汽车侧翻和滚翻事故建模研究

分析汽车在侧翻和滚翻过程中的受力状态和轮胎或车身与路面的相互作用方式,建立汽车侧翻和滚翻的运动学和动力学模型,揭示汽车临界侧翻碰撞力与持续作用时间等参数的关系,推导侧翻车辆侧向速度的范围,确定滚筒模型中关键参数的选取方法。事故案例表明模型在实际应用中效果良好、定量准确、直观性强。     

汽车ABS轮速传感器及其信号处理

研究了汽车防抱死制动系统变磁阻式磁电轮速传感器及其信号特性。在此基础上提出了轮速传感器信号处理电路的要求,并设计出了由低通滤波器和迟滞比较器构成的信号处理电路。在Matlab/Simulink环境下对电路进行了仿真研究和实验研究。结果表明,设计的轮速信号处理电路工作稳定、可靠,抗干扰能力强,能满足ABS系统的要求。     

半开放式差速器的技术优势及实践应用探讨

差速器提供了自由的转速差满足车辆的行驶需要,然而却在特殊路况下导致了车轮空转车辆停滞.差速锁介入消除了转速差,解决了这一特殊情况的同时却带来了其他问题.差速器不限制的转速差超出使用要求,差速锁直接砍掉全部转速差.差速器与差速锁,本身就是矛盾对立的二者,汽车总是在二者之间艰难的取舍.其实我们并不需要差速锁,只需差速器保留...     

汽车高压线束中高压端子的压接性能分析

高压线束是新能源汽车动力和信号传输分配系统的重要载体,高压线束端子的压接性能是新能源汽车最重要的性能指标。论文针对新能源汽车高压线束端子压接性能建立数据分析模型,通过分析相关数据,找出高压线束端子压缩比的最佳适配范围,以提高高压线束冷压接的工艺能力和质量水平。     

钢纤维掺量及规格对桥梁用超高性能混凝土性能影响的研究

为了探究钢纤维掺量及规格对桥梁用超高性能混凝土施工性能和力学性能的影响,通过设置不同钢纤维掺量(0％、0.5％、1％、1.5％、2％、2.5％、3％、3.5％、4％)和长径比(65、80、90、100)进行对照试验,分别得到试件的扩展度、抗压强度、抗折强度.试验结果表明:当钢纤维长径比为65时,随着掺量的增加,超高性能...     

Categorizing bicycling environments using GPS-based public bicycle speed data

A promising alternative transportation mode to address growing transportation and environmental issues is bicycle transportation, which is human-powered and emission-free. To increase the use of bicycles, it is fundamental to provide bicycle-friendly environments. The scientific assessment of a bicyclist’s perception of roadway environment, safety and comfort is of great interest. This study developed a methodology for categorizing bicycling environments defined by the bicyclist’s perceived level of safety and comfort. Second-by-second bicycle speed data were collected using global positioning systems (GPS) on public bicycles. A set of features representing the level of bicycling environments was extracted from the GPS-based bicycle speed and acceleration data. These data were used as inputs for the proposed categorization algorithm. A support vector machine (SVM), which is a well-known heuristic classifier, was adopted in this study. A promising rate of 81.6% for correct classification demonstrated the technical feasibility of the proposed algorithm. In addition, a framework for bicycle traffic monitoring based on data and outcomes derived from this study was discussed, which is a novel feature for traffic surveillance and monitoring.     

Theory of safety surrogates using vehicle trajectories in macroscopic and microscopic settings: Application to dynamic message signs controlled traffic at work zones

This paper presents a new mathematical framework for obtaining quantitative safety measure using macroscopic as well as microscopic traffic data. The safety surrogate obtained from the macroscopic data is in terms of analysis performed on vehicle trajectories obtained from the macroscopic data. This method of obtaining safety measure can be used for many different types of applications. The safety surrogate for the traffic dynamics are developed in terms of a new concept of Negative Speed Differentials (NSD) that involve a convolution of vehicle speed function obtained from vehicle trajectories and then performing the integration of the square of the output for its negative values. The framework is applicable to microscopic traffic dynamics as well where we can use car following models for microscopic dynamics or the LWR model for macroscopic dynamics. This paper then presents the use of this new safety surrogate on the development of a feedback control law for controlling traffic in work zones using Dynamic Message Signs. A hybrid dynamics model is used to represent the switching dynamics due to changing DMS messages. A feedback control design for choosing those messages is presented as well as a simple simulation example to show its application.     

Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters

Eco-driving is an energy efficient traffic operation measure that may lead to important energy savings in high speed railway lines. When a delay arises in real time, it is necessary to recalculate an optimal driving that must be energy efficient and computationally efficient.In addition, it is important that the algorithm includes the existing uncertainty associated with the manual execution of the driving parameters and with the possible future traffic disturbances that could lead to new delays.This paper proposes a new algorithm to be executed in real time, which models the uncertainty in manual driving by means of fuzzy numbers. It is a multi-objective optimization algorithm that includes the classical objectives in literature, running time and energy consumption, and as well a newly defined objective, the risk of delay in arrival. The risk of delay in arrival measure is based on the evolution of the time margin of the train up to destination.The proposed approach is a dynamic algorithm designed to improve the computational time. The optimal Pareto front is continuously tracked during the train travel, and a new set of driving commands is selected and presented to the driver when a delay is detected.The algorithm evaluates the 3 objectives of each solution using a detailed simulator of high speed trains to ensure that solutions are realistic, accurate and applicable by the driver. The use of this algorithm provides energy savings and, in addition, it permits railway operators to balance energy consumption and risk of delays in arrival. This way, the energy performance of the system is improved without degrading the quality of the service.     

Mental models of driving and speed: biases,choices and reality

This paper provides a review of research performed by Svenson with colleagues and others work on mental models and their practical implications. Mental models describe how people perceive and think about the world including covariances and relationships between different variables, such as driving speed and time. Research on mental models has detected the time-saving bias [Svenson, O. (1970). A functional measurement approach to intuitive estimation as exemplified by estimated time savings. Journal of Experimental Psychology, 86, 204–210]. It means that drivers relatively overestimate the time that can be saved by increasing speed from an already high speed, for example, 90–130?km/h, and underestimate the time that can be saved by increasing speed from a low speed, for example, 30–45?km/h. In congruence with this finding, mean speed judgments and perceptions of mean speeds are also biased and higher speeds given too much weight and low speeds too little weight in comparison with objective reality. Replacing or adding a new speedometer in the car showing min per km eliminated or weakened the time-saving bias. Information about braking distances at different speeds did not improve overoptimistic judgments of braking capacity, but information about collision speed with an object suddenly appearing on the road did improve judgments of braking capacity. This is relevant to drivers, politicians and traffic regulators.     

Liner shipping network design with emission control areas: A genetic algorithm-based approach

To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO₂ and SO_x) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.