The conventional information used to guide automobile drivers in selecting their driving routes is the shortest-distance path (SDP). As several researchers have pointed out, driver route selection is a multiple criteria decision process. This research proposes a multiobjective path optimisation (MOPO) decision model to make a more precise simulation of the decision-making behaviour of driver route selection. Seven single-objective path optimisation (SOPO) decision models are taken into account to establish the MOPO decision model. They relate to travel time, travel cost, cumulative distance, roadway capacity, roadway grade, passed intersections and number of turns. To solve the MOPO problem, a two-stage technique which incorporates shortest path (SP) algorithms and techniques for solving the multiobjective programming problem and a path genetic algorithm (PGA) are proposed. In addition, algorithms such as Dijkstra, A* and GA are reviewed and algorithms that are applicable for solving the MOPO problems are suggested. Furthermore, new algorithms for solving least-node path (LNP) problem, corresponding to the objective of passed intersections, as well as minimum-turn path (MTP) problem, corresponding to the objective of number of turns, are developed. To conduct the empirical study, a software tool - the multiobjective path optimisation analysis tool (MOPOAT) - was implemented. It contains tools for constructing a road network and its corresponding network topology, the environment of coding techniques for solving the MOPO problems and tools for the manipulation, statistics, analysis and display of experimental results. The purpose of implementing the MOPOAT software is to provide more efficient, convenient and user-friendly tools for solving MOPO and SOPO problems so that an empirical study of real road networks can be carried out more easily. To demonstrate the advantages of the proposed model in supporting more diverse information to drivers to assist in route selection, several experiments were conducted utilising three real road networks with different roadway types and numbers of nodes and links. Techniques and algorithms such as the two-stage approach, Dijkstra and the PGA for solving the MOPO problem, and the Dijkstra, LNP and MTP algorithms for solving the SOPO problems were applied. Finally, to deal with improvements in computational efficiency for identifying SPs in a large road network and for population initialisation of the PGA, the critical-section (CS) approach and the seed-path expansion (SPE) approach are proposed. To compare the run time between the conventional SP and CS algorithms as well as the PGA and the SPE algorithms, tools were implemented with commercial GIS, and experimental tests were conducted using road networks with a large amount of nodes and links and different roadway types. Through these theoretical and empirical studies, several useful contributions and conclusions were obtained. Some of the most significant findings are: 1. The experimental results demonstrate the advantages of integration with commercial GIS packages in supporting both spatial and attribute data displays. It can be safely said that, assisted by the MOPOAT software, it is easy for automobile drivers to obtain the optimal paths of the SDP, LNP, MTP and MOPO problems in seconds, despite these problems being highly complex and difficult to resolve manually. 2. According to the experimental results, the proposed LNP, MTP and MOPO decision models give automobile drivers richer information for choosing their driving routes in a more diverse way. 3. It is shown by the experimental results that the SDP and LNP mostly locate different paths in both radial-circumferential and grid-type road networks, and that the total passed intersections by the SDP are greater than passed by the LNP. Moreover, it is revealed that ambiguous turns might occur in both radial-circumferential and grid-type road networks. 4. It is found that the number of nodes of the SDP is in general greater than the number of nodes of the LNP and MTP irrespective of the type of road network. 5. A sensitivity analysis for weights shows that as the weighting value of the SDP objective incrementally increases by 0.1 units, the corresponding SDP??s objective value varies either low or high. The same results also occur for the LNP and MTP objectives. This verifies the fact that the weighting coefficients do not reflect proportionally the relative importance of the objectives. Moreover, the MTP objective has the higher sensitivity in comparison with the other two objectives. 6. Despite utilising Dijkstra or PGA algorithms for solving the MOPO problem, the LNP and MTP algorithms have to be employed to solve the non-commeasurable problem, whereby the standardisation objective value can be obtained. In addition, without any assisting information the PGA might fail to reach the best-compromise solution. 7. It is found that the total run time for solving the MOPO problem by applying the Dijkstra algorithm is much faster than by the PGA. However, if the run time excludes the time needed for population initialisation, the PGA is much faster than the Dijkstra algorithm. 8. Based on calculated bottlenecks, the proposed CS approach partitions a SP into many critical sections in advance, with the result that a long SP can be obtained by combining all SPs of all CSs. The experimental results show that the run time of the CS algorithm is much faster than Dijkstra??s algorithm. Moreover, the test result for the P-pointer indicates that if the total number of nodes of a SP grows the computational efficiency of the CS algorithm becomes significantly better than the Dijkstra algorithm, and that the CS approach has the best performance. 9. The experimental result for the E-pointer reveals that the computational efficiency of the CS algorithm will decrease gradually as the number of selected CSs increases. Therefore, the total percentage of selected CSs suggested by the experimental result is no more than 30 percent. 10. According to the experimental results, the performance order among SDP, LNP and MTP algorithms from fast to slow is SDP, MTP and LNP, and the LNP algorithm requires much more time than the other two algorithms. 11. As the total nodes of a path increase, most of the run time for SDP and LNP also increases. However, there are still some paths that violate the above rule. This result verifies that the run time needed for solving SDP and LNP is not only affected by the node numbers but also depends on the network topology. 12. Run time for solving the MOPO problem by applying the PGA is faster than applying the Dijkstra algorithm, if the run time of the former algorithm does not take into account the population initialisation time. Nevertheless, if the run time of the former algorithm does take into account the population initialisation time, the latter algorithm is much faster than the former algorithm. 13. In comparing the run time for population initialisation, the run time of the evolution process by applying the PGA is quite small, and the bottleneck of the run time for solving MOPO problem by applying the PGA is the population initialisation. 14. The population initialisation time is reduced significantly by applying the SPE algorithm, and increases at a very slow rate as the number of nodes of a path increases. As the total nodes of a path grow ever larger, the computing time is reduced more noticeably.

The conventional information used to guide automobile drivers in selecting their driving routes is the shortest-distance path (SDP). As several researchers have pointed out, driver route selection is a multiple criteria decision process. This research proposes a multiobjective path optimisation (MOPO) decision model to make a more precise simulation of the decision-making behaviour of driver route selection. Seven single-objective path optimisation (SOPO) decision models are taken into account to establish the MOPO decision model. They relate to travel time, travel cost, cumulative distance, roadway capacity, roadway grade, passed intersections and number of turns. To solve the MOPO problem, a two-stage technique which incorporates shortest path (SP) algorithms and techniques for solving the multiobjective programming problem and a path genetic algorithm (PGA) are proposed. In addition, algorithms such as Dijkstra, A* and GA are reviewed and algorithms that are applicable for solving the MOPO problems are suggested. Furthermore, new algorithms for solving least-node path (LNP) problem, corresponding to the objective of passed intersections, as well as minimum-turn path (MTP) problem, corresponding to the objective of number of turns, are developed. To conduct the empirical study, a software tool - the multiobjective path optimisation analysis tool (MOPOAT) - was implemented. It contains tools for constructing a road network and its corresponding network topology, the environment of coding techniques for solving the MOPO problems and tools for the manipulation, statistics, analysis and display of experimental results. The purpose of implementing the MOPOAT software is to provide more efficient, convenient and user-friendly tools for solving MOPO and SOPO problems so that an empirical study of real road networks can be carried out more easily. To demonstrate the advantages of the proposed model in supporting more diverse information to drivers to assist in route selection, several experiments were conducted utilising three real road networks with different roadway types and numbers of nodes and links. Techniques and algorithms such as the two-stage approach, Dijkstra and the PGA for solving the MOPO problem, and the Dijkstra, LNP and MTP algorithms for solving the SOPO problems were applied. Finally, to deal with improvements in computational efficiency for identifying SPs in a large road network and for population initialisation of the PGA, the critical-section (CS) approach and the seed-path expansion (SPE) approach are proposed. To compare the run time between the conventional SP and CS algorithms as well as the PGA and the SPE algorithms, tools were implemented with commercial GIS, and experimental tests were conducted using road networks with a large amount of nodes and links and different roadway types. Through these theoretical and empirical studies, several useful contributions and conclusions were obtained. Some of the most significant findings are: 1. The experimental results demonstrate the advantages of integration with commercial GIS packages in supporting both spatial and attribute data displays. It can be safely said that, assisted by the MOPOAT software, it is easy for automobile drivers to obtain the optimal paths of the SDP, LNP, MTP and MOPO problems in seconds, despite these problems being highly complex and difficult to resolve manually. 2. According to the experimental results, the proposed LNP, MTP and MOPO decision models give automobile drivers richer information for choosing their driving routes in a more diverse way. 3. It is shown by the experimental results that the SDP and LNP mostly locate different paths in both radial-circumferential and grid-type road networks, and that the total passed intersections by the SDP are greater than passed by the LNP. Moreover, it is revealed that ambiguous turns might occur in both radial-circumferential and grid-type road networks. 4. It is found that the number of nodes of the SDP is in general greater than the number of nodes of the LNP and MTP irrespective of the type of road network. 5. A sensitivity analysis for weights shows that as the weighting value of the SDP objective incrementally increases by 0.1 units, the corresponding SDP??s objective value varies either low or high. The same results also occur for the LNP and MTP objectives. This verifies the fact that the weighting coefficients do not reflect proportionally the relative importance of the objectives. Moreover, the MTP objective has the higher sensitivity in comparison with the other two objectives. 6. Despite utilising Dijkstra or PGA algorithms for solving the MOPO problem, the LNP and MTP algorithms have to be employed to solve the non-commeasurable problem, whereby the standardisation objective value can be obtained. In addition, without any assisting information the PGA might fail to reach the best-compromise solution. 7. It is found that the total run time for solving the MOPO problem by applying the Dijkstra algorithm is much faster than by the PGA. However, if the run time excludes the time needed for population initialisation, the PGA is much faster than the Dijkstra algorithm. 8. Based on calculated bottlenecks, the proposed CS approach partitions a SP into many critical sections in advance, with the result that a long SP can be obtained by combining all SPs of all CSs. The experimental results show that the run time of the CS algorithm is much faster than Dijkstra??s algorithm. Moreover, the test result for the P-pointer indicates that if the total number of nodes of a SP grows the computational efficiency of the CS algorithm becomes significantly better than the Dijkstra algorithm, and that the CS approach has the best performance. 9. The experimental result for the E-pointer reveals that the computational efficiency of the CS algorithm will decrease gradually as the number of selected CSs increases. Therefore, the total percentage of selected CSs suggested by the experimental result is no more than 30 percent. 10. According to the experimental results, the performance order among SDP, LNP and MTP algorithms from fast to slow is SDP, MTP and LNP, and the LNP algorithm requires much more time than the other two algorithms. 11. As the total nodes of a path increase, most of the run time for SDP and LNP also increases. However, there are still some paths that violate the above rule. This result verifies that the run time needed for solving SDP and LNP is not only affected by the node numbers but also depends on the network topology. 12. Run time for solving the MOPO problem by applying the PGA is faster than applying the Dijkstra algorithm, if the run time of the former algorithm does not take into account the population initialisation time. Nevertheless, if the run time of the former algorithm does take into account the population initialisation time, the latter algorithm is much faster than the former algorithm. 13. In comparing the run time for population initialisation, the run time of the evolution process by applying the PGA is quite small, and the bottleneck of the run time for solving MOPO problem by applying the PGA is the population initialisation. 14. The population initialisation time is reduced significantly by applying the SPE algorithm, and increases at a very slow rate as the number of nodes of a path increases. As the total nodes of a path grow ever larger, the computing time is reduced more noticeably.

Doctor of Philosophy (PhD) / Changing the behaviour of firms to take environmental concerns into account is seen as unlikely without effective regulations. However, corporations are increasingly keen to represent themselves as ‘green’, including those in the world’s largest manufacturing sector: the car industry. Given rising concern for the environment and environmental sustainability since the 1990s this thesis asks: what motivates car firms to actually make environmental commitments? Answering this question has implications for whether these commitments are ‘real’ and if so whether they are occurring in response to material factors (e.g. state regulations and consumer demand) versus normative factors (e.g. social attitudes and internal company strategies). In order to answer it, the thesis applies the insights of the institutional varieties of capitalism approach to the German, United States and Japanese car industries, and specific firms within them, in respect of the environmental issue of climate change from 1990 to 2004. Empirical national data is analysed, as well the environmental reporting of individual firms and interviews with key personnel. The main findings are that what leads the car industry to see environmental issues as central to their business interests hinges on the impact of differing national institutional factors. Specifically, it is a matter of whether firms have a liberal market economy (LME) as their home base, in the case of US firms, or a coordinated market economy (CME) as their home base, in the case of German and Japanese firms. US car firms react more to the material imperatives of consumer demand and state regulations. German and Japanese firms are more mindful of normative factors for their initiatives, such as social attitudes (especially for German firms) and internal company strategies (especially for Japanese firms). They have more of a partnership approach with government. Therefore, car firms have very distinct ‘lenses’ through which they see the environmental performance of the cars they produce. As such, the thesis concludes that the variety of capitalism of nations has implications not just for the type of products that economic actors such as car firms produce, and the competitive advantages they develop, but also the way they address related issues arising as a result of their activities, including environmental issues.

Thesis (Ph.D.) - Carleton University, 2006. / Includes bibliographical references (p. 256-262). Also available in electronic format on the Internet.

Thesis (M.A.)--Ball State University, 2009. / Title from PDF t.p. (viewed on July 12, 2010). Research paper (M.A.), 3 hrs. Includes bibliographical references (p. 76-80).

Thesis--Yale University, 1971. / "72-17,134." "A note on sources": leaves [399]-415.

This research is concerned with exploring the relationship between car driving and musculoskeletal troubles and following on from this investigating methods which could aid the automotive industry in the design and evaluation of car seats. The thesis is divided into two parts. Part I describes the development and results of an epidemiological survey undertaken with data obtained from two sample groups. Study 1 was an interview survey (based on the Nordic Questionnaire) of 600 members of the British public, randomly selected within the strata of age and gender. Study 2 used the same interview, but with two carefully chosen groups of police officers (n=200). The results indicated that car drivers (especially those who drove as part of their job) appeared to be at risk in terms of reported discomfort and sickness absence due to low back trouble. Evidence from this and other studies has also indicated that drivers with the most adjustable driving packages may benefit in terms of both reduced discomfort and reduced sickness absence. This provided the background for the subsequent research in Part II and some impetus for car manufacturers to consider health issues in the design of car workstations. Part II involved a series of three experiments designed to investigate methodologies which could be used by manufacturers to predict car seat discomfort The literature was reviewed to identify suitable predictive techniques which would be robust enough to provide information to the automotive industry in 'real world' situations. The technique of interface pressure measurement had already generated interest in some seat manufacturers and was therefore selected for investigation. As a result of the findings in experiment 1, established guidelines for a comfortable driving posture may need to be modified. The other two experiments were designed to create discomfort in subjects firstly by varying foam hardness and secondly by varying posture. A clear, simple and consistent relationship between interface pressure and discomfort in realistic driving situations was not identified. Future studies using this technique should provide information regarding such factors as gender, the body mass index, anthropometric data, posture and foam hardness due to the confounding nature of these variables.

No description available.

To achieve passive vibration control, an adaptive flywheel design is proposed and fabricated from two different materials. The corresponding mathematical models for the adaptive flywheels are developed. A two-terminal hydraulic device and a two-terminal inverse screw device are introduced to analyze the two adaptive flywheels. Experiments are carried out to identify key parameters for both the two-terminal hydraulic system and the inverse screw system. The performance of three different suspension systems are evaluated; these are the traditional suspension system, the suspension system consisting of an ideal two-terminal device with constant flywheel and the suspension system consisting of an ideal two-terminal device with an adaptive flywheel (AFW suspension system). Results show that the AFW suspension system can outperform the other two suspension systems under certain conditions. The performance of a suspension system with the adaptive flywheel under different changing ratio is evaluated, and an optimal changing ratio is identified under certain circumstances. To obtain the steady-state response of the two-terminal device with adaptive flywheel, three different methods have been applied in this thesis. These methods are the single harmonic balance method, the multi-harmonic balance method and the scanning iterative multi-harmonic balance method, respectively. Compared to the single harmonic balance method, the multi-harmonic balance method provides a much more accurate system response. However, the proposed scanning iterative multi-harmonic balance method provides more accurate system response than the single harmonic balance method with much less computational effort.

This master thesis deals with the unique idea of sharing vehicles called car sharing. Thesis is divided into two parts, theoretical and practical. Theoretical part describes the basic concept of car sharing as a concept of a new development of a lifestyle spread around the world. Car sharing is described as a source of new ecological and convenient way of transport. This paper looks at the history behind the carsharing, car sharing organizations model as part of different forms of carsharing, as well as benefits and environmental effects that are associated with this revelation. It describes a view of this concept in different countries in Europe and in the US. Focus is then made on the situation in Czech republic, more specifically on the first carsharing company Autonapul on the czech market. Practical part emphasizes carsharing situation in Czech republic, providing list of different car companies on the market. It looks at situation in the capital city, Prague, and suggests the new marketing strategy for the oldest company.