Delivering Value for Money to Government through Efficient and Effective Public Transit Service Continuity: Some Thoughts

Abstract

This paper documents some thoughts on the reform agenda in public transit that is occurring throughout the world. The specific focus is on a growing commitment to competitive regulation through competitive tendering, and the efforts by a few governments (notably in Australia) to take control of the tangible assets used by private operators as a mechanism to exercise the opportunity, if so taken, to put services out to competitive tender. The paper reviews the theoretical arguments and empirical evidence on contracting regimes and asset ownership, and the role that government and the operator might play in a setting in which building trusting and collaborative partnerships has merit in delivering services that are in the main funded from the public purse.     

Evaluating the long term impacts of transport policy: The case of passenger rail privatisation

Britain's national rail system was ‘privatised’ as a result of the 1993 Railways Act, with most of the organisational and ownership changes implemented by 1997. This paper examines the long term impacts of these changes. A key issue when examining long term changes is that of the counterfactual – what would have happened if the changes had not occurred? A simple econometric model of the demand for passenger rail services was developed and used in conjunction with extrapolative methods for key variables such as fares and train km to determine demand-side counterfactuals. Extrapolative methods were also used to determine counterfactual infrastructure and train operation costs. Although our results are sensitive to the assumptions we have made concerning the counterfactual they suggest a number of impacts. Since privatisation, rail demand has grown strongly but our analysis indicates that transitional disruptions suppressed demand by around 9% over a prolonged period (1992/3 to 2005/6), whilst the Hatfield accident reduced demand by about 5%, albeit over a shorter period (2000/1 to 2006/7). A welfare analysis suggests that although consumers seem to have gained as a result of privatisation, for most years this has been offset by increases in costs. An exception is provided by the two years immediately before the Hatfield accident. Overall the loss in welfare since the reforms were introduced far exceeds the net receipts from the sale of rail businesses. Thus although the reforms have had advantages in terms of lower fares and better service levels than otherwise would have been the case, this appears to have been offset by increased infrastructure and train operations costs. The source of these high costs remains an area of speculation but appear to be related to aspects of both market and regulatory failure.     

Cluster-based correlation of severe driving events with time and location

In this article, a systematic strategy is proposed to identify severe driving events occurrence correlation with time and location. The proposed approach, which is constructed based on batch clustering and real-time clustering techniques, incorporates historical and real-time data to predict the time and location of severe driving events. Batch clustering is implemented with the combination of subtractive clustering and fuzzy c-means clustering to generate clusters representing the initial correlation patterns. Real-time clustering is then developed to create and update real-time correlation patterns on the foundation of the batch clustering using the evolving Gustafson–Kessel like (eGKL) algorithm. In both clustering processes, the correlation of the events within time domain is identified first, and then two different levels of accurate correlations are conducted for the location domain. Real-time data of operating vehicles each equipped with a data acquisition and wireless communication platform are used to validate the proposed strategy. Batch clustering results reveal the severe braking events distribution and concentration at daytime and nighttime. Real-time clustering provides and updates the variation of the correlations/intercorrelation of different regions. Drivers can be notified of the potential severe driving locations through maps showing the driving routes. Through the variation of the correlations, drivers can recognize the events occurrence at different times and locations. The generated time series can be potentially used to develop spatial-time models for regions to model and forecast the events occurrence.     

Forecasting petrol demand and assessing the impact of selective strategies to reduce fuel consumption

Abstract

The use of fossil fuels in transportation is an important topic as a result of growing concerns over global warming. Automobile petrol demand has been of particular interest to researchers and policy-makers, given that the automobile is a major contributor to the enhanced greenhouse effect. This paper forecasts Australia's automobile petrol demand up to the year 2020 based on the best performing forecasting model selected out of eight models. In order to establish ways to reduce the demand for petrol, and the consequent by-product of reducing the amount of greenhouse gas emissions, we have estimated the impact on CO₂ for several potential policy instruments, using Transportation and Environment Strategy Impact Simulator (an integrated transport, land use and environmental strategy impact simulation programme). We find that a carbon tax of AU$0.50/kg can reduce automobile kilometres by 5.9%, resulting in reduced demand for petrol and a reduction in CO₂ of 1.5%.     

Forecasting automobile petrol demand in Australia: An evaluation of empirical models

Transport fuel consumption and its determinants have received a great deal of attention since the early 1970s. In the literature, different types of modelling methods have been used to estimate petrol demand, each having methodological strengths and weaknesses. This paper is motivated by an ongoing need to review the effectiveness of empirical fuel demand forecasting models, with a focus on theoretical as well as practical considerations in the model-building processes of different model forms. We consider a linear trend model, a quadratic trend model, an exponential trend model, a single exponential smoothing model, Holt’s linear model, Holt–Winters’ model, a partial adjustment model (PAM), and an autoregressive integrated moving average (ARIMA) model. More importantly, the study identifies the difference between forecasts and actual observations of petrol demand in order to identify forecasting accuracy. Given the identified best-forecasting model, Australia’s automobile petrol demand from 2007 through to 2020 is presented under the “business-as-usual” scenario.     

Where do cyclists ride? A route choice model developed with revealed preference GPS data

To better understand bicyclists’ preferences for facility types, GPS units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.     

Workshop 3A: Governance,contracting, ownership and competition issues in public transport: Looking up not down

Workshop 3A focussed on matters of institutional design that seem likely to improve public transport outcomes. It started by defining high level outcome goals, as measures of ultimate public transport success, and then identified the major societal issues that public transport systems can help to resolve. These issues were separately defined for Southern African and western settings. The importance of taking an integrated approach to transport, particularly land use/transport integration, was seen as fundamental to goal achievement. Workshop papers provided many and varied examples of this importance, ranging from PPPs for major public transport projects to system design issues and contracting out of services. The Workshop included detailed discussion on paratransit development in Southern Africa, where relationship management is proving to be critical, in-line with much previous Thredbo discussion about the important role of trusting partnerships. Parallels and contrasts were drawn with paratransit in western settings. Competition in passenger rail was also a focus, with some questioning of the benefits of franchising. Discussion concluded by proposing recommendations for policy and research and suggesting agenda items for future Thredbo Conferences.     

Evaluating the long term impacts of transport policy: An initial assessment of bus deregulation

Local buses in Britain, outside London, were ‘deregulated’ as a result of the 1985 Transport Act, with most of the organisational changes implemented in 1986 but many of the ownership changes occurring over a longer period. By contrast, in London, the 1984 London Regional Transport Act introduced a system of comprehensive tendering – but it took 10 years for the organisational and ownership changes to be fully implemented. This paper examines the long term impacts of these changes. A key issue when examining long term changes is that of the counterfactual – what would have happened if the changes had not occurred? An econometric model of the demand for local bus services in Britain is outlined and used in conjunction with extrapolative methods for key variables such as fares and bus kms to determine demand-side counterfactuals. Some analyses of subsidy and of costs will also be outlined. This will then permit the examination of welfare change by estimating changes in consumer and producer surpluses, updating earlier studies. It is found that outside London, bus demand declined strongly, at least up to the year 2000 and some of this reduction can be ascribed to deregulation. By contrast in London, demand has generally been increasing. However, in both areas operating costs also declined strongly, again up to 2000, but since then there have been strong increases in costs and subsidy. Our initial finding is that there are net welfare increases both outside and inside London, but with welfare increases per capita being five times greater in London than elsewhere. However, sensitivity analysis shows that our results are sensitive to the specification of the modelling system and assumptions made concerning the counterfactual, particularly for the results for London.