The project has been done in cooperation with Schenker Åkeri AB in Sweden, Halmstad. The project is based on an inspection made by Arbetsmiljöverket, where they found minor shortcomings with distribution of goods for the employees. The project is an investigation of the drivers’ working environment. Schenker Logistics is one of the world's leading providers of integrated logistics services. Schenker Åkeri AB is a subsidiary to Schenker Logistics and transports 2.4 million tons of goods yearly. The project started with a background study to evaluate drivers working environment. We have studied goods receptions, the working environment, strain injury and injury mechanisms. Methods used was observations, tests, questionnaire surveys and ergonomic and biomechanical calculations. One result of the study is a working model, which gives recommendations for the maximum weight a driver should push and pull. A truck evaluation was done to exam the need for new technical equipment. An ergonomic investigation was done to investigate the drivers’ working tasks. A questionnaire was given to the drivers to evaluate their working environment and tasks. The questionnaire involved questions about stress, handling of goods and technical equipment. Together with Schenker Åkeri AB in Halmstad, an action plan was made. This action plan will be handed over to Arbetsmiljöverket by Schenker.

Road transportation grew by 3.3 % per year over the past ten years which is faster than the economic growth of 2.3 % per year. European Commission plans for an increase of 55 % for road transportation between 2000 and 2020. This growth puts pressure on current trucking industry considering fuel consumption, emissions of green house gases, and traffic congestion.  High demand logistics industry and current pressure creates trends towards flexibility and longer vehicle combinations for efficiency and to reduce the number of engines on roads, challenging the current coupling methods of the trailers.  Primary method called 5th wheel coupling comes from a similar coupling used on 4 wheel horse-drawn carriages of the 19th century which is reliable in terms of attaching truck and trailer but has significant safety, efficiency and comfort issues for driver and the vehicles-people around.  So what if hauling setup could be safer and smarter?

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The safety requirements for vehicles are today high and they will become more stringent in the future. The car companies test their products every day to ensure that safety requirements are met. These tests are often done by professional drivers. If the car is tested in an everyday traffic situation, a normal experienced driver is desired. A drawback is that a human will eventually learn the manoeuvre he/she is told to do. An artificial driver is therefore to prefer to make the test repeatable. This thesis’ purpose is to develop and implement an artificial driver as a controller in order to follow a predefined trajectory. The driver model’s performance driving a double lane change manoeuvre should be as close to a real driver’s as possible. Data was gathered by inviting people to drive in a simulator. The results from the simulator tests were used to implement three different drivers with different experiences. The gathered data was used to categorize the test drivers into different driver types for each specific velocity by using the vehicle position from thetest results. This thesis studies the driver from a controller’s perspective and it resulted in two implemented controllers for reference tracking. The first approach was a Model Predictive Controller with reference tracking and the other approach was to use a FIR-filter in order to describe the drivers’ characteristics. A vehicle model was implemented in order to do the double lane change manoeuvre in a simulation environment together with the implemented driver model. The results show that the two approaches can be used for reference tracking. The MPC showed good results with the recreation of the test runs that were made by the categorized drivers. The FIR-filter had problems to mimic the drivers’ test runs and their characteristics. The advantage with MPC is its robustness, while the advantages with the FIR-filter are its, in comparison, simplicity in the implementation and the algorithm’s low computational cost. In order to make the FIR-filter more robust, some improvements have to be made. One improvement is to use gain scheduling in order to adjust the filter coefficients depending on thevelocity. / De säkerhetskraven som idag ställs på fordon är höga och det kommer bli mer strikt i framtiden. Bilföretag testar sina bilar varje dag för att se om komponenterna och bilen klarar säkerhetskraven som ställs. Till dessa tester används professionella testförare. I en vardaglig trafiksituation är det önskvärt att en normalt erfaren bilförare utför testen. En mänsklig förare kommer använda sin inlärningsförmåga vid repeterande manöver, vilket inte är önskvärt. En artificiell förare är därför att föredra. Den artificiella föraren ska köra så likt en verklig förare som möjligt vid en "double lane change"- (DLC) manöver. Detta examensarbete har som avsikt att implementera en förare som en regulator för att kunna följa en förutbestämd trajektoria på samma sätt som en verklig förare. I detta examensarbete har "DLC"-manövern studerats. I examensarbetet har insamlad data från testförare använts för att kunna implementera tre olika förartyper med olika erfarenheter. Den insamlade datan användes till att kategorisera testförarna för varje särskild hastighet. Två tillvägagångssätt har gjorts med föraren, en där föraren är en modellbaserad prediktionsregulator med referensignalsföljning (MPC) och en där föraren implementeras som ett ändligt impulssvarsfilter (FIR-filter). En fordonsmodell har implementerats för att en "DLC"-manöver ska kunna testas i en simuleringsmiljö. Resultaten blev att de två metoderna klarade av referensföljningen. MPC:n var bra på att återskapa testförararnas körningar. FIR-filtret hade problem med att härma förarnas körningar och deras karaktäristik. Fördelen med MPC är dessrobusthet och fördelen med FIR-filtret är dess, i jämförelse, simplicitet vid implementering samt den låga beräkningskostnaden för algoritmen. För att göra FIR-filtret mer robust måste förbättringar göras. En förbättring är att använda gain scheduling för att anpassa filterkoefficienterna beroende på hastigheten.

Den här uppsatsen visar att valutakursen och sekundärt energipriser har en hög förmåga att prediktera framtida rörelser i livsmedelspriser, både ”inom sample” och ”utanför sample”. Uppsatsen använder VAR-modeller och hittar empiriska belägg för att energipriser påverkar valutakursen (EUR/USD), som även indirekt påverkar livsmedelspriser. Teoretiskt och empiriskt visas att export- och produktionssubventioner reducerar eller ökar de ursprungliga priseffekterna vid chocker i valutakursen, och introducering av dessa samband visades öka precisionen av prognoserna. Resultatet är intressant för policybeslut eftersom identifieringen av vad som driver livsmedelspriserna visar att chocker i valutakursen har en omfattande effekt på framtida livsmedelspriser.

This paper presents the results of a focus group study exploring older individuals' perceptions of older drivers. The study extends the stereotype research of Joanisse, Gagnon, and Voloaca (2012b), further investigating the terms used to describe older drivers. Also explored were the ways older adults perceive age versus health in their considerations of driving. Three focus groups (N=24) were conducted with former and current drivers, 64 years and older, living in Asheville, North Carolina. Participants showed positivity in their descriptions of older drivers as "slow" and "cautious" and believed they adapted their driving behavior as aging demanded. Participants showed heterogeneity in their acceptance of the health issues that threatened their continued driving ability. The importance of context in understanding stereotypes of older adults is illustrated. Results are discussed in terms of ingroup/outgroup theory in line with the proposed model.

This research aims to examine how, and to what extent, the advanced network technology such as custom-built large-scale network, or internet-based technology contribute to the correlations between supply chain drivers and performance measures. The uniqueness of the research is to use network technology as a leverage factor, instead of merely one of the supply chain drivers, to analyse how it would impact on the correlations between supply chain drivers and performance measures. Through literature review, we identified the key drivers in supply chain and the key performance indicators as independent and dependent variables respectively for data analysis in the research. We consider the utilisation of network technology as a selection variable in the analysis. We also proposed a set of research questions and hypotheses resulting from the literature review. The subsequent data analyses attempted to find answers for these questions and test the validity of the hypotheses. This was achieved by a field survey for 1035 major Australian firms through a structured questionnaire. The response rate of the survey was 20.8%. All these data were analysed with statistical models such as reliability test, multi-collinearity test, MANOVA procedures, factor analysis, and multiple regression modelling to validate whether the survey was robust and how the leverage factor (network technology) would impact on the correlations between supply chain drivers and performance measures. Each research question and hypothesis was reviewed, validated, and concluded based on the results from data analysis. The key findings from the data analysis support the perception that the network technologies with their external customers and suppliers dramatically affect the correlations between supply chain drivers and performance measures. Statistically it actually determines whether the supply chain will success or fail when comparing firms using the technologies with firms not using them. In general, the impact on the correlations is directional and positive. A set of validated theoretical models was also proposed to depict the dynamics between supply chain variables under the influence of network technology. Implications of the findings are also provided in the thesis.

Obstructive sleep apnoea (OSA) is characterised by repetitive reductions or pauses in breathing during sleep due to upper airway narrowing or closure. Due to disruption to normal sleep patterns, many patients with OSA suffer from increased daytime sleepiness. Epidemiological studies have established a link between OSA and driver fatigue and accidents, generally showing a two to seven times increased risk of road traffic accidents in non-commercial drivers with OSA. There is emerging evidence that commercial drivers have a higher prevalence of OSA than the general population, being predominately male, middle-aged and overweight, three important risk factors for OSA. However, little is known about the relationship between OSA and driver sleepiness in commercial drivers, whether road accidents are increased in commercial drivers with OSA, and whether OSA interacts with other fatigue promoting factors, such as sleep deprivation, to further escalate road accident risk. One thousand randomly selected commercial drivers were surveyed in the field. In addition, 61 randomly selected NSW commercial drivers had in hospital sleep studies and daytime performance testing, including a PC based driving simulator task. The prevalence of OSA, defined as Respiratory Disturbance Index (RDI) < 10, was approximately 50% in NSW commercial drivers. Approximately one quarter of the drivers reported pathological daytime sleepiness, and 12-14% had both OSA and pathological daytime sleepiness. A diagnosis of OSA was the most important factor predicting excessive daytime sleepiness in these drivers: OSA was more important than 15 other work-related, lifestyle and medical factors that could be expected to promote, or be associated with, daytime sleepiness. Drivers with sleep apnoea syndrome (both OSA and pathological daytime sleepiness) had an increased driving accident risk, using driving simulator and daytime performance testing as proxy measures for accident risk. These results demonstrate the importance of OSA as a cause of driver fatigue in commercial drivers and suggest that all commercial drivers should be screened for the presence of sleep apnoea syndrome in order to potentially reduce road accident risk through treatment. A separate, but related body of work examined the combined effects of mild OSA and other fatigue promoting factors (sleep deprivation and circadian influences) on driving performance. Twenty nine subjects, consisting of a group with mild OSA and a group of non-OSA controls, were tested on several occasions throughout the night and day using an intensive performance battery, under both baseline conditions and after a period of 36 hours of total sleep deprivation. The results suggest that drivers with mild OSA are not different to the control group in their response to sleep deprivation or time of day influences. However, the subjects with mild OSA were less aware of their impairment due to sleep deprivation, which is of concern if drivers with OSA are relying on their subjective awareness of fatigue to make decisions about when to stop driving. A final perspective on OSA and driver fatigue is provided through a clinical case series of seven fall-asleep fatality associated MVA�s associated with unrecognised or under-treated sleep disorders. As well as demonstrating the day to day potential for devastating road accidents due, at least in part, to un-recognised or untreated sleep disorders, these cases also serve to highlight some of the current medico-legal controversies and difficulties in this area of driver fatigue. In conclusion, this body of work has provided novel information about the epidemiology and implications of OSA in commercial drivers, and about how OSA interacts with other fatigue promoting factors. Finally, it has explored some of the medico-legal issues that relate to sleep disorders and driver fatigue. As well as providing much needed information in the area of driver fatigue, at the same time this work raises many more questions and suggests areas of future research. For instance, such research should examine the relationship between objective accident rates and OSA/sleep apnoea syndrome in commercial drivers, the interaction between mild sleep apnoea syndrome and other fatigue risk factors, and driver perception of sleepiness prior to sleep onset in drivers with sleep disorders.

Thesis (M.S.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains vi, 94 p. Includes abstract. Includes bibliographical references (p. 89-93).

This thesis examines the interactions between road users and the factors that contribute to the occurrence of traffic accidents, and discusses the implications of these interactions with regards to driver behaviour and accident prevention measures. Traffic accident data is collected on a macroscopic level by local police authorities throughout the UK. This data provides a description of accident related factors on a macroscopic level which does not allow for a complete understanding of the interaction between the various road users or the influence of errors made by active road users. Traffic accident data collected on a microscopic level analysis of real world accident data, explaining why and how an accident occurred, can further contribute to a data driven approach to provide safety measures. This data allows for a better understanding of the interaction of factors for all road users within an accident that is not possible with other data collection methods. In the first part of the thesis, a literature review presents relevant research in traffic accident analysis and accident causation research, afterwards three accident causation models used to understand behaviour and factors leading to traffic accidents are introduced. A comparison study of these accident causation coding models that classify road user error was carried out to determine a model that would be best suited to code the accident data according to the thesis aims. Latent class cluster analyses were made of two separate datasets, the UK On the Spot (OTS) in-depth accident investigation study and the STATS19 national accident database. A comparison between microscopic (in-depth) accident data and macroscopic (national) accident data was carried out. This analysis allowed for the interactions between all relevant factors for the road users involved in the accident to be grouped into specific accident segmentations based on the cluster analysis results. First, all of the cases that were collected by the OTS team between the years 2000 to 2003 were analysed. Results suggested that for single vehicle accidents males and females typically made failures related to detection and execution issues, whereas male road users made diagnosis failures with speed as a particularly important factor. In terms of the multiple vehicle accidents the interactions between the first two road users and the subsequent accident sequence were demonstrated. A cluster analysis of all two vehicle accidents in Great Britain in the year 2005 and recorded within the STATS19 accident database was carried out as a comparison to the multiple vehicle accident OTS data. This analysis demonstrated the necessity of in-depth accident causation data in interpreting accident scenarios, as the resulting accident clusters did not provide significant differences between the groups to usefully segment the crash population. Relevant human factors were not coded for these cases and the level of detail in the accident cases did not allow for a discussion of countermeasure implications. An analysis of 428 Powered Two Wheeler accidents that were collected by the OTS team between the years 2000 to 2010 was carried out. Results identified 7 specific scenarios, the main types of which identified two particular looked but did not see accidents and two types of single vehicle PTW accidents. In cases where the PTW lost control, diagnosis failures were more common, for road users other than the PTW rider, detection issues were of particular relevance. In these cases the interaction between all relevant road users was interpreted in relation to one another. The subsequent study analysed 248 Pedestrian accidents that were collected by the OTS team between the years 2000 to 2010. Results identified scenarios related to pedestrians as being in a hurry and making detection errors, impairment due to alcohol, and young children playing in the roadside. For accidents that were initiated by the other road user s behaviour pedestrians were either struck after an accident had already occurred or due to the manoeuvre that a road user was making, older pedestrians were over-represented in this accident type. This thesis concludes by discussing how (1) microscopic in-depth accident data is needed to understand accident mechanisms, (2) a data mining approach using latent class clustering can benefit the understanding of failure mechanisms, (3) accident causation analysis is necessary to understand the types of failures that road users make and (4) accident scenario development helps quantify accidents and allows for accident countermeasure implication discussion. The original contribution to knowledge is the demonstration that when relevant data is available there is a possibility to understand the interactions that are occurring between road users before the crash, that is not possible otherwise. This contribution has been demonstrated by highlighting how latent class cluster analysis combined with accident causation data allows for relevant interactions between road users to be observed. Finally implications for this work and future considerations are outlined.