106国道沿线样带区农村空心化土地整治潜力研究

基于典型调查资料和社会经济统计数据,在构建农村空心化评价指标体系并定量评判106国道沿线样带区县域农村空心化程度的基础上,结合自然条件和土地资源特点、农村居民点用地的有关法律规定,采用专家集成法选取与现实潜力转化有关的自然、社会、经济等10个指标建立综合指标体系,对空心村整治的自然适宜性、社会接受性、经济可行性进行了综合评价;将计算得到的农村空心化指数与现实转化潜力系数作为综合修正系数,对理论潜力进行修正,结合农村居民点整治潜力测算公式,测算出106国道沿线样带区不同农村空心化演进类型的现状潜力和远景潜力。研究表明:106国道沿线样带区县域农村空心化指数为0.18~0.82,现实转化潜力系数为0.07~0.32; 2009、2020年农村居民点整治的现实潜力分别为93 219.4、145 430.0 hm²,村庄整治增地率分别为6.8%、11.4%。研究将为空心村整治和新农村建设规划决策提供科学依据。     

机动车排放检测运行体系的相关研究

机动车污染物排放标准与其检测方法是相辅相成的，不同的机动车检测方法对应不同的机动车排放污染物限值。该文主要对机动车排放检测运行体系中的怠速和简易工况检测方法进行了对比性研究，并对机动车实施常规检测的年检和监督手段的路检进行了对比分析，从而得出：工况法检测对于尾气排放情况的模拟要优于怠速法检测，并可对NOx进行有效控制，所以建议在有条件的地区，应该尽量实施工况法检测：年检和路检的数据有较大的差异，反映出对在用车的监督不力，今后应加强；高排放车辆的贡献率所占的比例与发达国家相比太小，说明机动车总体控制水平较低。     

Risk analysis for road and rail transport of hazardous materials: a GIS approach

An approach to transportation risk analysis for road and rail transport of dangerous goods is proposed, which is based on the use of geographic information systems (GIS) to manage territorial information, coupled with a product data bank in a risk evaluation tool. Such an approach enables to accurately take into account the local data affecting risk analysis, such as population, accident rate, and weather conditions along all the route, by means of a system which can be easily updated. The resulting risk evaluation tool assists in the step of route identification and allows to rapidly perform an accurate transportation risk analysis, for a single transportation event as well as for multiple substances, trips and itineraries.     

道路交通环境影响评价的物元模型

分析了城市道路交通环境影响因素,提出了一套道路交通环境影响评价指标体系,并应用物元分析理论建立了相应的评价物元模型     

上海城市街道峡谷道路绿化模式研究

街道峡谷在上海城市中普遍存在,街道峡谷中污染气体的扩散受到屋顶风向、风速、高宽比、峡谷两侧建筑物的对称性、高度分布和街区形状等因素的影响。文章对适合于不同街道峡谷形式的、较为典型的道路绿化模式进行了研究。结果表明,上海城市街道峡谷中的道路绿化模式可归纳为:梯级递进式、斑块复合式、疏朗开敞式、模纹花镜式和独立行道树式5种。当街道峡谷与主导风垂直:(1)街道峡谷的W/H>5且为平行型峡谷时,绿化模式应采用梯级递进式或疏朗开敞式;(2)街道峡谷的W/H为0.6～5且为平行型峡谷时,绿化模式在迎风侧采用流朗开敞式、背风侧采用模纹花镜式,或者两侧都采用模纹花镜式;(3)街道峡谷的W/H<0.6且为平行型峡谷时,绿化模式应采用模纹花镜式或独立行道树式;(4)街道峡谷的W/H<0.6且为递升型峡谷时,绿化模式在迎风侧采用斑块复合式或模纹花镜式,背风侧采用模纹花镜式或独立行道树式;(5)街道峡谷的W/H<0.6且为递降型峡谷时,绿化模式可采用模纹花镜式或独立行道树式;当街道峡谷与主风向平行:宽、高比大的街道绿化模式应采用梯级递进式或斑块复合式,当街道峡谷的高度是宽度的倍数时,道路绿化宜采用疏朗开敞式或独立行道树式。     

Determining the risk of driver-at-fault events associated with common distraction types using naturalistic driving data

Introduction: Studies thus far have focused on automobile accidents that involve driver distraction. However, it is hard to discern whether distraction played a role if fault designation is missing because an accident could be caused by an unexpected external event over which the driver has no control. This study seeks to determine the effect of distraction in driver-at-fault events. Method: Two generalized linear mixed models, one with at-fault safety critical events (SCE) and the other with all-cause SCEs as the outcomes, were developed to compare the odds associated with common distraction types using data from the SHRP2 naturalistic driving study. Results: Adjusting for environment and driver variation, 6 of 10 common distraction types significantly increased the risk of at-fault SCEs by 20-1330%. The three most hazardous sources of distraction were handling in-cabin objects (OR = 14.3), mobile device use (OR = 2.4), and external distraction (OR = 1.8). Mobile device use and external distraction were also among the most commonly occurring distraction types (10.1% and 11.0%, respectively). Conclusions: Focusing on at-fault events improves our understanding of the role of distraction in potentially avoidable automobile accidents. The in-cabin distraction that requires eye-hand coordination presents the most danger to drivers’ ability in maintaining fault-free, safe driving. Practical Applications: The high risk of at-fault SCEs associated with in-cabin distraction should motivate the smart design of the interior and in-vehicle information system that requires less visual attention and manual effort.     

Modeling drivers’ reaction when being tailgated: A Random Forests Method

Background: Tailgating is a common aggressive driving behavior that has been identified as one of the leading causes of rear-end crashes. Previous studies have explored the behavior of tailgating drivers and have reported effective solutions to decrease the amount or prevalence of tailgating. This paper tries to fill the research gap by focusing on understanding highway tailgating scenarios and examining the leading vehicles’ reaction using existing naturalistic driving data. Method: A total of 1,255 tailgating events were identified by using the one-second time headway threshold criterion. Four types of reactions from the leading vehicles were identified, including changing lanes, slowing down, speeding up, and making no response. A Random Forests algorithm was employed in this study to predict the leading vehicle’s reaction based on corresponding factors including driver, vehicle, and environmental variables. Results: The analysis of the tailgating scenarios and associated factors showed that male drivers were more frequently involved in tailgating events than female drivers and that tailgating was more prevalent under sunny weather and in daytime conditions. Changing lanes was the most prevalent reaction from the leading vehicle during tailgating, which accounted for more than half of the total events. The results of Random Forests showed that mean time headway, duration of tailgating, and minimum time headway were three main factors, which had the greatest impact on the leading vehicle drivers’ reaction. It was found that in 95% of the events, leading vehicles would change lanes when being tailgated for two minutes or longer. Practical Applications: Results of this study can help to better understand the behavior and decision making of drivers. This understanding can be used in designing countermeasures or assistance systems to reduce tailgating behavior and related negative safety consequences.     

Disaggregated traffic conditions and road crashes in urban signalized intersections

Introduction: Road safety studies in signalized intersections have been performed extensively using annually aggregated traffic variables and crash frequencies. However, this type of aggregation reduces the strength of the results if variables that oscillate over the course of the day are considered (speed, traffic flow, signal cycle length) because average indicators are not able to describe the traffic conditions preceding the crash occurrence. This study aims to explore the relationship between traffic conditions aggregated in 15-min intervals and road crashes in urban signalized intersections. Method: First, an investigation of the reported crash times in the database was conducted to obtain the association between crashes and their precursor conditions. Then, 4.1 M traffic condition intervals were consolidated and grouped using a hierarchical clustering technique. Finally, charts of the frequency of crashes per cluster were explored. Results: The main findings suggest that high vehicular demand conditions are related to an increase in property damage only (PDO) crashes, and an increase in the number of lanes is linked to more PDO and injury crashes. Injury crashes occurred in a wide range of traffic conditions, indicating that a portion of these crashes were due to speeding, while the other fraction was associated with the vulnerability of road users. Traffic conditions with: (a) low vehicular demand and a long cycle length and (b) high vehicular demand and a short cycle length were critical in terms of PDO and injury crashes. Practical Applications: The use of disaggregated data allowed for a stronger evaluation of the relationship between road crashes and variables that oscillate over the course of the day. This approach also permits the development of real-time risk management strategies to mitigate the frequency of critical traffic conditions and reduce the likelihood of crashes.     

Structural anatomy and temporal trends of road accident research: Full-scope analyses of the field

Introduction: Scholarly research on road accidents over the past 50 years has generated substantial literature. We propose a robust search strategy to retrieve and analyze this literature. Method: Analyses was focused on estimating the size of this literature and examining its intellectual anatomy and temporal trends using bibliometric indicators of its articles. Results: The size of the literature is estimated to have exceeded N = 25,000 items as of 2020. At the highest level of aggregation, patterns of term co-occurrence in road accident articles point to the presence of six major divisions: (i) law, legislation & road trauma statistics; (ii) vehicular safety technology; (iii) statistical modelling; (iv) driving simulator experiments of driving behavior; (v) driver style and personality (social psychology); and (vi) vehicle crashworthiness and occupant protection division. Analyses identify the emergence of various research clusters and their progress over time along with their respective influential entities. For example, driver injury severity ” and crash frequency show distinct characteristics of trending topics, with research activities in those areas notably intensified since 2015 Also, two developing clusters labelled autonomous vehicle and automated vehicle show distinct signs of becoming emerging streams of road accident literature. Conclusions: By objectively documenting temporal patterns in the development of the field, these analyses could offer new levels of insight into the intellectual composition of this field, its future directions, and knowledge gaps. Practical Applications: The proposed search strategy can be modified to generate specific subsets of this literature and assist future conventional reviews. The findings of temporal analyses could also be instrumental in informing and enriching literature review sections of original research articles. Analyses of authorships can facilitate collaborations, particularly across various divisions of accident research field.     

Driver glare exposure with different vehicle frontlighting systems

Introduction: Highway safety performance at night has received less attention in research than daytime, despite the higher accident rates occurring under night-time conditions. This study presents a procedure to assess the potential hazard for drivers created by headlight glare and its interaction with the geometric design of highways. Method: The proposed procedure consists of a line-of-sight analysis performed by a geoprocessing model in geographic information systems to determine whether the rays of light that connect headlights and oncoming drivers are obstructed by either the roadway or its roadsides. Then, the procedure checks whether the non-obstructed rays of light are enclosed by a given headlight beam. Different hypotheses were set concerning the headlight beam features, including the horizontal spread angle and whether the headlights are fixed or swiveling. A highway section was selected to test and validate the procedure proposed. A 3D recreation of the highway and its environment derived from a LiDAR point cloud was used for this purpose. Results: The findings disclose how glare is produced on tangents, horizontal curves, transitions between them and sequences of curves. The effect of visual obstructions conveniently placed is also discussed. Conclusions: A greater glare incidence is produced as the horizontal headlights spread angle increases. Swiveling headlights increase glare on highways left curves and reduce it on right curves. Practical Applications: The procedure and conclusions of this study can contribute to develop more effective glare avoidance technologies as well as identify and assess glare-prone sections. The glare evaluation assists in evaluating glare countermeasures such as deciding whether to place a vegetation barrier and where.