A joint time-assignment and expenditure-allocation model: value of leisure and value of time assigned to travel for specific population segments

Transportation - Based on a time-use model with a sound theoretical basis and carefully collected data for Austria, the value of leisure (VoL) for different population segments has been estimated....     

Transport in Tokyo

This paper gives a review of the historical and geographical preconditions as well as of the population and economic development which led to the unique and complex transport systems of Tokyo. Tokyo Metropolis, one of the most populous cities in the world, is located in the National Capital Region of Japan where 32 million people are living today. The special transport problems deriving from this high population density are described in context with the development of employment, transport infrastructure and motorization. Due consideration is given to the influence exerted by the structure of the whole region on the overall traffic behaviour.

Several transport phenomena and problem solutions which are typical of the traffic systems in Tokyo are described, such as the change of rush hour congestion rates depending on subway extension, modal split for different trip purposes in the inner urban area, or information via local radio broadcasts with very short range of transmission.

The main current transport issues are discussed. Though the transport networks in Tokyo are some of the most developed in the world, there is still heavy congestion in rush hours. The basic policy therefore is the further strengthening and improvement of the public transport network.     

New appraisal values of travel time saving and reliability in Great Britain

Transportation - This paper provides an overview of the study ‘Provision of market research for value of time savings and reliability’ undertaken by the Arup/ITS Leeds/Accent consortium...     

A simplified grounding damage prediction method and its application in modern damage stability requirements

This paper presents the analyses and results aimed at developing damage stability requirements which take into account the structural vulnerability to grounding damage, i.e. the kinetic energy available to generate damage and the structural resistance. The paper presents analysis of new damage statistics in order to determine impact scenarios, in particular in terms of impact speed, impact location, and width and height of damage. Furthermore a new empirical damage prediction formula is developed based on a combination of full-scale testing and extensive non-linear finite element analyses. This deterministic prediction method is validated against grounding experiments and then used in a probabilistic (Monte Carlo) simulation framework. First the simulation method is calibrated and validated against the real statistical damage data for conventional ships and then it is used to generate damage statistics for high-speed craft. It turns out that the grounding damage statistics for all ships can be characterized by a single parameter; the Grounding Damage Index, GDI, which includes the ship kinetic energy and its structural resistance to grounding damage. Simple, closed-form expressions are developed for the GDI and it is shown how the probability of exceeding a box-shaped damage is a simple function of the GDI and the size of the box. The paper therefore gives the background and the results for a new generation of damage stability rules where the structural crashworthiness is taken into account and where the passive safety level is explicitly expressed. It furthermore gives simplified prediction tools and data for actual ships, i.e. a toolbox that is readily available for risk analysis regarding grounding damage.     

Surrogate‐based optimization of cordon toll levels in congested traffic networks

The benefit, in terms of social surplus, from introducing congestion charging schemes in urban networks is depending on the design of the charging scheme. The literature on optimal design of congestion pricing schemes is to a large extent based on static traffic assignment, which is known for its deficiency in correctly predict travel times in networks with severe congestion. Dynamic traffic assignment can better predict travel times in a road network, but are more computational expensive. Thus, previously developed methods for the static case cannot be applied straightforward. Surrogate‐based optimization is commonly used for optimization problems with expensive‐to‐evaluate objective functions. In this paper, we evaluate the performance of a surrogate‐based optimization method, when the number of pricing schemes, which we can afford to evaluate (because of the computational time), are limited to between 20 and 40. A static traffic assignment model of Stockholm is used for evaluating a large number of different configurations of the surrogate‐based optimization method. Final evaluation is performed with the dynamic traffic assignment tool VisumDUE, coupled with the demand model Regent, for a Stockholm network including 1240 demand zones and 17 000 links. Our results show that the surrogate‐based optimization method can indeed be used for designing a congestion charging scheme, which return a high social surplus. Copyright © 2016 John Wiley & Sons, Ltd.     

Effects of increased awareness on choice of travel mode

This paper reports a field experiment with the purpose of studying the effects of increased awareness on travel mode choice. One hundred fifteen subjects were randomly assigned to an experimental and a control group. In the experimental group, a more deliberate choice of travel mode was induced and expected to result in a stronger relationship between attitude and behavior, a weaker relationship between habit and behavior, and a behavioral change among individuals with a strong habit. Attitude, habit, and behavior were measured in travel diaries and questionnaires. The results indicated no significant change in the relationship between attitude and behavior and no significant change in the relationship between habit and behavior. However, a temporally extended decrease in car use was observed in the experimental group. The effect was noted for individuals with a strong habit who reduced their car use but not for subjects with a weak habit.     

Analysis and optimisation of objective vehicle dynamics testing in winter conditions

Objective testing of vehicle handling in winter conditions has not been implemented yet because of its low repeatability and its low signal-to-noise ratio. Enabling this testing, by identifying robust manoeuvres and metrics, was the aim of this study. This has been achieved by using both experimental data, gathered with steering-robot tests on ice, and simulation models of different complexities. Simple bicycle models with brush and MF-tyre models were built, both optimally parameterised against the experimental data. The brush model presented a better balance in complexity performance. This model was also implemented in a Kalman filter to reduce measurement noise; however, a simpler low-pass filter showed almost similar results at lower cost. A more advanced full vehicle model was built in VI-CarRealTime, based on kinematics and compliance data, damper measurements, and real tyre measurements in winter conditions. This model offered better results and was therefore chosen to optimise the initial manoeuvres through test design and simulations. A sensitivity analysis (ANOVA) of the experimental data allowed one to classify the robustness of the metrics. Finally, to validate the results, the proposed and the initial manoeuvres were tested back to back in a new winter campaign.