Bicycling crash characteristics: An in-depth crash investigation study

The aim of this study was to describe the crash characteristics and patient outcomes of a sample of patients admitted to hospital following bicycle crashes. Injured cyclists were recruited from the two major trauma services for the state of Victoria, Australia. Enrolled cyclists completed a structured interview, and injury details and patient outcomes were extracted from the Victorian State Trauma Registry (VSTR) and the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR). 186 cyclists consented to participate in the study. Crashes commonly occurred during daylight hours and in clear weather conditions. Two-thirds of crashes occurred on-road (69%) and were a combination of single cyclist-only events (56%) and multi-vehicle crashes (44%). Of the multi-vehicle crashes, a motor vehicle was the most common impact partner (72%) and distinct pre-crash directional interactions were observed between the cyclist and motor vehicle. Nearly a quarter of on-road crashes occurred when the cyclist was in a marked bicycle lane. Of the 31% of crashes that were not on-road, 28 (15%) occurred on bicycle paths and 29 (16%) occurred in other locations. Crashes on bicycle paths commonly occurred on shared bicycle and pedestrian paths (83%) and did not involve another person or vehicle. Other crash locations included mountain bike trails (39%), BMX parks (21%) and footpaths (18%). While differences in impact partners and crash characteristics were observed between crashes occurring on-road, on bicycle paths and in other locations, injury patterns and severity were similar. Most cyclists had returned to work at 6 months post-injury, however only a third of participants reported a complete functional recovery. Further research is required to develop targeted countermeasures to address the risk factors identified in this study.     

Life cycle simulation system as an evaluation platform for multitiered circular manufacturing systems

A life cycle simulation (LCS) is a powerful tool for evaluating the life cycle scenarios of circular manufacturing. Although many LCSs have been developed so far, they were specific to particular scenarios and products. Therefore, we developed a general-purpose LCS system that can be used to evaluate various life cycle scenarios including multiple circulation paths such as closed-loop and cascade reuse and recycling. This system is useful for developing effective circular manufacturing systems with proper life cycle options. We applied it to a closed-loop and cascade reuse of lithium-ion batteries of electric vehicles in order to demonstrate its effectiveness.     

Look-ahead controls of heavy duty trucks on open roads — six benchmark solutions

A benchmark problem for fuel efficient control of a truck on a given road profile has been formulated and solved. Six different solution strategies utilizing varying degrees of off-line and on-line computations are described and compared. A vehicle model is used to benchmark the solutions on different driving missions. The vehicle model was presented at the IFAC AAC 2016 symposium and is compiled from model components validated in previous research projects. The driving scenario is provided as a road slope profile and a desired trip time. The problem to solve is a combination of engine-, driveline- and vehicle-control while fulfilling demands on emissions, driving time, legislative speed, and engine protections. The strength of this publication is the collection of all six different solutions in one paper. This paper is intended to provide a starting point for practicing engineers or researchers who work with optimal and/or model based vehicle control.     

Do German drivers use their smartphones safely?—Not really!

Research in the laboratory as well as in naturalistic driving studies has shown that texting while driving seems to be the most dangerous driver distraction. However, there is still some discussion about the extent to which drivers adapt their behavior to the traffic situation. Accordingly, they might use their phones only in easy driving situations but refrain from doing so when driving becomes more demanding. For Germany, no reliable data on these topics could be found although overall smartphone use has also increased exponentially in this country. As observational studies have proven to be an effective means to gather these data, such a study was done observing 11,837 drivers in three big German cities (Braunschweig, Hannover, Berlin) during daytime. An alarmingly high rate of texting while driving was found (4.5%) as compared to other international studies. This was even more frequent than the use of handheld (2.2%) and hands-free (1.7%) phones combined. Thus, there seems to be a special problem in Germany with texting which should be further examined as this activity is highly distracting. Finally, there was some indication that drivers adapt their secondary task activities to the requirements of the driving task (e.g. somewhat less texting when moving than when stationary at a red traffic light). However, these adaptations were not very strong. Thus, drivers seem to underestimate the dangers due to distraction. This could be a starting point for countermeasures which increase this awareness of danger.     

Analysis of wall-function approaches using two-equation turbulence models

This paper focuses the attention on the drawbacks and abilities of wall-function techniques through an analysis of well-known wall-functions from literature. Besides this, some deeper analysis of these tools by means of physical and numerical considerations are carried out in order to improve their limitations when they are applied to predict heat transfer and fluid flow. Accuracy, grid-sensitivity, numerical behaviour and verification of numerical simulations are key aspects in this paper. The main purpose is to obtain tools which are able to predict both fluid flow and heat transfer with low CPU time consumption, reduced grid-sensitivity and a relatively good accuracy.     

Generalization of case studies in road traffic when defining pre-crash scenarios for active safety function evaluation

To define pre-crash scenarios for evaluation of active safety functions, data from crash investigations is often used. Typical data sources include official databases with police reported crashes (macroscopic data) and in-depth case studies (microscopic data). Macroscopic data is often representative but has little detail on causation, while the opposite is true of microscopic data. Combining the sources by coupling causation information from a set of case studies to a macroscopic crash type would therefore seem ideal. For the coupling to be valid however, it must be verified that the selected case study set is representative of the crash type. The aim of this study is to describe and test a new methodology for such verification by means of an intermediate layer of representatively sampled crash information (questionnaire responses from crash involved drivers). The methodology was applied to intersection crashes. For the data sets used, the similarity in crash causation for case studies and questionnaire crashes, together with the context similarity for questionnaire crashes and the macroscopic crash type, was sufficient to argue that the case studies were representative of the crash type. While results must be considered preliminary given the limited data sets used, the proposed methodology shows promise for future work related to defining pre-crash scenarios for ADAS evaluation.     

The cross-section of returns,benchmark model parameters,and idiosyncratic volatility of nuclear energy firms after Fukushima Daiichi

This study analyzes how the stock market returns, the factor loadings from the Carhart (1997) 4-factor model, and the idiosyncratic volatility of shares in energy firms have been affected by the Fukushima nuclear accident. Unlike existing studies, which provide evidence of a wealth transfer from nuclear to renewable energy firms for specific countries, we use an international sample and investigate whether changes in the regulatory environment and the firm-specific commitment to nuclear and renewable energies correlate with the capital market's reactions to the Fukushima Daiichi accident. Our findings suggest that the more a firm relies on nuclear power, the more its share price declined after the accident. A commitment to renewable energies does not prevent declines in share prices but significantly helps to reduce the increase in market beta that is associated with this event. Nuclear energy firms domiciled in countries with a higher number of regulatory interventions that were triggered by the catastrophe have lower abnormal returns than those that are domiciled elsewhere. However, as a cross-sectional analysis reveals, a stronger commitment to nuclear power is the main driver for negative stock market returns. Furthermore, nuclear energy firms domiciled in countries with stronger regulatory shifts away from nuclear energy experience significant increases in market beta and the book-to-market equity factor loading according to the Carhart (1997) 4-factor model. We conclude that capital market participants are able to differentiate between the affectedness of firms with respect to their product portfolio. Energy firms could prevent increases in market beta due to catastrophes such as the Fukushima Daiichi accident by shifting some of their energy production from nuclear to renewable or other sources.     

Decentralized intelligence in freight transport—A critical review

The purpose of this paper is to provide a research outlook on the concept of decentralized freight intelligence, i.e. autonomous freight making localized routing decisions. A review of research literature on decentralized intelligence in freight transport serves as the foundation of the analysis. The analysis reveals a scarcity of scientific evidence to suggest a successful introduction of decentralized freight intelligence. Among numerous conceptual findings, the analysis reveals a dearth of research on the clear and present challenges of introducing and adopting decentralized freight concepts in contemporary multi organizational open freight systems. For practitioners this paper provides useful input on future ICT development in the transport field. In particular, due to the lack of guidance on adoption of decentralized freight, a focus on non-networked benefits of information technology is to be recommended. Given the large number of projects, papers and various initiatives related to decentralized freight intelligence, this paper, to the authors’ best knowledge, provides a novel technology adoption perspective on decentralized freight intelligence research.     

Quality-driven optimization of system architecture: Industrial case study on an automotive sub-system

Due to the complexity of today's embedded systems and time-to-market competition between companies developing embedded systems, system architects have to perform a complex task. To design a system which meets all its quality requirements becomes increasingly difficult because of customer demand for new innovative user functions. Methods and tools are needed to assist the architect during system design.     

Look-ahead control for heavy trucks to minimize trip time and fuel consumption

The scenario studied is a drive mission for a heavy diesel truck. With aid of an on board road slope database in combination with a GPS unit, information about the road geometry ahead is extracted. This look-ahead information is used in an optimization of the velocity trajectory with respect to a criterion formulation that weighs trip time and fuel consumption. A dynamic programming algorithm is devised and used in a predictive control scheme by constantly feeding the conventional cruise controller with new set points. The algorithm is evaluated with a real truck on a highway, and the experimental results show that the fuel consumption is significantly reduced.