Planning for cycling in the dispersed city: establishing a hierarchy of effectiveness of municipal cycling policies

Transportation - Urban utility cycling is being promoted widely due to various health, social, economic and environmental benefits. This study seeks to identify and rank which municipal-level...     

A study on time constraints and task deviations at sea leading to accidents – a cultural-historical perspective

The high frequency of maritime accidents and incidents occurring at sea has been a major challenge for the maritime industry in the last decades. The majority of these accidents are attributed to seafarers’ poor performance. This, despite the fact that the international maritime domain continues to adopt and update conventions regulating maritime safety to mitigate these accidents from occurring. In this paper, utilising a qualitative research approach, we show through a socio-cultural contextual perspective that time constraints as a major influencing factor in causing task deviations at sea which leads to dangerous situations. We analyse how some of the present barriers in place to prevent accidents at sea are in effect prompt seafarers who are working under time pressure to deviate from their task. Moreover, the paper discusses the social constituents such as job insecurity and the seafarers’ viewpoint towards the ship operators’ commitment to safe ship operations are crucial in motivating seafarers’ deviating from the task at hand when faced with time pressure.     

e-Navigation and situation-dependent manoeuvring assistance to enhance maritime emergency response

Safe ship handling in every situation and under all prevailing circumstances of ship status and the environment is a core element contributing to the safety of the maritime transportation system. Especially in case of emergencies, there is a need for quick, accurate and reliable information to manoeuvre a ship safely. This paper focusses on investigations into enhanced response to maritime emergencies by means of onboard manoeuvring support. The research and discussions are done exemplarily for person overboard (PoB) accidents. PoB is a typical situation for application of manoeuvring assistance and decision support, e.g. in order to return quickly to the position of the accident. Based on the analysis of selected accident case studies and existing solutions representing the technical state-of-the-art, shortcomings will be identified and discussed, and a potential approach for advanced manoeuvring support in the context of e-Navigation-based requirements will be introduced and discussed.     

Self- and peer-assessments of ambulance drivers' driving performance

The aim of the present study was to develop and examine the quality of the Ambulance Driver Self-assessment Questionnaire (ADSQ) and the Ambulance Driver Peer-assessment Questionnaire (ADPQ) measuring aspects of, driving performance, driving style and driving competence. In addition the ADSQ measures self-reflection and safety-attitudes. The aim of the study was also to examine ambulance drivers' self- and peer-assessments as well as to examine the accuracy of self-assessments by comparing self-assessed and peer-assessed driving performance, driving style and competence. 76 ambulance drivers employed at two ambulance stations in northern Sweden completed ADSQ and ADPQ. Item analyses were conducted to examine the psychometric properties of the items, and based on the results some revisions were made to improve the questionnaires. The revised questionnaires were functioning rather well, although some subscale demonstrated low internal consistency. Subscale inter-correlations provided support for construct validity. Self- and peer-assessments indicated safe driving performance and good driver competence, which is positive from a traffic safety perspective. A comparison of mean self- and peer-assessment ratings, controlling for age, gender and driving experience showed no significant differences, except for the subscale overtaking. This indicates that ambulance drivers' self-assessments are realistic in most areas.     

Range Extender Module Transmission Topology Study

Range extender modules are one option to compensate for short drive ranges of electric vehicles. The close interaction of combustion engine and generator poses new challenges in development. A key requirement for range extender systems is to be light and virtually imperceptible in operation. High-speed electrical machines aim at increasing power density. However, their introduction in a range extender requires a gearbox. The combustion engine torque fluctuations can lead to rattle in the gearbox. The rattle can be overcome by a dual mass flywheel. An interdisciplinary model is developed and used to analyse three different range extender systems: one with a low speed generator without gearbox, one with a high-speed generator, and one with a high-speed generator and a dual mass flywheel. The efficiency was found to be higher for the system with a low speed generator, whereas the power density and the costs are beneficial for the high-speed concept. A dual mass flywheel eliminates the changes of torque direction in the gearbox. It reduces the speed fluctuations of the gearbox and generator by over 90 % compared to the low speed setup. But it increases rolling moment and subsequently chassis excitation compared to a setup with only a gearbox.     

Integrating land use and transport knowledge in strategy-making

There is broad and growing consensus regarding the central place of integrated Land Use and Transport (LUT) strategy development in establishing more efficient and sustainable urban environments. However, empirical evidence shows that such integration is hard to achieve in daily planning practice, due to many institutional barriers and substantive differences. More specifically, the tools developed to support LUT strategy development have very low implementation rates in daily planning practice. This paper introduces the concept of ‘knowledge generation’ as a potentially useful mechanism for closing the gap between support tools and planning practice. Through two specific Dutch planning cases, we analyze the applicability of this concept in supporting integrated LUT strategy development. The paper focuses on the developed strategies, how these differ from current practice, and how knowledge generation supported their development. We argue that socialization produces shared strategies and that effective socialization needs to be supported by efficient mutual exchange between tacit and explicit knowledge. We conclude by discussing the implications of this argument for the wider practice of LUT planning integration.     

Transportation mode detection – an in-depth review of applicability and reliability

The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed by data insufficiency, ethics and privacy skepticism. The research problems whose study require hard-to-obtain data (e.g. transportation mode detection, service contextualisation, etc.) have now become more accessible to scientists because of the availability of data collecting outlets. One such problem is the detection of a user's transportation mode. Different fields have approached the problem of transportation mode detection with different aims: Location-Based Services (LBS) is a field that focuses on understanding the transportation mode in real-time, Transportation Science is a field that focuses on measuring the daily travel patterns of individuals or groups of individuals, and Human Geography is a field that focuses on enriching a trajectory by adding domain-specific semantics. While different fields providing solutions to the same problem could be viewed as a positive outcome, it is difficult to compare these solutions because the reported performance indicators depend on the type of approach and its aim (e.g. the real-time availability of LBS requires the performance to be computed on each classified location). The contributions of this paper are three fold. First, the paper reviews the critical aspects desired by each research field when providing solutions to the transportation mode detection problem. Second, it proposes three dimensions that separate three branches of science based on their main interest. Finally, it identifies important gaps in research and future directions, that is, proposing: widely accepted error measures meaningful for all disciplines, methods robust to new data sets and a benchmark data set for performance validation.     

Weather variability and travel behaviour – what we know and what we do not know

Given that severe weather conditions are becoming more frequent, it is important to understand the influence of weather on an individual’s daily activity-travel pattern. While some previously rare events are becoming more common, such as heavy rain, unpredicted snow, higher temperatures, it is still largely unknown how individuals will change and adapt their travel patterns in future climate conditions. Because of this concern, the number of research studies on weather and travel behaviour has increased in recent decades. Most of these empirical studies, however, have not used a cost–benefit analysis (CBA) framework, which serves as the the main tool for policy evaluation and project selection by stakeholders. This study summarises the existing findings regarding relationships between weather variability and travel behaviour, and critically assesses the methodological issues in these studies. Several further research directions are suggested to bridge the gap between empirical evidence and current practices in CBA.     

A causal inference approach to measure the vulnerability of urban metro systems

Transportation - Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal...     

Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results

Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific passenger car unit factors that depend on roadway type and the capabilities of the vehicles. The second extension enables travel demand models to calculate demand changes caused by a different perception of travel time as the active driving time is reduced. The presented methods are applied to a use case of a regional macroscopic travel demand model. The basic assumption is that AV are considered highly but not fully automated and still require a driver for parts of the trip. Model results indicate that first-generation AV, probably being rather cautious, may decrease traffic performance. Further developed AV will improve performance on some parts of the network. Together with a reduction in active driving time, cars will become even more attractive, resulting in a modal shift towards car. Both circumstances lead to an increase in time spent and distance traveled.