Search results

Existing three-dimensional (3D) road-surface models use approximation methods such as a set of discrete triangular patches and cannot accurately describe changes in the geometrically designed elements along the road. This paper aims to construct a 3D road-surface model with combinations of geometric design invariants and apply the proposed model to analyse the state of motion of a wheel’s centre.

In this paper, the 3D road surface is modelled as a continuous function with combinations of geometric design invariants. By introducing the theories of differential geometries and rigid body dynamics, a wheel-road model wherein a wheel fixed to a Darboux frame moves along a curved road surface is constructed, and the wheel time-dependent properties of the velocity, angular velocity and acceleration at an arbitrary point of the surface are described using road geometry design invariants.

This paper adopts the Darboux frame to study the instantaneous spin-rolling motion of a wheel. It is found that the magnitudes of the spin-rolling velocity, the acceleration and the geometric invariants of the road surface, including the geodesic curvature, the normal curvature and the geodesic torsion, determine the instantaneous states of motion of a wheel.

This work provides a theoretical foundation for future studies of wheel motion states, such as the relationship between road geometry design invariants and driving safety, vehicle lane changing and other vehicle microbehaviours. New insights are gained in the areas of road safety and vehicles incorporating artificial intelligence.

This paper presents the second-generation estimates for the Italian engineering industry in 1911, a year documented both by the customary demographic census, and the first industrial census. The first part of this paper uses the census data to estimate the industry’s value added, sector by sector; the second further disaggregates each sector by activity, and estimates the value added, employment, physical product, and metal consumption of each one. A third, concluding section dwells on the dependence of cross-section estimates on time-series evidence. Three appendices detail the specific algorithms that generate the present estimates; a fourth, a useful sample of firm-specific data.

Lane tracking is one of the most important processes for autonomous vehicles because the navigable region usually stands between the lanes, especially in urban environments. A robust lane tracking method is also required for reducing the effect of the noise and the required processing time. The purpose of this paper is to present a new lane tracking method.

A new lane tracking method is presented which uses a partitioning technique for obtaining multiresolution Hough transform of the acquired vision data where Hough transform is one of the most popular algorithms for lane detection. After the detection process, for tracking the detected lanes, a hidden Markov model (HMM) based method is proposed.

The results of the proposed approach show that the partitioned Hough transformation reduces the effect of noise and provides robust lane tracking. In addition, the acquired lanes are successfully tracked by using the designed HMM.

This paper provides a fast lane tracking system which can be integrated with an autonomous vehicle or a driver assistance system.

The paper aims to overcome the shortcomings that proportional‐integral‐derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual retuning, has large speed fluctuations and is hard to adjust control parameters. A novel control approach based on fuzzy neural network applied to URAT was proposed.

According to the target vehicle speed and driving command table, the multiple manipulator coordinated control model was established. After that, the displacement of throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for URAT was used as input of fuzzy neural network (FNN) model, and vehicle speed was used as output of FNN model. The number of membership functions was three, and the type of that was generalized bell membership function (gbellmf). The hybrid learning algorithm which combined with back propagation algorithm and least square method was applied to train the model. The Sugeno model was selected as fuzzy reasoning model.

Experimental results demonstrated that compared with PID control method, the proposed approach can greatly improve the accuracy of vehicle speed tracking. The approach can accurately realize the vehicle speed tracking of given driving test cycle. Therefore, it can ensure the accuracy and effectiveness of automotive test results.

Future work will focus on improving the efficiency of this learning algorithm.

The paper provides effective methods for improving the accuracy of speed tracking and repeatability.

After establishing the multiple manipulator coordinated control model, this paper proposes a novel control approach based on FNN for URAT.

The purpose of this paper is to improve the application of neural networks on vehicle engine systems for fault detecting and analysing engine oils.

Three types of neural networks are employed to find exact neural network predictor of vehicle engine oil performance and quality. Nevertheless, two oil types are analysed for predicting performance in the engine. These oils are used and unused oils. In experimental work, two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases.

The results of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases.

The results of the proposed neural network analyser follow the desired results of the vehicle engine's vibration variation. However, this kind of neural network scheme can be used to analyse oil quality of the car in experimental applications.

As theoretical and practical studies are evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area.

This paper is an original contribution on vehicle oil quality analysis using a proposed artificial neural network and it should be helpful for industrial applications of vehicle oil quality analysis and fault detection.

The purpose of this paper is to provide a methodology with which to perform variable screening and optimization in automotive crashworthiness design.

The screening method is based on response surface methodology in which linear response surfaces are used to create approximations to the design response. The response surfaces are used to estimate the sensitivities of the responses with respect to the design variables while the variance is used to estimate the confidence interval of the regression coefficients. The sampling is based on the D‐optimality criterion with over‐sampling to improve noise filtering and find the best estimate of the regression coefficients. The coefficients and their confidence intervals as determined using analysis of variance (ANOVA), are used to construct bar charts for the purpose of selecting the important variables.

A known analytical function is first used to illustrate the effectiveness of screening. Using the finite element method (FEM), a complex vehicle occupant impact problem and a full vehicle multidisciplinary problem featuring frontal impact and torsional modal analysis of the vehicle body are modeled and parameterized. Two optimizations are conducted for each FEM example, one with the full variable set and one with a screened subset. An iterative, successive linear approximation method is used to achieve convergence. It is shown that, although significantly different final designs may be obtained, an appropriately selected subset of variables is effective while significantly reducing computational cost.

The method illustrated provides a practical approach to the screening of variables in simulation‐based design optimization, especially in automotive crashworthiness applications with costly simulations. It is shown that the reduction of variables used in the optimization process significantly reduces the total cost of the optimization.

Although variable screening has been used in other disciplines, the use of response surfaces to determine the variable screening information is novel in the crashworthiness field.

The purpose of the paper is to identify the main determinants of the development of the neighbourhood electric vehicle (NEV) industry in China, including influences from private stakeholders as well as the government, and domestic as well as foreign interest groups. Particular emphasis is placed on the role of state‐owned enterprises (SOEs) and the relations between the government and the SOE sector.

The paper follows an inductive approach, and is largely based on interviews with industry actors and representatives for relevant government agencies, complemented with secondary data.

The preliminary findings suggest that unlike Western market economies, where the impact of public policy on innovation is relatively transparent and well recorded (in the form of fiscal and financial incentives and formal legislation), much of Chinese innovation is driven by less formal decisions taken in the nexus between SOEs and relevant state agencies. Hence, although China suffers no lack of legislation at various levels (including laws, decrees, and guidelines) it is often difficult to identify the specific drivers for change.

The findings are useful for understanding the development of the NEV industry in China.

The current paper is the first application of the GIST (Governance of Innovation towards Sustainability Technology) framework to the case of the Chinese NEV industry.

New services design and development are difficult to plan, execute, measure and evaluate. Particularly, new services that are capital-intensive and involve a long gestation and development time are considered extremely risky. The purpose of this paper is to discuss a list of innovative practices in various managerial aspects in designing, planning and development of a large scale infrastructure intensive public transportation service. A contemporary new public transportation service development is discussed as evidence of proven and benchmarked criteria.

This is a technical paper, where theoretical foundations of best practices in new service development project are discussed and supported by practice-based evidences from a real-life urban transportation project. A case study approach is adopted with secondary data.

Worldwide during and after economic recession of 2008, several projects were stalled or abandoned. The inference through this work is that through efficient management practices, a large capital-intensive new service development project can be made successful even during a turbulent economy in a region marred by more challenges than elsewhere.

Several issues in large scale services development, such as urban transportation are domain specific. Some of the issues faced in urban transportation are common to several Gulf countries; therefore the policy guidelines, managerial practices and development strategies reported in this paper can be replicated in many of them. The commercial impact of the service project is a significant drive towards fuel conservation and to save huge amounts of productive time.

Public transportation with a high quality of networked service improves the quality of life to a large extent. Unless certain measurable demands are not met, an affluent society is less likely to endorse public transportation. In addition, endorsement of public transportation is been promoted in several parts of the world as a drive towards a green, energy efficient, low-carbon emission and sustainable environment.

To the best of the authors’ knowledge, new services planning and development is a key operations management topic, on which very little is written about. Particularly no other paper has presented a real-world large scale infrastructure intensive project development to this detail, and along with a theoretical background to benchmark performance and development practices.

To examine how inventors are using natural systems and structures as models for technological innovation and design.

Looks at specific cases of how nature has been used in the invention of products.

The examples show that there are vast potential advantages to be gained from the mimicry of nature ranging from new applications opening up new markets, to improvements in performance, reduced manufacturing costs, and reduced pollution. Yet, despite all the successes and the growing acceptance of the principle, transplanting natural designs into man‐made technologies is still hit‐or‐miss affair.

This paper is useful to those who are investigating biomimetics.

Bicycle industry, emerging markets, competitor analysis, financial forecasting.

This case can be used as a teaching tool in the following courses: MBA/post-graduate programs in management in management accounting, management control systems and strategic cost management; executive training programs for middle and senior level employees; and under-graduate/post-graduate programs in entrepreneurship. It can be used to explain and test the concepts of SWOT analysis, Porter's five forces model and PEST analysis. It introduces the technique of breakeven analysis and its relationship with operating leverage. Moreover, it demonstrates the application and analyses of the Du Pont equation.

Hero Cycles Ltd was established by the four Munjal brothers in pre-independence India. It started off as a business of bicycle spare parts, but quickly expanded in post-independence India, with Ludhiana as its base. The company later joined with foreign firms like Honda Motors, Japan to become the largest manufacturers of bicycles in the world. It dominates domestic markets with a market share of around 40 percent. Ananth Munjal, a learned, ambitious and cautious individual, is the next generation, ready to take over the reins of the company. Being someone who believes in learning from past mistakes, he forms a team to critically examine the decisions made by his predecessors. This team is also directed to utilize forecasting techniques for determining the expected profitability given the existing state of affairs that prevail. Additionally, Du Pont analysis is to be performed for studying the efficiency of the company on the facets of operating performance, asset turnover and associated financial leverage. Also, Ananth's risk-averse nature compels him to study the past with regard to the relationship between operating leverage, breakeven sales and corresponding margin of safety. Furthermore, he wishes to inspect the historical cost structure of the firm, and its influence on company performance.

These include the use of: SWOT analysis to identify the strengths, weaknesses, opportunities and threats to a company; PEST analysis to identify the political, economic, social and technological factors that affect the operations of a company; Porter's five forces model to analyse an industry. The case also helps students: by identifying fixed costs and variable costs that are a part of operating expenditure of a business; in the use of forecasting the financials of a company for the sake of predicting the future outcomes of certain business strategies; by application of Du Pont analysis to examine the efficiency of the various processes and strategies; in determining quantitative terms like contribution margin, breakeven sales, operating leverage, margin of safety, their significance, and the relationship between these terms.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.