Role of the Railways in the Future of Air Transport

Abstract

The role of the railways in the air transport industry is usually limited to provision of access to airports. However, the development of high-speed rail networks and the congestion and environmental problems faced by the air transport industry suggest the railways could have a greater role in working with the airlines to provide an integrated transport service for medium-distance journeys (up to 800 km). Many air journeys involve two flights and a transfer at a hub airport. The alternative being investigated here would replace air journeys by a rail journey and a flight, and a transfer between them at the hub airport. Such integration could offer a positive alternative to aircraft on some routes and lead to railway journeys to airports becoming part of air transport services, and not only to provide access to them. Integration could therefore provide a better use of available air capacity rather than duplicating some high-speed rail routes and services.     

Parameter transfer of common-metric attributes in choice analysis: implications for willingness to pay

There is a growing literature that promotes the presence of a mix of compensatory and semi-compensatory processing strategies in the way that individuals evaluate packages of attributes in real or hypothetical markets, and make choices. This paper proposes a specification for the utility form in a choice model to test if, given a pair of attributes with a common-metric (e.g., components of travel time or cost), the attribute with the dominating level defines the marginal (dis)utility that is assigned to both attributes. We refer to this processing strategy as a parameter transfer rule. We use a stated choice data set, in the context of car driving individuals choosing between tolled and non-tolled routes, to estimate a mixed logit model which incorporates the presence of the parameter transfer rule and the conventional fully compensatory rule, both existing up to a probability. We find that if this parameter transfer heuristic is part of the mix, the WTP is more than 30% higher, on average, than when only a fully compensatory rule is imposed. We also contrast the parameter transfer rule with other semi-compensatory heuristics which have been investigated in other papers, and show that the finding adds further support to the accumulating evidence that a semi-compensatory attribute processing rules tend to result in higher mean WTP estimates compared to the fully compensatory attribute processing rule.     

The traffic and behavioral effects of the I-35W Mississippi River bridge collapse

On August 1, 2007, the collapse of the I-35W bridge over the Mississippi River in Minneapolis abruptly interrupted the usual route of about 140,000 daily vehicle trips, which substantially disturbed regular traffic flow patterns on the network. It took several weeks for the network to re-equilibrate, during which period travelers continued to learn and adjust their travel decisions. A good understanding of this process is crucial for traffic management and the design of mitigation schemes. Data from loop-detectors, bus ridership statistics, and a survey are analyzed and compared, revealing the evolving traffic reactions to the bridge collapse and how individual choices could help to explain such dynamics. Findings on short-term traffic dynamics and behavioral reactions to this major network disruption have important implications for traffic management in response to future scenarios.     

Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling

This study reviews the 50-year history of travel demand forecasting models, concentrating on their accuracy and relevance for public decision-making. Only a few studies of model accuracy have been performed, but they find that the likely inaccuracy in the 20-year forecast of major road projects is ±30 % at minimum, with some estimates as high as ±40–50 % over even shorter time horizons. There is a significant tendency to over-estimate traffic and underestimate costs, particularly for toll roads. Forecasts of transit costs and ridership are even more uncertain and also significantly optimistic. The greatest knowledge gap in US travel demand modeling is the unknown accuracy of US urban road traffic forecasts. Modeling weaknesses leading to these problems (non-behavioral content, inaccuracy of inputs and key assumptions, policy insensitivity, and excessive complexity) are identified. In addition, the institutional and political environments that encourage optimism bias and low risk assessment in forecasts are also reviewed. Major institutional factors, particularly low local funding matches and competitive grants, confound scenario modeling efforts and dampen the hope that technical modeling improvements alone can improve forecasting accuracy. The fundamental problems are not technical but institutional: high non-local funding shares for large projects warp local perceptions of project benefit versus costs, leading to both input errors and political pressure to fund projects. To deal with these issues, the paper outlines two different approaches. The first, termed ‘hubris’, proposes a multi-decade effort to substantially improve model forecasting accuracy over time by monitoring performance and improving data, methods and understanding of travel, but also by deliberately modifying the institutional arrangements that lead to optimism bias. The second, termed ‘humility’, proposes to openly quantify and recognize the inherent uncertainty in travel demand forecasts and deliberately reduce their influence on project decision-making. However to be successful either approach would require monitoring and reporting accuracy, standards for modeling and forecasting, greater model transparency, educational initiatives, coordinated research, strengthened ethics and reduction of non-local funding ratios so that localities have more at stake.     

Active Roll Control of Single Unit Heavy Road Vehicles

Summary Strategies are investigated for controlling active anti-roll systems in single unit heavy road vehicles, so as to maximise roll stability. The achievable roll stability improvements that can be obtained by applying active anti-roll torques to truck suspensions are discussed. Active roll control strategies are developed, based on linear quadratic controllers. It is shown that an effective controller can be designed using the LQG approach, combined with the loop transfer recovery method to ensure adequate stability margins. A roll controller is designed for a torsionally flexible single unit vehicle, and the vehicle response to steady-state and transient cornering manoeuvres is simulated. It is concluded that roll stability can be improved by between 26% and 46% depending on the manoeuvre. Handling stability is also improved significantly.     

Driver steering and muscle activity during a lane-change manoeuvre

The article reports an experimental study of driver steering control behaviour in a lane-change manoeuvre. Eight test subjects were instrumented with electromyography to measure muscle activation and co-contraction. Each subject completed 30 lane-change manoeuvres with one vehicle on a fixed-base driving simulator. For each driver, the steering torque feedback characteristic was changed after every ten manoeuvres; the response of the vehicle to steering angle inputs was not changed. Drivers' control strategies were found to be robust to changes in steering torque feedback. Path-following errors, muscle activity and muscle co-contraction all reduce with the number of lane-changes performed by the driver, suggesting the existence of a learning process. Comparing the test subjects, there was some evidence that high levels of co-contraction were used to allow high-frequency steering inputs to be generated. The results contribute to the understanding of vehicle-driver (and more generally, human-machine) dynamic interaction.     

Towards connected autonomous driving: review of use-cases

Connected autonomous vehicles are considered as mitigators of issues such as traffic congestion, road safety, inefficient fuel consumption and pollutant emissions that current road transportation system suffers from. Connected autonomous vehicles utilise communication systems to enhance the performance of autonomous vehicles and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring. The former refers to the ability to share and fuse information gathered from vehicle sensors and road infrastructures to create a better understanding of the surrounding environment while the latter enables groups of vehicles to drive in a co-ordinated way which ultimately results in a safer and more efficient driving environment. However, there is a gap in understanding how and to what extent connectivity can contribute to improving the efficiency, safety and performance of autonomous vehicles. Therefore, the aim of this paper is to investigate the potential benefits that can be achieved from connected autonomous vehicles through analysing five use-cases: (i) vehicle platooning, (ii) lane changing, (iii) intersection management, (iv) energy management and (v) road friction estimation. The current paper highlights that although connectivity can enhance the performance of autonomous vehicles and contribute to the improvement of current transportation system performance, the level of achievable benefits depends on factors such as the penetration rate of connected vehicles, traffic scenarios and the way of augmenting off-board information into vehicle control systems.