Analysis of a large injection-molded body using knowledge-based flow process technology

A knowledge-based flow process is presented for large injection-molded body technology (LIMBT). Injection molding of a large body is a difficult technique because of the many factors and their interactions during the molding process. The proposed flow process can support LIMBT through integration of CAE(Computer-Aided Engineering), CAI (Computer-Aided Inspection), and monitoring systems. CAE and DOE (Design of Experiment) are used to construct an optimal mold design in terms of gates and runners and to identify working conditions for the molding process. CAI and monitoring systems with temperature sensors and pressure sensors can be used to inspect the physical molding process and the molded parts. The flow process of a large body is systematically planned and constructed using a knowledge-based flow process with DOE and computer-aided technologies. The proposed flow process is implemented for the molding process of an automobile front bumper fascia.     

Lateral controller design for an unmanned vehicle via Kalman filtering

This paper proposes a lateral control system for an unmanned vehicle that is designed to improve the responsiveness of the system with the use of a PD control. The vehicle heading error can be stabilized, and the transient response characteristics can be improved using the proposed controller. A mathematical model of the vehicle dynamics using two degrees of freedom was developed for the controller design. The waypoint tracking method for autonomous navigation was tested with incorporation of the Point-to-Point algorithm with position and heading measurements received from GPS receivers via Kalman filtering. The performance of the designed controller was verified through experiments with a real vehicle.     

Travel differences by gender for older people in London

As a guarantee of life quality, older people’s travel demand has to be satisfied, so understanding their travel demand is important. An important point to bear in mind is that older people are not a homogeneous group but that distinguishing between older women and older men in their mobility needs and travel patterns is necessary. Older people’s travel demand needs to be investigated from many different aspects, including trip generation, travel time, and mode choice. In this study, the investigation is focused on older people’s trip chaining, including trip chain complexity, tour composition in a chain.     

Estimating traffic volumes on intercity road locations using roadway attributes,socioeconomic features and other work-related activity characteristics

Traffic volume data are key inputs to many applications in highway design and planning. But these data are collected in only a limited number of road locations due to the cost involved. This paper presents an approach for estimating daily and hourly traffic volumes on intercity road locations combining clustering and regression modelling techniques. With the aim of applying the procedure to any road location, it proposes the use of roadway attributes and socioeconomic characteristics of nearby cities as explanatory variables, together with a set of previously discovered patterns with the hourly traffic percent distribution. Test results show that the proposed approach significantly produces accurate estimates of daily volumes for most locations. The accuracy at hourly level is a bit more reduced but, for periods when traffic is significant, more than half of the estimates are within 20% of absolute percentage error. Moreover, the main peak period is approximately identified for most cases. These findings together with its great applicability make this approach attractive for planners when no traffic data are available and an estimate is helpful.     

The acceptability of road pricing in Vienna: the preference patterns of car drivers

The acceptability of road pricing has attracted considerable attention among researchers over the last decade, as is evident in the amount of literature about transport and environmental economics. The general conclusion from these studies has been that there is low acceptability for road pricing among car users. In this paper, we add more knowledge to the existing literature by conducting an acceptability study of road pricing in Vienna, where such a study has never been conducted before. We used a replication study approach where a previous approach used in the EU research project AFFORD (acceptability of fiscal and financial measures and organisational requirements for demand management) was replicated for Vienna and further supplemented with a conjoint analysis. In order to examining whether the Vienna study confirms previous findings. We investigated the acceptability of two concrete policy packages factors influencing this acceptability, and preference patterns that can be used in designing a road pricing policy for Vienna. The survey reveals a higher acceptability if road pricing schemes lead to perceived personal benefits. According to the multivariate analyses, the “personal outcome expectations”, “social norm” and “perceived effectiveness” variables account for more than 50 % of the criterion variance and therefore these are the most influential factors. Road pricing schemes can be an effective transport management instrument for a city particularly if they are associated with direct investment in public transport and public infrastructure. Thus, personal benefits can be perceived more easily and direct effects can be expected.     

桥梁耐久性发展的历史与现状

回顾了近代桥梁在病害及事理的斗争中不断发展的历史，讨论了当前国外桥梁的耐久性问题，并对提高我国桥梁的耐久性所应进行的工作提出了若干建议。     

Preview-Based Control of Suspension Systems for Commercial Vehicles

An active suspension with preview is developed for the rear axle of a commercial vehicle. The obtained improvements are promising and justify further investigation of the more feasible semi-active suspensions with preview. The inherent non-linearity of semi-active suspensions with switching shock absorbers and the need for controllers that can handle a broad class of control objectives has led to the development of several numerical control methods for both multi-level and continuously variable shock absorbers. The most promising control method and shock absorber type are selected and mounted in a test vehicle. Some first experimental results are discussed.     

Optimization for Vehicle Suspension II: Frequency Domain

The objective of this study is optimizing the components design of a vehicle suspension system under excitation due to road roughness. The vehicle is modelled as a dynamic system made of masses interconnected by, linear, springs and dampers. The optimizing code provides values corresponding to the caracteristics of masses, dampers and springs which, within a range, minimize the objective function for a defined excitation. This objective function auantifies the vehicle comfort level.

The optimization method used is the sequential linear programming by iteratively applying the Simplex algorithm. The model response is obtained in frequency domain and the vehicle excitation can be either random or deterministic.

The exact nature of the optimization problem, objective function and restrictions, depend on the type of excitation considered.

In succeeding paragraphs, the problem formulation together with a comparison with other authors is presented.     

Active Control of Non-stationary Response of Vehicles with Nonlinear Suspensions

Active control of non-stationary response of a single degree of freedom vehicle model with nonlinear passive suspension elements is considered in this paper. The method of equivalent linearization is used to derive the equivalent linear model and the optimal control laws are obtained by using stochastic optimal control theory based on full state information. Velocity squared quadratic damping and hysteresis type of stiffness nonlinearities are considered. The effect of the nonlinearities on the active system performance is studied. The performance of active suspensions with nonlinear passive elements is found to be superior to the corresponding passive suspension systems.     

Automated detection of lane-blocking freeway incidents using artificial neural networks

A major source of urban freeway delay in the U.S. is non-recurring congestion caused by incidents. The automated detection of incidents is an important function of a freeway traffic management center. A number of incident detection algorithms, using inductive loop data as input, have been developed over the past several decades, and a few of them are being deployed at urban freeway systems in major cities. These algorithms have shown varying degrees of success in their detection performance. In this paper, we present a new incident detection technique based on artificial neural networks (ANNs). Three types of neural network models, namely the multi-layer feedforward (MLF), the self-organizing feature map (SOFM) and adaptive resonance theory 2 (ART2), were developed to classify traffic surveillance data obtained from loop detectors, with the objective of using the classified output to detect lane-blocking freeway incidents. The models were developed with simulation data from a study site and tested with both simulation and field data at the same site. The MLF was found to have the highest potential, among the three ANNs, to achieve a better incident detection performance. The MLF was also tested with limited field data collected from three other freeway locations to explore its transferability. Our results and analyzes with data from the study site as well as the three test sites have shown that the MLF consistently detected most of the lane-blocking incidents and typically gave a false alarm rate lower than the California, McMaster and Minnesota algorithms currently in use.