Pan-electronic Vehicle System

提出了全电子汽车系统的汽车车身电气系统设计方案,它以骨干网和局域网两级网络为数字信号网络、以电源网络提供电源并以中央协调器进行整车的协调控制.通过骨干网/局域网实现电器互联,并以分布式电源网实现整车弱电和强电的供电,以标准化电器接口实现了整车线束的简化,从而构建了一个智能型、标准化、一致性强、扩展性好、可靠性高的电器系统.最后开发了实验样车,验证了系统的可行性.     

New lead-acid battery management system based on generator regulation

A novel regulation system for a vehicle generator and lead-acid battery is proposed in this paper. By integrating the regulation method, the output voltage of the generator is determined and controlled by the algorithm to save electrical energy and protect the lead-acid battery. The regulation algorithm is implemented in Matlab/Simulink, and the logic function of the system is verified using the dSPACE/AutoBox workbench. The experimental results show that the new algorithm improves the performance of the fuel economy of the vehicle and the battery state-of-health compared to the traditional control method.     

Development of knowledge based body structure concept design model

The purpose of this study is to propose a concept design process for an automotive body structure using technical information on the major joints and members of vehicles. First, in order to collect the technical information on major joints and members, 17 vehicles were selected using benchmark data. The collected technical information for the selected vehicles was the cross sectional shapes of each joint and member which were used for the analysis of joint stiffness, crashworthiness and static stiffness of the member to make a database along with cross section properties. This study applied a ‘What If Study’ technique to perform a concept design of an automotive body using the analyzed information and selected cross section meeting the design objectives. The criteria for the selection of the cross section were defined by subdividing the defined design objectives of an automotive body structure and constraints into members and joints. In order to configure an analysis model of an automotive body structure using the selected cross section, a shape parametric model was used and static stiffness, dynamic stiffness and crashworthiness were assessed to evaluate the configured automotive body structure. The evaluation result showed that the crashworthiness and static/dynamic stiffness were improved compared to an existing body structure. In addition, the weight of the body structure was reduced. Through this study, the process that can rapidly and effectively derive and evaluate the concept design of an automotive body structure was defined. It is expected that, henceforth, this process will be helpful for the study of automotive body structures.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Analysis of cost estimation disclosure in environmental impact statements for surface transportation projects

Reliability in cost estimates in publicly funded projects is more important today than ever with increased governmental funding to infrastructure projects and associated accountability requirements, but surface transportation projects, large and small, in the United States have a legacy of cost overruns. The problems with these overruns start with the cost estimation process before projects begin. Studies have shown that early cost estimations reflect best-case scenarios rather than realistic expectations, and have attributed technical, economic, psychological, and political reasons for underestimation. The primary objectives of this research were to determine how costs have been presented and updated in environmental impact statements, to identify endemic technical problems with cost estimation during the environmental review of surface transportation projects, and to develop recommendations for improving cost estimation and disclosure. Cost estimation methods were analyzed from the documents of 100 projects, including draft environmental impact statements, final environmental impact statements, and records of decision. The study concluded that the lack of guidance on how to include cost estimation in environmental review revealed itself in the level of detail and attention given to estimating costs. Agencies omitted or included various aspects of cost estimation randomly. Professional organizations should fill the gap of the need for specific guidance to cost estimation for environmental review so it can evolve as a state of the practice.     

Modeling adoption timing of autonomous vehicles: innovation diffusion approach

Autonomous vehicles (AVs) are expected to act as an economically-disruptive transportation technology offering several benefits to the society and causing significant changes in travel behavior and network performance. However, one of the critical issues that policymakers are facing is the absence of a sound estimation of their market penetration. This study is an effort to quantify the effect of different drivers on the adoption timing of AVs. To this end, we develop an innovation diffusion model in which individuals’ propensities to adopt a new technology such as AVs takes influence from a desire to innovate and a need to imitate the rest of the society. It also captures various sources of inter-personal heterogeneity. We found that conditional on our assumptions regarding the changes in market price of AVs over time, their market penetration in our study region (Chicago metropolitan area) will eventually reach 71.3%. Further, model estimation results show that a wide range of socio-demographic factors, travel pattern indicators, technology awareness, and perceptions of AVs are influential in people’s AV adoption timing decision. For instance, frequent long-distance travelers are found to make the adoption decision more innovatively while those who have experienced an accident in their lifetime are found to be more influenced by word of mouth.     

搞好新建公路绿化 恢复自然生态平衡

结合哈同公路佳哈段的绿化谈公路绿化美化的作用和方法 ,总结经验并指出了不足 ,可供有关人员参考。     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.     

Lightweight mixture faults detection method for gasoline engine using on-line trend analysis

Mixture faults detection is meaningful for gasoline engines because proper mixture is the basic prerequisite for healthy running of a combustion engine. Among existing methods for faults detection, the data-driven trend analysis technique is widely used due to the simplicity and efficiency in time-domain. The CUSUM (Cumulative Sum Of Errors) algorithm is good at real-time trend extraction, but it’s easy to be costly on the fuel trim signal during the engine in normal working conditions, which will increase battery energy consumption because engine failure is rarely occurs. Hence, the conventional treatment methods of artifacts in the CUSUM algorithm are modified by means of decay function and detection time analysis. The thresholds are tuned according to the characteristics of artifacts instead of residual variability, which leads to better results of trend extraction and less computation. Then, the revised CUSUM algorithm is used for monitoring the mixture abnormal behaviors, and the mixture faults can be detected in real time through analyzing the variation features of fuel trim signal. The lightweight faults detector using the advanced CUSUM algorithm (FD-A-CUSUM) is evaluated on the experimental data collected from a Ford engine. The validation results show that while engine works under normal conditions, the computation of FD-A-CUSUM has decreased by 72.79 % in comparison with the detection method using the original CUSUM algorithm (FD-O-CUSUM), and the false alarm ratio of FD-A-CUSUM is 3.37 %. Futhermore, the detection results of FD-A-CUSUM for two leakage faults have achieved 91.18 % test accuracy.