemented and, if it is implemented, the extent to which it is used. The outputs of the model are pathways as to how the future might unfold (in terms of a number of future time steps) with respect to specific pedestrian and cyclist schemes. The transitions of the decision making processes are formulated using a qualitative simulation method, which describes the step-changes of the WaC scheme development. In this article a Bayesian belief network (BBN) theory is extended to model the influence between and within factors in the dynamic decision making process.

The specification of sustainable urban transport strategies

Transport strategies have been developed for nine European cities to achieve optimum performance in terms of a range of objective functions. The functions selected represent economic efficiency, sustainability and a combination of these. The strategies have been based on combinations of a standard set of policy instruments, including public transport infrastructure, frequency and fares, road capacity increases, low cost road pricing and parking charges. The optimisation method is described, and results presented. The reactions of city authorities to the proposed strategies are discussed and implications for transport policy outlined.

Modeling Bus Lane Priorities in a Motorcycle Environment Using SATURN

Bus lanes and median bus ways such as those in Curitiba, Brazil, and Bogotá, Colombia, are attracting a great deal of attention worldwide. For many Asian developing cities, there is an interest in how successfully bus lanes and bus rapid transit will function, given that traffic conditions in such cities typically are different from those found in Latin America. This paper addresses this issue for Asian cities whose traffic is dominated by motorcycles, concentrating particularly on Hanoi, Vietnam. With the use of a SATURN mesoscopic simulation model for Hanoi (with 322 junctions and 1,108 links), different bus lane–bus way designs are compared in regard to their effects on travel time savings. Results show that the level of motorcycle violations has an important impact on the success of bus lane schemes and that there is no significant speed improvement on bus lanes if enforcement is weak. Bus ways can achieve much higher bus speeds than can bus lanes, but general traffic speeds are likely to reduce them significantly if there is no mode switching from private modes to buses. In such circumstances the potential extra delay due to a poorly designed bus way is greater than that due to a poorly designed bus lane. The route-switching flexibility of motorcycles also has considerable effects on the performance of bus lanes and bus ways.

The interface between transport policy‐making and science: A ‘two‐person’ model

Abstract The paper attempts to build a qualitative ‘two‐person’ model which encapsulates the complex relationship between transport policy‐making and science, by personifying the relationship as a dialogue between ‘the politician’ and ‘the scientist’. The approach is illustrated by making references to the methods and results of the research project OPTIMA, which has attempted to find optimal urban transport policies in a number of European cities. Whilst finding much usefulness in the model, the paper recognizes its limitations and makes recommendations of a number of extensions that could be made.

Estimating individual physical capability (IPC) to make journeys by bicycle

ABSTRACT We propose a novel method to estimate capability to make bicycle journeys, specifically considering the individual physical capability (IPC) of entire populations of individuals from all population segments of an area, not just current cyclists. IPC considers the physical constraints on the maximum distance people could cycle given the typical topography of where they live (Distance IPC), and then estimates their ability to make a particular journey (Journey IPC). IPC, when estimated in this way for a particular point in time, may be informed by antecedent behavioral choices and capabilities, and may be a constraint or enabler of subsequent capabilities, potential adaptations and behavior. The focus of the present paper is on explaining a generic method of estimating Distance IPC and Journey IPC by constructing an individually based spatially fine-grained model. We show how such an individual-level model may be implemented for a population resident in many small spatial zones by use of spatial micro-simulation (population synthesis), to generate the individual attributes required as inputs to the model. We present a case-study for the city of Leeds, UK. We explain the range of data sources used, explore sensitivity of the results to assumptions of the model, and illustrate the ability of the model to simulate the effects of policies. Finally, we identify several possible application areas and opportunities to further develop the model.