一种基于垂直字符边界特征的车牌定位方法

提出了一种基于垂直字符边界点特征的车牌定位方法，该方法能有效定位车牌，定位精度高达９８％，定位时间不超过２ｓ，并能有效地克服光线和天气条件等影响。     

键合图理论在汽车振动分析中的应用

本文应用键合图理论建立了汽车5自由度振动系统的键图模型并推导出状态方程。编制了动态仿真程序,计算了国产某轻型越野车和某轻型货车驶过三角形单个凸起时的振动响应,分析了悬架参数对振动的影响,指出了提高该车平顺性的途径。进行了轻型货车实车试验并将试验结果与计算结果做了对照,证明所选模型和所编程序是正确的和实用的。     

温度和麻醉对神经几种兴奋性指标的影响——兼论何者可以正确反映兴奋性

在蟾蜍坐骨神经-腓神经观察了温度和麻醉对几种兴奋性指标的影响。结果表明,标准电量(a)随兴奋性的变化而有规律地变化。兴奋性愈高。a值愈小。而Weiss式中的b、基强度(Rh)、时值(Chr)及强度—时间曲线均不能正确反映兴奋性。细胞膜时间常数(RC)与兴奋性的变化无规律性联系。结论,a是兴奋性的可靠定量指标。     

街道设计理念下工程实践的若干思考

“完整街道”、“街道设计”等城市道路改造设计理念开始广泛应用于城市道路旧改等实际工程项目。然而，街道设计理念与传统的设计习惯、道路管理模式及使用者的接受程度，依然在现实应用以及工程实施上存在较大的分歧。以深圳市罗湖区道路设施品质提升工程和深圳市罗湖区精品示范路工程两个项目为工程背景，分别从宏观的街道空间改造和部分微观细节设计两个角度，分析项目实施过程中存在的难点和优化处置方案，为后续工程实践以及相关街道设计导则优化提供借鉴。     

Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design,demonstration and validation

Estimation/updating of Origin–Destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in on-line contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks – except from closed highway systems – thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under “standardized” conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources.     

Optimizing the locations of electric taxi charging stations: A spatial–temporal demand coverage approach

Vehicle electrification is a promising approach towards attaining green transportation. However, the absence of charging stations limits the penetration of electric vehicles. Current approaches for optimizing the locations of charging stations suffer from challenges associated with spatial–temporal dynamic travel demands and the lengthy period required for the charging process. The present article uses the electric taxi (ET) as an example to develop a spatial–temporal demand coverage approach for optimizing the placement of ET charging stations in the space–time context. To this end, public taxi demands with spatial and temporal attributes are extracted from massive taxi GPS data. The cyclical interactions between taxi demands, ETs, and charging stations are modeled with a spatial–temporal path tool. A location model is developed to maximize the level of ET service on the road network and the level of charging service at the stations under spatial and temporal constraints such as the ET range, the charging time, and the capacity of charging stations. The reduced carbon emission generated by used ETs with located charging stations is also evaluated. An experiment conducted in Shenzhen, China demonstrates that the proposed approach not only exhibits good performance in determining ET charging station locations by considering temporal attributes, but also achieves a high quality trade-off between the levels of ET service and charging service. The proposed approach and obtained results help the decision-making of urban ET charging station siting.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Exchange rate and transport cost sensitivities of bilateral freight flows between the US and China

This paper explores the long-run impacts of gross domestic product, exchange rate, and transport costs on bilateral air and ocean freight flows between the US and China. The study employs a cointegration framework by using export and import data over the period of 2003:Q1-2014:Q2. Results show that gross domestic product is the key determinant of bilateral freight flows, indicating that real income of a trading partner is a driving force of the bilateral freight flows between the US and China. In examining the sensitivities of the bilateral trade flows, air freight flows are found to be more responsive to a real income change than ocean freight flows. The bilateral exchange rate is a significant factor affecting the freight flows from China to the US, suggesting that a US dollar appreciation against the Chinese yuan increases the inflows of Chinese commodities to the US. The impacts of the bilateral exchange rate and transport cost are found to vary at industry and commodity levels. These findings support the importance of employing disaggregate data in the bilateral freight flow analysis.     

Estimating travel time functions for urban roads: options and issues

Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified.

In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions.