一车一档系统在客车技术履历管理中的应用

随着客车技术的迅猛发展,原有的卡片式客车技术履历已经不能适应生产的需要,针对这一要求,结合多年的工作实践,利用中文Visual Foxpr06.0技术,编写一车一档这套数据库管理软件,利用电脑来管理客车履历,实现客车技术履历的电子化,本系统也可以将字段名进行改编,在其他系统中使用.     

冲压件品质控制

在整车开发过程中,整车外观品质至关重要,因其决定顾客对整车的第一感官印象,而冲压件品质直接决定整车外观品质,因此对冲压件品质有较高的要求。冲压件品质主要受产品设计和过程工艺设计2个阶段影响,文章主要从产品设计和过程工艺设计2个方面阐述了影响冲压件品质的一些注意事项及控制方法,指出冲压件品质直接影响整车白车身品质,冲压件从设计到量产任何一道工序都不能疏忽。     

Heavy metals and metalloid contamination in Louisiana Lake Pontchartrain Estuary along I-10 Bridge

In this study, HMs concentration in sediments and water from the Lake Pontchartrain estuary along the I-10 Bridge were investigated in two seasons to evaluate the level of contamination and to assess the effect of vehicular traffic. Vehicular traffic has led to HMs such as As, Cd, Cr, Pb, Zn, Ni, and Cu accumulation in sediments along the bridge. The HMs content in water especially in summer increased due to high temperature which led to release of HMs from the sediments. The level of pollution attributed to anthropogenic activities was evaluated using several pollution indicators. The overall HMs bioavailability and EFs was mostly high in summer and the concentration of the HMs in both sediments and water was highly influenced by the season and the distance from the highways. The content of As and Cd in lake sediments were higher than the background values (BGV) for both seasons (spring and summer), and Cr and Pb in sediments were higher than the BGV in most sampling points in the spring. According to Sediments Quality Guidelines (SQGs), heavy metals except for As have low biotoxicity, and As could potentially result in harmful effects on the aquatic organisms. The relationship between As and vehicular traffic is less studied so our finding stress the need for further study on source of As in Lake Pontchartrain sediments.     

Fuel economy testing of autonomous vehicles

Environmental pollution and energy use in the light-duty transportation sector are currently regulated through fuel economy and emissions standards, which typically assess quantity of pollutants emitted and volume of fuel used per distance driven. In the United States, fuel economy testing consists of a vehicle on a treadmill, while a trained driver follows a fixed drive cycle. By design, the current standardized fuel economy testing system neglects differences in how individuals drive their vehicles on the road. As autonomous vehicle (AV) technology is introduced, more aspects of driving are shifted into functions of decisions made by the vehicle, rather than the human driver. Yet the current fuel economy testing procedure does not have a mechanism to evaluate the impacts of AV technology on fuel economy ratings, and subsequent regulations such as Corporate Average Fuel Economy targets. This paper develops a method to incorporate the impacts of AV technology within the bounds of current fuel economy test, and simulates a range of automated following drive cycles to estimate changes in fuel economy. The results show that AV following algorithms designed without considering efficiency can degrade fuel economy by up to 3%, while efficiency-focused control strategies may equal or slightly exceed the existing EPA fuel economy test results, by up to 10%. This suggests the need for a new near-term approach in fuel economy testing to account for connected and autonomous vehicles. As AV technology improves and adoption increases in the future, a further reimagining of drive cycles and testing is required.     

深水AUV安全系统的设计与实现

  目的  为保障高速自主式水下机器人（AUV）的航行安全,研制一套智能应急自救系统。  方法  首先,介绍应急自救系统的组成与功能,对其进行可靠性分析与设计;其次,重点研究多信道信息采集融合机制、主动应急机制、故障优先级整定机制和应急处理决策机制;再次,设计应急专家决策模型,提出一种基于离散规则应急操舵的应急处理方法;最后,基于VxWorks实时操作系统编制应急系统控制软件,并搭建半实物仿真平台进行系统联调仿真试验。  结果  试验结果验证了该应急自救机制与策略的可靠性和可行性。  结论  该应急系统弥补了传统应急手段的不足,对AUV的应急自救具有重要的借鉴作用。     

Vehicle routing with roaming delivery locations

We propose the vehicle routing problem with roaming delivery locations (VRPRDL) to model an innovation in last-mile delivery where a customer’s order is delivered to the trunk of his car. We develop construction and improvement heuristics for the VRPRDL based on two problem-specific techniques: (1) efficiently optimizing the delivery locations for a fixed customer delivery sequence and (2) efficiently switching a predecessor’s or successor’s delivery location during the insertion or deletion of a customer in a route. Furthermore, we conduct an extensive computation study to assess and quantify the benefits of trunk delivery in a variety of settings. The study reveals that a significant reduction in total distance travelled can be achieved, especially when trunk delivery is combined with traditional home delivery, which has both economic and environmental benefits.     

Customized bus service design for jointly optimizing passenger-to-vehicle assignment and vehicle routing

Emerging transportation network services, such as customized buses, hold the promise of expanding overall traveler accessibility in congested metropolitan areas. A number of internet-based customized bus services have been planned and deployed for major origin-destination (OD) pairs to/from inner cities with limited physical road infrastructure. In this research, we aim to develop a joint optimization model for addressing a number of practical challenges for providing flexible public transportation services. First, how to maintain minimum loading rate requirements and increase the number of customers per bus for the bus operators to reach long-term profitability. Second, how to optimize detailed bus routing and timetabling plans to satisfy a wide range of specific user constraints, such as passengers’ pickup and delivery locations with preferred time windows, through flexible decision for matching passengers to bus routes. From a space-time network modeling perspective, this paper develops a multi-commodity network flow-based optimization model to formulate a customized bus service network design problem so as to optimize the utilization of the vehicle capacity while satisfying individual demand requests defined through space-time windows. We further develop a solution algorithm based on the Lagrangian decomposition for the primal problem and a space-time prism based method to reduce the solution search space. Case studies using both the illustrative and real-world large-scale transportation networks are conducted to demonstrate the effectiveness of the proposed algorithm and its sensitivity under different practical operating conditions.     

CO2 emissions correction of light-duty vehicles based on an energy deviation analysis method

In present study, a total of 3 types of light-duty vehicles were tested for 7 types of driving modes by using a vehicle dynamics-based simulation method. Deviations between the target and actual test vehicle speed and inaccurate chassis dynamometer road load settings are selected as the two main factors affecting the CO₂ emission measurement test. 126 cases of simulations were conducted to analyze the effects of the deviation between the target and actual test vehicle speed on CO₂ emissions and 63 cases of simulation were conducted to analyze the effectiveness of inaccurate road load test conditions on CO₂ emissions. Then, the CO₂ correlation method proposed by World Forum for Harmonization of Vehicle Regulations (WP.29, UN) was applied for simulated results in original simulation cases, and a correction to performance was validated by comparative analysis. From the simulation results, it is revealed that velocity and road load deviation are related to distinct changes in fuel efficiency and CO₂ emission rates of test vehicles. Also, it is revealed that CO₂ correction method show good performance to reduce the relative error lower than 2% in all test cases.     

Pedestrian traffic management of boarding and alighting in metro stations

The objective of this work is to determine, by means of simulation and experiments, the effect of pedestrian traffic management in the boarding and alighting time of passengers at metro stations. Studies were made by means of a pedestrian traffic microsimulator (LEGION Studio) and experiments at the Human Dynamic Laboratory (HDL) of Universidad de los Andes in Santiago de Chile, to obtain criteria for the pedestrian traffic management on the platform and doors of metro cars. The methodology consists of building a boarding/alighting hall of a metro car and the relevant portion of the platform in front of the hall. The simulation scenarios included the location of the vertical handrail in the hall of the car, delimitation of a keep out zone in front of the doors and the use of differentiated doors for boarding and alighting. The results of the simulation and laboratory experiments are expressed in Pedestrian Level of Service (LOS), Passenger Service Time (PST), passenger density on the vehicle and platform, and passenger dissatisfaction. Both, the simulation results and laboratory experiments allow us to give some recommendations for the pedestrian traffic management in metro systems.     

Vehicle detection grammars with partial occlusion handling for traffic surveillance

Traffic surveillance is an important topic in intelligent transportation systems (ITS). Robust vehicle detection is one challenging problem for complex traffic surveillance. In this paper, we propose an efficient vehicle detection method by designing vehicle detection grammars and handling partial occlusion. The grammar model is implemented by novel detection grammars, including structure, deformation and pairwise SVM grammars. First, the vehicle is divided into its constitute parts, called semantic parts, which can represent the vehicle effectively. To increase the robustness of part detection, the semantic parts are represented by their detection score maps. The semantic parts are further divided into sub-parts automatically. The two-layer division of the vehicle is modeled into a grammar model. Then, the grammar model is trained by a designed training procedure to get ideal grammar parameters, including appearance models and grammar productions. After that, vehicle detection is executed by a designed detection procedure with respect to the grammar model. Finally, the issue of vehicle occlusion is handled by designing and training specific grammars. The strategy adopted by our method is first to divide the vehicle into the semantic parts and sub-parts, then to train the grammar productions for semantic parts and sub-parts by introducing novel pairwise SVM grammars and finally to detect the vehicle by applying the trained grammars. Experiments in practical urban scenarios are carried out for complex traffic surveillance. It can be shown that our method adapts to partial occlusion and various challenging cases.