我国汽车行业电子商务发展模式研究

文章针对目前国内汽车电子商务模式的几点争论，结合中国电子商务的现实环境和汽车行业的实际情况。进行了充分论证。并借鉴国外汽车行业电子商务发展模式．提出了适台鼗国汽车行业电子商务的三阶段发展模式。     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.     

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.     

基于Prover的联锁软件形式化验证过程研究

计算机联锁系统是铁路信号控制系统的核心设备,是有着苛刻安全要求的复杂控制系统。本文采用Prover形式化开发工具对联锁软件安全需求进行形式化验证。通过模型检验的形式化验证方法,遍历系统输入变量的所有状态空间.验证联锁特定应用满足系统安全需求,确保系统的安全性得以正确实现。在保证系统安全性的基础上,以全状态空间查找反例的检验方法进一步提升产品的质量。     

Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide.     

Multi-criteria optimization of traffic signals: Mobility,safety, and environment

Two-dimensional multi-objective optimizations have been used for decades for the problems in traffic engineering although only few times so far in the optimization of signal timings. While the other engineering and science disciplines have utilized visualization of 3-dimensional Pareto fronts in the optimization studies, we have not seen many of those concepts applied to traffic signal optimization problems. To bridge the gap in the existing knowledge this study presents a methodology where 3-dimensional Pareto Fronts of signal timings, which are expressed through mobility, (surrogate) safety, and environmental factors, are optimized by use of an evolutionary algorithm. The study uses a segment of 5 signalized intersections in West Valley City, Utah, to test signal timings which provide a balance between mobility, safety and environment. In addition, a set of previous developed signal timing scenarios, including some of the Connected Vehicle technologies such as GLOSA, were conducted to evaluate the quality of the 3-dimensional Pareto front solutions. The results show success of 3-dimensinal Pareto fronts moving towards optimality. The resulting signal timing plans do not show large differences between themselves but all improve on the signal timings from the field, significantly. The commonly used optimization of standard single-objective functions shows robust solutions. The new set of Connected Vehicle technologies also shows promising benefits, especially in the area of reducing inter-vehicular friction. The resulting timing plans from two optimization sets (constrained and unconstrained) show that environmental and safe signal timings coincide but somewhat contradict mobility. Further research is needed to apply similar concepts on a variety of networks and traffic conditions before generalizing findings.     

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.     

A traffic-condition-based route guidance strategy for a single destination road network

Most of existing route guidance strategies achieves user optimal equilibrium by comparing travel time. Measuring travel time, however, might be uneasy on an urban road network. To contend with the issue, the paper mainly considers easily obtained inflow and outflow of a link and road capacity as input, and proposes a route guidance strategy for a single destination road network based on the determination of free-flow or congested conditions on alternative routes. An extended strategy for a complex network and a feedback approximation for avoiding forecast are further explored. Weaknesses of the strategy are also explicitly analyzed. To test the strategy, simulation investigations are conducted on two networks with multiple parallel routes. The results indicate that the strategy is able to provide stable splitting rates and to approximate user optimal equilibrium in different conditions, in particular when traffic demand is high. This strategy has potential to be applied in an urban road network due to its simplicity and easily obtained input data. The strategy is also applicable for single destination if some alternatives and similar routes are available.     

Optimal placement of omnidirectional sensors in a transportation network for effective emergency response and crash characterization

Rapid motor vehicle crash detection and characterization is possible through the use of Intelligent Transportation Systems (ITS) and sensors are an integral part of any ITS system. The major focus of this paper is on developing optimal placement of accident detecting omnidirectional sensors to maximize incident detection capabilities and provide ample opportunities for data fusion and crash characterization. Both omnidirectional sensors (placed in suitable infrastructure locations) and mobile sensors are part of our analysis. The surrogates used are acoustic sensors (omnidirectional) and Advanced Automated Crash Notification (AACN) sensors (mobile). This data fusion rich placement is achieved through a hybrid optimization model comprising of an explicit–implicit coverage model followed by an evaluation and local search optimization using simulation. The compound explicit–implicit model delivers good initial solutions and improves the detection and data fusion capabilities compared to the explicit model alone. The results of the studies conducted quantify the use of a data fusion capable environment in crash detection scenarios, and the simulation tool developed helps a decision maker evaluate sensor placement strategy.     

六五式铁路军用桥墩模拟拼装系统研制与开发

为了满足六五式铁路军用桥墩拼装演练的要求,介绍了“六五式铁路军用桥墩模拟拼装系统”的研制与开发工作。该系统不仅可以解决实际拼装作业的标准化和规范化问题,探索出安全、经济、高效、规范的拼装技术作业程序;而且可以降低拼装演练的费用,提高拼装作业人员的拼装技术水平,减小拼装时间,提高拼装效率。对培训专业保障队伍和保障战时铁路运输的畅通,具有一定的作用。