Competition in the UK passenger railway industry: Prospects and problems

The promotion of competition between passenger train operators was a key aim of the 1992- 97 Conservative Government when it privatized British Rail. Although the potential for competition in the market was constrained through regulation at the time of the sale, competition for the market became intense. Regulatory controls are now being relaxed and the promotion of competition remains central to the present Labour Government's rail strategy, particularly in the form of a redefined and reinvigorated franchising programme. It seems to be generally accepted in policy-making circles that it is both possible and desirable to encourage competition in the UK's railway industry on the grounds that it can further enhance service quality across the network. This paper highlights some qualifications to this position and suggests that, for various reasons, a strong policy emphasis on market liberalization may be impractical or unsuitable, at least in the short to medium term.     

Meeting mobility and air quality goals: Strategies that work

Recent federal legislation sets tough air quality goals for the nation but offers scant guidance to urban areas responsible for meeting those goals. Traditionally, transportation-related air quality policy emphasized cleaner vehicle and fuels technologies and alternatives to single-occupant vehicle travel such as car-pooling and mass transit. Analysis suggests, however, that meeting air quality goals will require the addition of policies to manage the growing demand for transportation. The introduction of market forces into transportation supply and demand decisions would support traditional transportation and air quality strategies, and produce additional mobility, air quality, and economic benefits. Recent transportation legislation offers states and localities the flexibility to meet mobility and air quality goals in an innovative, nontraditional manner. Drawing on theoretical analysis and recent empirical evidence we offer a package of measures for the consideration of state, and federal policy-makers.The authors are with the Office of Policy Analysis of the U.S. Environmental Protection Agency. The views expressed here belong solely to the authors. This paper does not represent the view of the US EPA or the policy of the United States Government. This paper was significantly improved by extensive comments from Bruce Schillo, and by suggestions from Michael Shelby, John Chamberlin (all of the EPA Office of Policy Analysis), Robin Miles-McLean (EPA Office of Mobile Sources), Allen Basala (EPA Office of Air Quality Planning and Standards), and numerous other colleagues. The authors are responsible for all errors and interpretations.     

Bayesian updating of trip generation data: Combining national trip generation rates with local data

With traffic impact analyses and impact fee assessment becoming more popular, the need for accurately estimating the trip generation rate of a proposed development is becoming more important. An overwhelming percentage of state transportation agencies depend either partly or entirely on the ITETrip Generation Report to predict the traffic that will be attracted to and/or produced from a proposed development. However, the rates obtained from the ITE publication have been derived from data collected throughout the United States. They represent a national average and fail to take into account the local trip generation characteristics that the site under consideration might have. This paper establishes a methodology for obtaining more reliable local trip generation rates using Bayesian statistics. In this method, the ITE rates are assumed to be the prior information, which are updated using limited local trip generation data that are available. The method also allows for temporal updating, incorporating subjective judgment and using borrowed data in the updating procedure. Sample calculations in this paper illustrate the developed methodology.     

Effective Public Participation is Fundamental for Marine Conservation—Lessons from a Large-Scale MPA

The Representative Areas Program (RAP) was, at the time, the most comprehensive process of community involvement and participatory planning for any environmental issue in Australia. The RAP was a key component of the widely acclaimed rezoning of the Great Barrier Reef Marine Park, and although completed in 2003, many lessons learned are still relevant today. This paper provides an analysis of the comprehensive public participation program that significantly influenced the final planning outcome. It provides insights into a fundamental component of effective marine planning, assessing what worked well and what did not in terms of public engagement. Some aspects of the public participation program were innovative, and some were more effective than others. The outcome was one-third of the Marine Park was declared as highly protected no-take zones in 2004, with the remainder of the park also zoned to provide lower levels of protection. The methods used to engage the public and the 25 lessons discussed in this paper should be of interest for practitioners, policy makers and academics elsewhere aiming for “good practice” approaches to achieve environmental conservation.     

The relationship between property values and railroad proximity: a study based on hedonic prices and real estate brokers' appraisals

We study the relationship between the price of residential property value and proximity to railroads in Oslo, by two different methods, namely a) through a hedonic price study where the statistical relationship between property prices and railroad proximity is estimated, and b) through a multi-attribute utility investigation of real estate agents' evaluation of such a relationship. We find in both cases that there are strong effects of proximity to railroad lines on property prices, at distances less than 100 meters from the lines. In the statistical study log-linear relationships fit the data best, and our estimates indicate that a doubling of the distance from the railroad line, within a 100 meter bound, increases the property price by about 10%. With real estate agents only a linear relationship is probed. This yields an increase in the price of an average relevant housing unit by about 182,000 NOK, due to a increase in the distance to a railroad track from 20 to 100 meters. The equivalent figure from the statistical study is in the range 120–150,000 NOK. The two figures are thus of the same magnitude.     

Men Shape a Downward Trend in Car Use among Young Adults—Evidence from Six Industrialized Countries

This paper investigates trends in the travel behaviour of young adults in Germany, France, Great Britain, Japan, Norway, and the USA over the past few decades with a focus on car availability and car travel. The trend analysis relies on micro-data from over 20 National Travel Surveys from the study countries dating back to the mid-1970s. The analysis of the survey data is supplemented by official statistics on licence holding. On this basis, this paper compiles a body of evidence for changes in mobility patterns among young adults in industrialized countries over the past few decades. The findings indicate that since the turn of the millennium, access to cars, measured in terms of drivers' licences and household car ownership, has decreased in most study countries—especially for men. Moreover, average daily car travel distance has decreased in most study countries, again especially for men. In France, Japan, and most significantly in the USA, the decrease in car travel has led to a reduction in total everyday travel by young travellers. In Great Britain, the decline in car travel was partly, and in Germany fully, compensated by an increased use of alternative modes of transport.     

Using kinematic driving data to detect sleep apnea treatment adherence

People spend a significant amount of time behind the wheel of a car. Recent advances in data collection facilitate continuously monitoring this behavior. Previous work demonstrates the importance of this data in driving safety but does not extended beyond the driving domain. One potential extension of this data is to identify driver states related to health conditions such as obstructive sleep apnea (OSA). We collected driving data and medication adherence from a sample of 75 OSA patients over 3.5 months. We converted speed and acceleration behaviors to symbols using symbolic aggregate approximation and converted these symbols to pattern frequencies using a sliding window. The resulting frequency data was matched with treatment adherence information. A random forest model was trained on the data and evaluated using a held-aside test dataset. The random forest model detects lapses in treatment adherence. An assessment of variable importance suggests that the important patterns of driving in classification correspond to route decisions and patterns that may be associated with drowsy driving. The success of this approach suggests driving data may be valuable for evaluating new treatments, analyzing side effects of medications, and that the approach may benefit other drowsiness detection algorithms.