Thesis (M.S.)--California Polytechnic State University, 2009. / Title from PDF title page; viewed on Nov. 16, 2009. "October 2009." "In partial fulfillment of the requirements for the degree [of] Master of Science in Mechanical Engineering." "Presented to the faculty of California Polytechnic State University, San Luis Obispo." Major professor: Charles Birdsong, Ph.D. Includes bibliographical references (p. 76-77).

The purpose of this study is to measure the costs of the perceived safety threat from triple trailer operation in Oregon. This is done using the political referendum model of a common non-market valuation technique, contingent valuation. Specifically, the average cost of allowing triples will be found so that comparison with previously estimated benefits will provide a measure of net social welfare associated with triple trailer use. The data were collected through in-person interviews conducted in five regions in Oregon. Questions relating to the respondents' attitudes toward triple trailer trucks, driving experience, education and other demographics were asked. The empirical model estimates the probability that respondents will vote to ban triple trailers. The results of this study suggest that there are concerns about the safety of triple trailer operation. However, there seem to be still greater benefits; a result which is consistent with the recent ballot measure. / Graduation date: 1995

This study investigated the performance and cost of scarification with a tractormounted excavator. Due to variations in terrain conditions the performance variedbetween 0.08 and 0.11 ha/E15h and, with a machine cost of 366 SEK/h, the cost ofscarification varied between 3 330 and 4 750 SEK/ha.

Manoeuvring a vehicle with additionally attached trailers is a tedious task. Albeit driver assistance systems support the driver in nearly any situation in these days, tools facilitating the manoeuvring process of extended vehicles can only rarely be found in research and especially in the market. This thesis deals with the prototypical implementation of a rear view camera parking assistance system. In particular, the visualisation of the predicted driving path of the tractor-trailer combination in the camera image is emphasised, following the representation of existing parking assistance systems for individual vehicles. A general approach is aiming at the portability of the system to nearly any kind of trailer. The superimposed guidelines are based on a state space model, which is derived on top of assumptions agreeing with results found in the literature. Due to the strong assumptions and simplifications, the model is tested in three different ways and moreover for different types of trailers. All underlying methods are described in detail and furthermore tested in several scenarios, if necessary. Special importance is attached to the comparison of the actual driven paths with their previous predictions, for which a new method has been derived, implemented and tested successfully. Beside the implementation of the guideline projection to the camera’s image, the human-machine interface is augmented by a Bird’s Eye view animation, too. A final test of the integrated system for different types of trailers shows the proper operation of the overall system during parking situations.

Laser Measurement Systems (LMS) are used in autonomous agricultural vehicles for guidance and obstacle detection purposes. In the particular case of agricultural vehicles, the efficiency of LMS measurements is affected by mechanical vibrations induced by the operation of these machines on uneven terrains. The objective of this study was to evaluate the effectiveness of a mounting system capable of reducing the transmission of mechanical vibrations to an LMS sensor installed on an agricultural tractor for the purpose of improving the detection accuracy of obstacles during field operation. A stabilization system (SS) was designed for a SICK LMS 291-S14 scanner. The LMS sensor and the SS were installed on an agricultural tractor to scan four objects positioned at known locations in the field. An experimental analysis was carried out to evaluate the detection accuracy of the LMS sensor under different operating conditions: with and without SS; with and without support bars (S); and for different types of terrains (in terms of roughness) and field operating speed. The detection accuracy of the LMS sensor was assessed by determining the difference between the known location of the four objects and their corresponding estimated location from the LMS measurements. The increase of tractor speed had a negative effect on the accuracy of the LMS sensor with an increase in the positioning error of up to 75%. However, it was not possible to establish a clear relationship between terrain roughness and the accuracy of the LMS sensor. The addition of the S systems positively affected the accuracy of the LMS sensor and resulted in a 41% decrease of the average positioning error from 0.340 to 0.201 m. Finally, the used of the SS mounting system decreased the average positioning error by 57% from 0.382 to 0.161 m. These experimental results confirmed the effectiveness of the joint use of the SS and S mounting systems in improving the accuracy of the LMS sensor mounted on an agricultural tractor through a reduction in transmitted vibrations.

An autonomous machine is a machine that can navigate through its environment without human interactions. These machines use sensors to sense the environment and have computing abilities for receiving and interpreting the sensory data as well as for controlling their displacement. At the University of Saskatchewan (Saskatoon, Canada), a low level autonomous machine was developed. This low level machine was the sensor system for an autonomous machine. The machine was capable of sensing the environment and carrying out actions based on commands sent to it. This machine provided a sensing and control layer, but the path planning (decision making) part of the autonomous machine was not developed.<p>This autonomous machine was developed on a Case IH DX 34H tractor with the purpose of providing a machine for testing software and sensors in a true agricultural environment. The tractor was equipped with sensors capable of sensing the speed and heading of the tractor. A control architecture was developed that received input commands from a human or computer in the form of a target heading and speed. The control architecture then adjusted controls on the tractor to make the tractor reach and maintain the target heading and speed until a new command was provided. The tractor was capable of being used in all kinds of weather, although some minor issues arose when testing in rain and snow. The sensor platform developed was found to be insufficient for proper control. The control structure appeared to work correctly, but was hindered by the poor sensor platform performance.

An autonomous machine is a machine that can navigate through its environment without human interactions. These machines use sensors to sense the environment and have computing abilities for receiving and interpreting the sensory data as well as for controlling their displacement. At the University of Saskatchewan (Saskatoon, Canada), a low level autonomous machine was developed. This low level machine was the sensor system for an autonomous machine. The machine was capable of sensing the environment and carrying out actions based on commands sent to it. This machine provided a sensing and control layer, but the path planning (decision making) part of the autonomous machine was not developed.<p>This autonomous machine was developed on a Case IH DX 34H tractor with the purpose of providing a machine for testing software and sensors in a true agricultural environment. The tractor was equipped with sensors capable of sensing the speed and heading of the tractor. A control architecture was developed that received input commands from a human or computer in the form of a target heading and speed. The control architecture then adjusted controls on the tractor to make the tractor reach and maintain the target heading and speed until a new command was provided. The tractor was capable of being used in all kinds of weather, although some minor issues arose when testing in rain and snow. The sensor platform developed was found to be insufficient for proper control. The control structure appeared to work correctly, but was hindered by the poor sensor platform performance.

Buying behaviour is a complex, wide– ranging field, intricately associated with human mental processes, responding to environmental stimuli. Understanding the customer and being able to predict their behaviour, is of prime importance to all marketers and marketing strategists for two reasons: Firstly because, the overall strategy of the company has to be clearly reflected in the marketing strategy for any meaningful progress. Secondly, to be able to adjust or adapt the marketing effort to changing marketing conditions. The focus of this study is to research the buying behaviour of farmers through the marketing mix paradigm. Although slightly contentious in terms of recent theories and field of application, the dichotomous nature of farmers buying behaviour and the characteristics of the purchase makes this theory a good fit for the circumstances. The marketing mix theory focuses on the controllable external stimuli which reinforces the practical application of this study. The buying behaviour of farmers was researched by asking farmers to evaluate the importance of a statement related to an element of the marketing mix theory by telephonic interview. The answers of the farmers were analysed using various statistical methods and the following salient results were obtained: All the elements of the marketing mix theory are important to farmers when deciding on buying a new tractor. The less experienced farmers rated all the elements of the marketing mix as more important than more experienced farmers. There was a definitive subset of farmers for whom the more changeable part of the marketing mix, price and promotion, had a definite impact on their decision. Price and promotion did not correlate with farmers who viewed the product of high importance. Other results indicated that the farmers in the test sample bought a new tractor every 2.3 years with 54% of farmers buying a new tractor in the past year. The frequency with which farmers buy new tractors shows the importance of the market. The finding that the elements of the marketing mix theory are important to farmers was expected and could serve as an incentive for future research. The marketing mix theory is viewed as highly applicable in this case, due to its relative simplicity and the focus on the more controllable stimuli on the farmer. It was also found that for a significant subset of farmers the more modifiable elements had a definitive impact on their decision when buying a tractor. This offers an opportunity to marketers willing to respond to changing uncontrollable conditions to influence buying decisions in the short term. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2012.

Buying behaviour is a complex, wide– ranging field, intricately associated with human mental processes, responding to environmental stimuli. Understanding the customer and being able to predict their behaviour, is of prime importance to all marketers and marketing strategists for two reasons: Firstly because, the overall strategy of the company has to be clearly reflected in the marketing strategy for any meaningful progress. Secondly, to be able to adjust or adapt the marketing effort to changing marketing conditions. The focus of this study is to research the buying behaviour of farmers through the marketing mix paradigm. Although slightly contentious in terms of recent theories and field of application, the dichotomous nature of farmers buying behaviour and the characteristics of the purchase makes this theory a good fit for the circumstances. The marketing mix theory focuses on the controllable external stimuli which reinforces the practical application of this study. The buying behaviour of farmers was researched by asking farmers to evaluate the importance of a statement related to an element of the marketing mix theory by telephonic interview. The answers of the farmers were analysed using various statistical methods and the following salient results were obtained: All the elements of the marketing mix theory are important to farmers when deciding on buying a new tractor. The less experienced farmers rated all the elements of the marketing mix as more important than more experienced farmers. There was a definitive subset of farmers for whom the more changeable part of the marketing mix, price and promotion, had a definite impact on their decision. Price and promotion did not correlate with farmers who viewed the product of high importance. Other results indicated that the farmers in the test sample bought a new tractor every 2.3 years with 54% of farmers buying a new tractor in the past year. The frequency with which farmers buy new tractors shows the importance of the market. The finding that the elements of the marketing mix theory are important to farmers was expected and could serve as an incentive for future research. The marketing mix theory is viewed as highly applicable in this case, due to its relative simplicity and the focus on the more controllable stimuli on the farmer. It was also found that for a significant subset of farmers the more modifiable elements had a definitive impact on their decision when buying a tractor. This offers an opportunity to marketers willing to respond to changing uncontrollable conditions to influence buying decisions in the short term. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2012.

Laser Measurement Systems (LMS) are used in autonomous agricultural vehicles for guidance and obstacle detection purposes. In the particular case of agricultural vehicles, the efficiency of LMS measurements is affected by mechanical vibrations induced by the operation of these machines on uneven terrains. The objective of this study was to evaluate the effectiveness of a mounting system capable of reducing the transmission of mechanical vibrations to an LMS sensor installed on an agricultural tractor for the purpose of improving the detection accuracy of obstacles during field operation. A stabilization system (SS) was designed for a SICK LMS 291-S14 scanner. The LMS sensor and the SS were installed on an agricultural tractor to scan four objects positioned at known locations in the field. An experimental analysis was carried out to evaluate the detection accuracy of the LMS sensor under different operating conditions: with and without SS; with and without support bars (S); and for different types of terrains (in terms of roughness) and field operating speed. The detection accuracy of the LMS sensor was assessed by determining the difference between the known location of the four objects and their corresponding estimated location from the LMS measurements. The increase of tractor speed had a negative effect on the accuracy of the LMS sensor with an increase in the positioning error of up to 75%. However, it was not possible to establish a clear relationship between terrain roughness and the accuracy of the LMS sensor. The addition of the S systems positively affected the accuracy of the LMS sensor and resulted in a 41% decrease of the average positioning error from 0.340 to 0.201 m. Finally, the used of the SS mounting system decreased the average positioning error by 57% from 0.382 to 0.161 m. These experimental results confirmed the effectiveness of the joint use of the SS and S mounting systems in improving the accuracy of the LMS sensor mounted on an agricultural tractor through a reduction in transmitted vibrations.