广东省道路货运业与经济发展相关性分析

本文主要研究了广东省道路货运业与国民经济发展的联系,进行相关性分析。在总结、梳理广东省道路货运业与国民经济发展现状的基础上,选取能够代表道路货运业发展的相关经济指标(道路货运量、道路货运周转量),对数据进行整理分析,并计算其与国民经济相关指标(GDP、第二产业增加值、第三产业增加值)的相关系数,结果显示道路货运业与第三产业增加值的相关程度更高,并对相关的指标进行一元线性回归分析,得出广东省道路货运业基础设施完善,运输供给充足,同时广东省道路货运服务水平与宏观的发展具有较高的相关性,对经济发展具有促进作用。     

长春市冬季公共汽车主干路典型行驶工况研究

文章以长春市的城市规划、不同道路特征、不同路段的交通流特性等因素为依据,选取具有代表性典型路段,即主干线306路为调查样本进行取样试验;依据严寒及寒冷地区分类的国家标准,确定冬季试验时间为2013年1月;通过公共汽车的行驶条件确定试验方法为平均车流法;所用试验车辆为中国第一汽车集团公司所产的解放牌CA6120URH2型公共汽车。试验将采集到的数据根据不同行驶状态划分为若干行程片段,并分别计算出每个片段的对应特征值,进而对所有数据片段进行了主成分分析和聚类分析,在相关性及有效性验证之后通过数据拟合构建成主干路典型行驶工况。     

基于时空图神经网络的交通拥堵预测技术

随着全球定位和物联网技术的快速发展,道路上各种传感器采集的路网数据规模不断扩大。交管部门亟须针对已有的路网数据预测车辆未来的位置和区域分布,对道路前方可能发生的交通拥堵进行预警,并帮助驾驶员选择合适路线,从而缓解城市拥堵。文章采用时空图神经网络(STGNN)挖掘交通流量数据的潜在因果关系,对交通路网嵌入空间依赖和时间依赖进行建模分析。实验结果表明,该方案能更有效地预测未来的交通流量,防止发生拥堵。     

货运车型标准化专项治理管理系统设计与实现

货运车型标准化是国家运输行业结构调整及货运行业提质增效发展的重要工作手段与目标。从货运车型标准化转型治理工作的功能需求出发,以正在开展的常压液体危险货物罐车治理工作为基础,本文设计并实现了基于SSM架构的货运车型标准化专项治理管理系统。危险货物道路运输企业在系统中申报罐车信息,罐车检验机构基于车辆识别代码上传罐检报告,道路运输管理机构通过对罐车信息及关键报告进行审核,给予审核结果及意见。     

浅析无锡中小物流企业联盟发展

我国的物流企业,大多由传统货运企业转型而来,而且99%的物流企业为中小物流企业。无锡物流企业依然存在规模小、设备差、服务水平不高的现象,截至2013年底,无锡道路货运经营业户18326家,其中户均车辆数100辆以上的道路货运企业139家,仅占0.76%,道路运输货运车辆73975辆,户均车辆约4辆,货运市场竞争激励,大多数货运企业还着眼于运输价格的竞争,货运行业利润微薄。     

意大利科学家开发新技术实现车辆间“相互交流”

日前，意大利科学家开发出的一套系统，能够实现车辆间相互“交流”。这套由意大利博洛尼亚大学科学家开发的智能交通系统，可使一个路段上所有车辆间随时保持联系，一旦发生事故或影响交通的状况即可提前预警。研究人员称，该系统有望将车辆碰撞事故减少40％。     

基于车载测试的CNG汽车微观排放特性研究

为了分析CNG汽车道路排放的微观特性,采用车载排放测试系统,并选取市区主要道路为试验路段进行了实车道路试验。通过试验获取典型车辆的排放数据及行驶状态,分析车辆在实际行驶中的排放特性,为预测不同交通状态下CNG汽车的排放特性和区域排放清单建立提供参考。     

货车地标推力城市配送——货运汽车标准解读及城市配送车辆推介会在京召开

5月23日,以"绿色物流、畅行北京"为标志的城市配送车辆推介会,在北京召开。来自全国各地的货运车辆制造厂商及道路货运企业参加了此次以"人文交通、科技交通、绿色交通"为主题的盛会。北京市地方标准《城市中心区货运汽车营运技术要求》(DB11/T761-2010)(以下简称:《标准》)于2011年4月1日正式实施。为推动该《标准》的宣贯实施,推进城市中心区在用货运车辆和新增货运车辆的达标进程,为道路货运和物流企业与汽车制造厂商搭建沟通交流平台,在北京市交通委员会运输管理局指导下,北京市道路运输协会主办、北京博瑞启亚企业管理咨询有限公司承办了此次大会。     

道路货运安全现代化管理路径探索

随着交通运输现代化的推进和人民群众对“零死亡”愿景的期盼，道路货运安全问题倍受关注。如何破解道路货运车辆事故占比高、危害大等行业难题，降低负外部性对社会经济的负面效应，是统筹发展与安全需要关注的重要环节。通过梳理道路货运行业发展现状和存在问题，从企业组织、运输装备和人员素质三个方面，对道路货运安全隐患进行溯源分析，据此提出道路货运安全水平提升的管理路径，为相关部门构建全面系统的现代化安全管理体系提供参考借鉴。     

高原地区公路运行速度模型研究

文章基于对青藏公路车辆运行速度、车辆组成的调查,采用层次分析法对不同车辆组成、不同路段速度进行分析,建立了不同车辆组成下的运行速度模型,并结合交通事故数据,提出了确保交通安全的常年冻土区公路运行速度值。该运行速度模型的应用研究,为减少道路交通事故提供了一种新思路。     

A car-following model considering asymmetric driving behavior based on long short-term memory neural networks

Asymmetric driving behavior is a critical characteristic of human driving behaviors and has a significant impact on traffic flow. In consideration of the asymmetric driving behavior, this paper proposes a long short-term memory (LSTM) neural networks (NN) based car-following (CF) model to capture realistic traffic flow characteristics by incorporating the driving memory. The NGSIM data are used to calibrate and validate the proposed CF model. Meanwhile, three characteristics closely related to the asymmetric driving behavior are investigated: hysteresis, discrete driving, and intensity difference. The simulation results show the good performance of the proposed CF model on reproducing realistic traffic flow features. Moreover, to further demonstrate the superiority of the proposed CF model, two other CF models including recurrent neural network based CF model and asymmetric full velocity difference model, are compared with LSTM-NN model. The results reveal that LSTM-NN model can capture the asymmetric driving behavior well and outperforms other models.     

Emission evaluation of inter-vehicle safety warning information systems

Driver inattentiveness is one of critical factors contributing to vehicle crashes. The inter-vehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards using connected vehicle environments. A novel feature of the proposed ISWS is its ability to detect hazardous driving events, such as abrupt accelerations and lane changes, which are defined as moving hazards with a higher potential of causing crashes. This study evaluated the effectiveness of the ISWS in reducing vehicle emissions and its potential for traffic congestion mitigation. This study included a field experiment that documented actual vehicle maneuvering patterns for abrupt accelerations and lane changes, which were used for more realistic simulation evaluations, in addition to normal accelerations and lane changes. Probe vehicles equipped with customized on-board units consisting of a global positioning system (GPS) device, accelerometer, and gyro sensor were used to obtain the vehicle maneuvering data. A microscopic simulator, VISSIM, was used to simulate a driver’s responsive behavior when warning messages were delivered. A motor vehicle emission simulator (MOVES) was then used to estimate vehicle emissions. The results show that reduction in vehicle emissions increased when the ISWS’s market penetration rate (MPR) and the congestion level of the traffic conditions increased. The maximum CO and CO₂ emission reductions achieved were approximately 6% and 7%, respectively, under LOS D traffic conditions. The outcomes of this study can be valuable for deriving smarter operational strategies for ISWS to account for environmental impacts.     

The measurement of vehicular driving cycle within the city of Edinburgh

In this paper, the development of a driving cycle for the urban area of the city of Edinburgh is presented. The driving cycle was obtained from recorded data in actual traffic conditions, using the car chase technique. A new statistical method of analysing the recorded data was developed. The proposed TRAffic Flow IndeX (TRAFIX) enables the calculation of a representative driving cycle from the various measurements undertaken during two stages of experiments. Data from the City of Edinburgh Council traffic monitoring stations were weighted in proportion to traffic flows on the constituent driving routes. A comparison between the European ECE cycle and the presently proposed Edinburgh driving cycle (EDC) has also been made.     

A data perception model for the safe operation of high-speed rail in rainstorms

In order to solve the safety operation problems of High-speed rail (HSR) in different areas and different sections under the rainstorm condition, an early warning process for the rainstorm disaster is designed. Furthermore, in order to control the operation risk, a HSR operation program with different rainstorm degrees is given out based on the analysis of rainstorm warning mechanism and rainstorm warning threshold in this paper. In addition, considering the reality that natural conditions vary greatly and the rainfall is very uneven, a data perception model of rainstorm (DPM) is proposed with correction coefficients for solving the calculation problem of precipitation for rainstorm warning. The DPM mainly adopts Paulhus’s empirical equation and uses the linear function to improve it for calculating the precipitation, which is able to calculate the hourly precipitation in different regional environments, and also effectively evaluate the rainstorm warning level of high-speed rail in this period. It can calculate and monitor the process by big data and MATLAB. The result of case analysis shows that the DPM has good practical value for solving the safety operation problem of HSR in different areas under rainstorm environment.     

Observing freeway ramp merging phenomena in congested traffic

This work conducts a comprehensive investigation of traffic behavior and characteristics during freeway ramp merging under congested traffic conditions. On the Tokyo Metropolitan Expressway, traffic congestion frequently occurs at merging bottleneck sections, especially during heavy traffic demand. The Tokyo Metropolitan Expressway public corporation, generally applies different empirical strategies to increase the flow rate and decrease the accident rate at the merging sections. However, these strategies do not rely either on any behavioral characteristics of the merging traffic or on the geometric design of the merging segments. There have been only a few research publications concerned with traffic behavior and characteristics in these situations. Therefore, a three‐year study is undertaken to investigate traffic behavior and characteristics during the merging process under congested situations. Extensive traffic data capturing a wide range of traffic and geometric information were collected using detectors, videotaping, and surveys at eight interchanges in Tokyo Metropolitan Expressway. Maximum discharged flow rate from the head of the queue at merging sections in conjunction with traffic and geometric characteristics were analyzed. In addition, lane changing maneuver with respect to the freeway and ramp traffic behaviors were examined. It is believed that this study provides a thorough understanding of the freeway ramp merging dynamics. In addition, it forms a comprehensive database for the development and implementation of congestion management techniques at merging sections utilizing Intelligent Transportation System.     

Adaptive cruise control design for active congestion avoidance

We present an adaptive cruise control (ACC) strategy where the acceleration characteristics, that is, the driving style automatically adapts to different traffic situations. The three components of the concept are the ACC itself, implemented in the form of a car-following model, an algorithm for the automatic real-time detection of the traffic situation based on local information, and a strategy matrix to adapt the driving characteristics (that is, the parameters of the ACC controller) to the traffic conditions. Optionally, inter-vehicle and infrastructure-to-car communication can be used to improve the accuracy of determining the traffic states. Within a microscopic simulation framework, we have simulated the complete concept on a road section with an on-ramp bottleneck, using empirical loop-detector data for an afternoon rush-hour as input for the upstream boundary. We found that the ACC vehicles improve the traffic stability and the dynamic road capacity. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were already significantly reduced for much lower penetration rates. The efficiency of the proposed driving strategy even for low market penetrations is a promising result for a successful application in future driver assistance systems.     

Study on the framework of hybrid collision warning system using loop detectors and vehicle information

Safety warning systems generally operate based on information from sensors attached to individual vehicles. Various types of data used for collision risk calculation can be categorized into two types, microscopic or macroscopic, depending on how the sensors collect the information of traffic state. Most collision warning systems use only either of these types of data, but they all have limitations imposed by the data, such as requirement of high installation cost and high market penetration rate of devices. In order to overcome these limits, we propose a collision warning system that utilizes the integrated information of macroscopic data and microscopic data, from loop detectors and smartphones respectively. The proposed system is evaluated by simulating a real vehicle trip based on the NGSIM data. We compare the results against collision warning systems based on macroscopic data from infrastructure and microscopic data from Vehicle-to-Vehicle information. The analysis of three systems shows two findings that (a) ICWS (Infrastructure-based Collision Warning System) is inadequate for immediate collision warning system and (b) VCWS (V2V communication based Collision Warning System) and HCWS (Hybrid Collision Warning System) produce collision warning at very similar timing, even with different behavior of individual drivers. Advantages of HCWS are that it can be directly applied to existing system with small additional cost, because data of loop detector are already available to be used in Korea and smartphones are widely spread. Also, the computation power distributed to each individual smartphone greatly increases the efficiency of the system by distributing the computation resources and load.     

Development of a practical driving cycle construction methodology: A case study in Hong Kong

A practical methodology for constructing a representative driving cycle reflecting the real-world driving conditions is developed for vehicle emissions testing and estimation. The methodology tackles three major tasks, i.e., data collection, route selection and cycle construction. Both car chasing and on-board measurement techniques were employed to collect vehicle speed data. Route selection was based on the records of average annual daily traffic of the road network between major residential areas and commercial/industrial areas. A variety of parameters were employed as the target statistics characterising the driving pattern in the construction of driving cycles. The performance value and speed-acceleration probability distribution were utilised to determine the best synthesised driving cycle. The method is easy to follow and the driving cycles are comparative to other renounced cycles.     

Factors affecting public transportation usage rate: Geographically weighted regression

As the number of private vehicles grows worldwide, so does air pollution and traffic congestion, which typically constrain economic development. To achieve transportation sustainability and continued economic development, the dependency on private vehicles must be decreased by increasing public transportation usage. However, without knowing the key factors that affect public transportation usage, developing strategies that effectively improve public transportation usage is impossible. Therefore, this study respectively applies global and local regression models to identify the key factors of usage rates for 348 regions (township or districts) in Taiwan. The global regression model, the Tobit regression model (TRM), is used to estimate one set of parameters that are associated with explanatory variables and explain regional differences in usage rates, while the local regression model, geographically weighted regression (GWR), estimates parameters differently depending on spatial correlations among neighbouring regions. By referencing related studies, 32 potential explanatory variables in four categories, social-economic, land use, public transportation, and private transportation, are chosen. Model performance is compared in terms of mean absolute percentage error (MAPE) and spatial autocorrelation coefficient (Moran’ I). Estimation results show that the GWR model has better prediction accuracy and better accommodation of spatial autocorrelation. Seven variables are significantly tested, and most have parameters that differ across regions in Taiwan. Based on these findings, strategies are proposed that improve public transportation usage.     

关于设置上海越江隧道统一标志的探讨

上海越江隧道工程建设已经具有一定的数量规模和相当的技术水平,具备了设置统一标志的前提条件。统一标志的设置有助于提高越江隧道的导向性、指引性及行车安全性。文章介绍了设置越江隧道标志的必要性与可行性,并提出了几种隧道标志的设计方案,以供参考。