Travel choices in alcohol-related situations in Virginia

Transportation - Using survey data from 3004 respondents aged 21 and older in Northern Virginia, Richmond, and the Tidewater area, this paper identifies factors associated with respondents’...     

Slam events of high-speed catamarans in irregular waves

Slam events experienced by high-speed catamarans in irregular waves were characterised through experiments using a hydroelastic segmented model. The model was designed to represent the dynamic behaviour of the full-scale Incat 112 m vessel and to allow the measurement of the slam load on the centrebow and wet deck. It was tested in irregular head seas at two speeds relating to Froude numbers of 0.32 and 0.60. Nearly 300 slams were identified in the test data and analysed with respect to kinematic parameters. Slams were found to have a large range of magnitudes, with the largest equivalent to 1785 tonnes full scale (approximately 70% of vessel displacement); however, the majority of events were of relatively low severity. Differences in slam characteristics were found for the two model speeds tested; slams at the slower speed generally occurred further forward on the hull, prior to the wave crest and with a bow down pitch angle. Immersion of the centrebow to the two-dimensional filling height of the cross-section between the centrebow and demihulls is shown to be a better indicator of slam occurrence than immersion to the top of the archway.     

How perceptions mediate the effects of the built environment on travel behavior?

This study provides a better understand the mechanism underlying the built environment-behavior connection by systematically exploring the relationships between the objective (actual) environment and people’s perceptions of the environment, and their relative effects on travel behavior using the Stimuli-Organism-Response framework. Based on data for the Twin Cities, this study explores (1) How do perceptions mediate the effects of the objective environment on travel behavior? (2) How do travel attitudes influence the effects of perceptions on travel behavior? Among the eight empirical models tested here, six are consistent with the framework: objective built environment affects travel behavior through its influence on perceptions. Moreover, the framework fits walking and bicycling behavior better than transit and driving behavior. Furthermore, travel attitudes greatly moderate the influences of perceptions on travel behavior.

     

Using automatic passenger counter data in bus arrival time prediction

Artificial neural networks have been used in a variety of prediction models because of their flexibility in modeling complicated systems. Using the automatic passenger counter data collected by New Jersey Transit, a model based on a neural network was developed to predict bus arrival times. Test runs showed that the predicted travel times generated by the models are reasonably close to the actual arrival times.     

Giving a direction to port regionalisation

As theoretical approaches to port development have advanced over the years, the role of the inland terminal has attracted increasing focus, particularly under the framework of port regionalisation. This paper will explore port regionalisation in different contexts through a greater focus on the drivers and direction of a number of inland terminal development strategies.The paper will build on previous work by combining inland terminal taxonomies and the theory of directional development with traditional port development models. Regionalisation strategies will be compared and contrasted through examples derived from field work undertaken in Europe and the USA. The results contribute towards a disaggregation of the process of port regionalisation, revealing different levels of integration and cooperation observed in different location splitting models. In this way, different strategies will be elucidated, enabling further exploration and more nuanced understanding of the institutional aspects of spatial development.     

Accident precursors and safety nets: leading indicators of tanker operations safety

Leading indicators, one type of accident precursor, are conditions, events or measures that precede an undesirable event and that have some value in predicting the arrival of the event, whether it is an accident, incident, near miss, or undesirable safety state. Leading indicators are associated with proactive activities that identify hazards and assess, eliminate, minimize and control risk. An empirical analysis of leading indicators of safety for an international energy transportation company was undertaken, utilizing a previously validated research model. Quantitative safety performance and qualitative safety culture data were obtained from 943 participants on 37 vessels from three fleets in the organization. Organizational, vessel and individual safety factors and leading indicators were identified and an analysis of fleet, vessel, and individual safety cultures was undertaken. The results indicate that individual and vessel-level leading indicators can provide important input to an organization's continuous safety measuring and monitoring systems.     

How do passengers use travel time? A case study of Shanghai–Nanjing high speed rail

Traditional travel behavior theory regards travel time as a waste. Recent studies suggest that it carries a positive utility, among other reasons for the benefit of the activities conducted while traveling. However, most studies of travel time use have focused on conventional trains in developed countries. Few have systematically examined the permeation of information and communication technology (ICT) into travel time use and the correlates of activity participation in developing countries, particularly on high speed rail (HSR). Using a survey conducted on the Shanghai–Nanjing corridor (N = 901), this study examines how HSR passengers use their travel time and explores the correlates of the different types of activities of business and non-business travelers, respectively, through multivariate probit models. We found that 96% of the respondents use ICT during their HSR journey and that most passengers spend some of their travel time on work-related activities. Moreover, items carried and advance planning as well as work-related travel attributes contribute significantly to activity participation. However, the factors affecting time use of business and non-business travelers differ. HSR service design should facilitate passenger engagement in various activities and improvement of their travel experience. A stable internet connection, adequate power sockets, and a noise-free environment will promote both work and leisure activities on the HSR.     

The interactions between e-shopping and traditional in-store shopping: an application of structural equations model

As the proliferation of e-commerce leads to ever greater numbers of on-line transactions, transportation planners are interested in the impacts of e-shopping on our strained transportation systems. Although the substitution effect of e-shopping is appealing, previous studies provided mixed results on its impact. Using 539 adult internet users in the Minneapolis-St Paul metropolitan area, this study applied a structural equations model to investigate the interactions among online purchases, in-store shopping, and product information search via internet. We found that online searching frequency has positive impacts on both online and in-store shopping frequencies and online buying positively affects in-store shopping. In particular, the marginal effects of online-buying frequency and online-searching frequency on in-store shopping frequency were estimated at 0.153 and 0.189, respectively. Since the internet as a shopping channel tends to have a complementary effect on in-store shopping, the rise of e-shopping is not likely to be a solution but a challenge to travel reduction.     

What is responsible for the response lag of a significant change in discretionary time use: the built environment,family and social obligations,temporal constraints,or a psychological delay factor?

In this paper, we used the 10-wave Puget Sound Panel Dataset to investigate the response lag of a significant change in discretionary time use. In particular, we want to quantify the relative magnitude of the following factors: the built environment, family and social obligations, temporal constraints, or a psychological delay factor (people delay a behavioral change until the next life shock). To answer this question, we developed a survival model to treat (1) left-censoring, (2) partial observation, and (3) multi-type exits. The results suggest that family and social obligations, as well as temporal constraints, appear to play a more important role than the built environment. Support for the psychological delay factor is not evident. We also found that the probability of having a significant change in discretionary time use is negatively related to time progression, supporting the human adaptivity hypothesis.