“大网”从天降

王某驾驶小轿车行驶在高速路上,由于风速过快,从对向行驶的大货车上突然飞下来一个大篷布,篷布被风涨得鼓鼓的,形成了一张大网,差点罩在了王某高速行驶的车上,所幸有惊无险,没有酿成交通事故。在此交警提醒广大驾驶人,车用篷布一定要系好绑牢,避免滑落后引发交通事故。     

恶劣海况下火车轮渡运输技术及运动响应试验和仿真研究

火车海上运输技术要求与陆上铁路运输区别较大。通过理论分析和试验方式研究跨海火车轮渡在临近8级风、浪高4.5 m的恶劣海况下航行时加速度、摇摆角等运输技术参数变化情况，结果证明理论计算值与试验值相差较大，说明现行理论计算方法是基于远洋航行海况条件，计算工况与琼州海峡等近海海况条件相差较大。试验过程中渡船姿态变化比较平稳，火车甲板上铁路货车及货物运输技术状态优于陆上运行技术状态，按现行铁路相关规定可满足恶劣海况条件火车轮渡安全运输要求。对打舵操作模拟渡船恶劣海况航行时运动相应试验与仿真模拟计算结果对比表明，在6～8级风恶劣海况条件下只有部分试验测量值与相应海况模拟计算值相当，打舵操作方式尚不能完全模拟实际恶劣海况条件。     

春季驾车“五防”

春回大地,万物复苏,气候宜人,是运输行业的“旺季”。但春季风多、雨多,再加上有时寒流回升,一旦处理不好或身体不适,极易引发交通事故。因此,春季驾车要做到“五防”;一防春风。春季风多,尽管有些风的声波频率很低,但对人体神经中枢有影响,危害交通安全。若遇大风,路面灰尘满天,飞沙走石,影响驾驶员的视觉,直接影响行车安全。     

沥青混合料长距离运输施工质量保障措施

经过长距离运输后，沥青混合料温度衰减较快且往往达不到压实温度，严重影响沥青路面的密实度，进而影响其服役寿命。本文研究了传统篷布覆盖方式、顶部加盖保温材料条件下沥青混合料的温度变化规律，基于沥青混合料散热特征研究了运输车外裹不同保温材料的措施及设计方法。研究发现，置于车厢不同部位的沥青混合料温度衰减速率不同，顺序为边部>顶部>内部，且温度随时间呈现线性变化；加盖保温材料能够降低沥青混合料温度衰减速率；从经济性角度考虑，矿渣棉和岩棉更适用于长距离运输过程中的沥青混合料保温。     

加强非正常情况下铁路车站行车安全管理

非正常情况主要是指铁路车站由突然发生的危及运输安全的条件和环境变化所引起的情况.其主要包括发生行车设备故障而影响行车秩序,引发行车组织变化;发生铁路交通事故,需要应急处置和事故救援;出现风、雪、雾等不良天气,直接威胁运输安全,需要采取特定的行车组织方式;营业线和临近营业线施工,造成行车条件变化或施工中对运输安全构成一定的威胁.     

新疆铁路风区大风天气列车安全运行办法研究

新疆铁路强风地区是我国风灾最为严重的地区,((大风天气列车安全运行办法>,是乌鲁木齐铁路局在大风天气下指挥行车的重要依据,更足新疆铁路防风安全体系中的重要组成部分.根据新疆铁路风区的实际情况,结合多年来的研究成果和运营经验,对<大风天气列车安全运行办法>的关键技术指标制定的办法和步骤进行了探讨.     

D38型钳夹车托钩方式运输大型设备通过复式交分道岔的测试分析

对D_(38)型钳夹车采用托钩方式运输大型设备通过复式交分道岔时,货车和托钩的受力情况进行了分析,经与相关试验对比分析后,确认D_(38)型钳夹车托钩方式运输大型设备,以5km/h的速度通过复式交分道岔是可以保证运输安全的。     

舆情

正运17吨苹果因一卷篷布被收通行费不合理日前,网络上一则"货车司机因在运输17吨苹果的车厢里放了一卷40斤的备用篷布,被收取3570元通行费"的消息引发公众热议。根据相关规定,整车合法装载运输全国统一的《鲜活农产品品种目录》内产品的车辆,免收车辆通行费。"整车合法装载运输"是指车货总重和外廓尺寸均未超过国家规定的最大限值,且所载鲜活农产品应占车辆核定载质量或者车厢容积的80%以上、没有与非鲜活农产品混装等行为。     

铁路运输安全风险管控及评价体系构建

铁路运输安全质量的好坏直接关系到人民生命财产安全和铁路的可持续、高质量发展。实施安全风险管控可以有效防范和减少事故发生,降低事故造成的损失。立足于铁路运输安全,从风险识别研判、制定风险控制表、建立风险问题库、实施过程精准管控4个方面,研究铁路运输安全风险管控流程优化,构建运输安全风险评价模型,以某铁路局集团公司某站进行算法示例。运输安全风险管控体系的构建对于有效管控安全风险、客观评价风险受控状态,具有一定的现实价值和可操作性。     

六氟化铀铁路运输要求及现状分析

<正>六氟化铀作为核工业中重要的放射性物品，国家、行业等层面均针对铁路运输制定了管理规定和技术要求。其中，铁路运输行业依据《放射性物品安全运输管理条例》制定了放射性危险货物运输的相关管理办法，而六氟化铀包装和运输的技术要求依据GB11806，相比之下核行业相关标准的内容缺乏更新。结合实际运输活动中暴露的问题，建议开展高温条件下的试验和计算分析，优化六氟化铀铁路运输活动环节，降低人员辐射剂量。0.引言在核工业铀纯化转化环节，六氟化铀是获取浓缩铀极为重要的中间产品，其作为一种具有挥发性的放射性物品，     

Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data

Traffic crashes are geographical events, and their spatial patterns are strongly linked to the regional characteristics of road network, sociodemography, and human activities. Different human activities may have different impacts on traffic exposures, traffic conflicts and speeds in different transportation geographic areas, and accordingly generate different traffic safety outcomes. Most previous researches have concentrated on exploring the impacts of various road network attributes and sociodemographic characteristics on crash occurrence. However, the spatial impacts of human activities on traffic crashes are unclear. To fill this gap, this study attempts to investigate how human activities contribute to the spatial pattern of the traffic crashes in urban areas by leveraging multi-source big data. Three kinds of big data sources are used to collect human activities from the New York City. Then, all the collected data are aggregated into regional level (ZIP Code Tabulation Areas). Geographically Weighted Poisson Regression (GWPR) method is applied to identify the relationship between various influencing factors and regional crash frequency. The results reveal that human activity variables from multi-source big data significantly affect the spatial pattern of traffic crashes, which may bring new insights for roadway safety analyses. Comparative analyses are further performed for comparing the GWPR models which consider human activity variables from different big data sources. The results of comparative analyses suggest that multiple big data sources could complement with each other in the coverage of spatial areas and user groups, thereby improving the performance of zone-level crash models and fully unveiling the spatial impacts of human activities on traffic crashes in urban areas. The results of this study could help transportation authorities better identify high-risky regions and develop proactive countermeasures to effectively reduce crashes in these regions.     

A multi-criteria analysis framework including environmental and health impacts for evaluating traffic calming measures at the road network level

Recent interests in both vehicle emissions and public health have facilitated the development of more eco-friendly transportation systems. This study developed a multi-criteria evaluation framework to evaluate the effectiveness of traffic calming measures (TCMs) from the various perspectives at the road network level; operational efficiency, traffic safety, environmental and health impacts. The proposed methodology employs four-step sequential simulation experiments, including driving, traffic flow, emissions, and air dispersion simulations. The results obtained from these four simulations are used to evaluate the effectiveness in terms of safety and operational efficiency in addition to environmental and health impacts. A multi-criteria value function based on the weights estimated from the analysis of an analytical hierarchy process (AHP) is applied in the evaluation framework. As an application, chicanes and speed humps widely implemented in Korean school zones were evaluated at the road network level. The proposed simulation-based approach is expected to be effectively used for the decision-making process in selecting better alternatives for TCM.     

Assessing the road safety impacts of a teleworking policy by means of geographically weighted regression method

Travel demand management (TDM) consists of a variety of policy measures that affect the effectiveness of transportation systems by changing travel behavior. The primary objective of such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to simulate the traffic safety impact of conducting a teleworking scenario (i.e. 5% of the working population engages in teleworking) in the study area, Flanders, Belgium. Since TDM strategies are usually conducted at a geographically aggregated level, crash prediction models should also be developed at an aggregate level. Given that crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is also examined. The results indicate the necessity of accounting for the spatial correlation when developing crash prediction models. Therefore, zonal crash prediction models (ZCPMs) within the geographically weighted generalized linear modeling framework are developed to incorporate the spatial variations in association between the number of crashes (including fatal, severe and slight injury crashes recorded between 2004 and 2007) and other explanatory variables. Different exposure, network and socio-demographic variables of 2200 traffic analysis zones (TAZs) are considered as predictors of crashes. An activity-based transportation model framework is adopted to produce detailed exposure metrics. This enables to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models. In this study, several ZCPMs with different severity levels and crash types are developed to predict crash counts for both the null and the teleworking scenario. The results show a considerable traffic safety benefit of conducting the teleworking scenario due to its impact on the reduction of total vehicle kilometers traveled (VKT) by 3.15%. Implementing the teleworking scenario is predicted to reduce the annual VKT by 1.43 billion and the total number of crashes to decline by 2.6%.     

Optimal traffic calming: A mixed-integer bi-level programming model for locating sidewalks and crosswalks in a multimodal transportation network to maximize pedestrians’ safety and network usability

We study the effect that installing sidewalks and crosswalks, as traffic calming facilities, has on the safety and usability of a transportation network with automobile, public transit and walking as modes of transportation. A mathematical programming model is proposed for this problem whose objective is to minimize the safety hazard for pedestrians and the total transportation cost of the network. We utilize a customized greedy heuristic and a simulated annealing algorithm for solving the problem. The computational results indicate that installing sidewalks and crosswalks at proper locations can reduce the overall transportation cost and improve pedestrians’ safety.     

A delay estimation technique for single and double-track railroads

To route and schedule trains over a large complex network can be computationally intensive. One way to reduce complexity could be to “aggregate” suitable sections of a network. In this paper, we present a simulation-based technique to generate delay estimates over track segments as a function of traffic conditions, as well as network topology. We test our technique by comparing the delay estimates obtained for a network in Los Angeles with the delays obtained from the simulation model developed by Lu et al. [Lu, Q., Dessouky, M.M., Leachman, R.C., 2004. Modeling of train movements through complex networks. ACM Transactions on Modeling and Computer Simulation 14, 48–75], which has been shown to be representative of the real-world delay values. Railway dispatchers could route and schedule freight trains over large networks by using our technique to estimate delay across aggregated network sections.     

基于卷积神经网络的列车检测算法研究

列车检测作为列车自动驾驶的核心技术,可以有效地降低列车追尾等事故造成的人身危险和财产损失。为实现精准的列车检测,选用改进的卷积神经网络(PVANET)对输入图像进行特征提取,在此基础上,采用候选区域网络,从生成的特征图里滑动搜索,判断出图像中可能为列车的区域位置,并进一步采用快速区域卷积神经网络对每个候选区域进行分类,计算出其所属类别的置信度,同时精确定位列车。经验证,该方法适应范围广、鲁棒性高,可以有效地检测不同环境光强及不同朝向的列车,保障列车安全,为列车自动驾驶及辅助驾驶提供安全保障。     

The geography of freight-related accidents in the era of E-commerce: Evidence from the Los Angeles metropolitan area

Due to the burgeoning demand for freight movement in the era of e-commerce, freight related road safety threats have been growing in both urban and suburban areas, despite the improved general traffic safety over the past decades. The empirical evidence on how freight trucks related crashes are distributed across neighborhoods and correlated to spatially varying factors is, however, highly limited. This article uses data from the Los Angeles region in 2018 to analyze the spatial patterns of freight trucks related traffic crashes and examines the major factors that contribute to those patterns using spatial econometric models. Maps show that freight trucks related crashes are highly associated with major freight generators but less clustered than the overall traffic crashes. Results from the spatial Durbin model indicate that access to freight generators, economic attributes, land uses, road infrastructure, and road network variables all contribute to the spatial distribution of freight trucks related crashes. The findings could help transport planners understand the dynamics of freight trucks related traffic safety and develop operational measures for mitigating the impacts of growing goods movement on local communities.     

Investigating the associations between road network structure and non-motorist accidents

Road networks channel traffic flow and can impact the volume and proximity of walking and bicycling. Therefore, the structure of road networks—the pattern by which roads are connected—can affect the safety of non-motorized road users. To understand the impact of roads’ structural features on pedestrian and bicyclist safety, this study analyzes the associations between road network structure and non-motorist-involved crashes using data from 321 census tracts in Alameda County, California. Average geodesic distance, network betweenness centrality, and an overall clustering coefficient were calculated to quantify the structure of road networks. Three statistical models were developed using the geographically weighted regression (GWR) technique for the three structural factors, in addition to other zonal factors including traffic behavior, land use, transportation facility, and demographic features. The results indicate that longer average geodesic distance, higher network betweenness centrality, and a larger overall clustering coefficient were related to fewer non-motorist-involved accidents. Thus, results suggest that: (1) if a network is more highly centered on major roads, there will be fewer non-motorist-involved crashes; (2) a network with a greater average number of intersections on the shortest path connecting each pair of roads tends to experience fewer crashes involving pedestrians and bicyclists; and (3) the more clustered road networks are into several sub-core networks, the lower the non-motorist crash count. The three structural measurements can reflect the configuration of a network so that it can be used in other network analyses. More information about the types of road network structures that are conducive to non-motorist traffic safety can help to guide the design of new networks and the retrofitting of existing networks. The estimation results of GWR models explain the spatial heterogeneity of correlations between explanatory factors and non-motorist crashes, which can support regional agencies in establishing local safety policies.     

Driver behaviour,truck motion and dangerous road locations – Unfolding from emergency braking data

Road vehicles equipped with measurement, computing, data storage and data communication capabilities can be utilised as probe-vehicles. Data received from such vehicles can provide valuable traffic and traffic safety information in respect of the covered routes and the connecting road network. In this study, trucks negotiating their normal daily haulage trips were used as probe-vehicles and the data recording their vehicular emergency events, such as abrupt braking events, detected by their on-board vehicular safety systems were analysed. The motivation for such an analysis is manifold. The aspect emphasized here is that the recorded vehicular emergency actions and events can be seen as surrogate safety events. Some of these surrogate safety events mark traffic incidents and therefore can be used as input by the surrogate safety assessment methodology. Though the vehicular emergency data used herein provides only sparse spatial and temporal coverage of the road network investigated, its analysis led to some interesting findings about interactions between drivers, trucks and roads.     

A systematic approach to assess the effectiveness of airport noise mitigation strategies

Regional airports are often located very close to the urban area they serve and the increasing traffic rate that many of them have experienced in the last years has produced several impacts on the communities living close to the airport area, mainly aviation noise. If not properly managed, noise impacts produced by airport operations can cut down significantly the development of airport air traffic with direct effects on the economic and territorial systems. Aeronautical noise has greatly reduced in the last decade, due to aircraft design technological improvements and more severe regulations. However, the noise reduction during a single event does not make the issue of the airport location – and then the whole noise impact – less significant. This paper proposes an assessment process to evaluate the effects of actions adopted to reduce airport noise impacts on populated areas. Both airport-related factors – such as number of take-off; day-evening-night distributions of movements; aircraft type; flying paths – and land-use characteristics have been considered and combined in a density index that synthesizes the impacts of airport noise on the territory. The assessment process has been tested on a real case, the airport of Bologna in Northern Italy. The predicted results, compared with available real data for the test case, are significant and encourage the use of the proposed assessment process as decision support system for the airport management.