道路交叉口冲突仿真分析

针对基于事故的安全评价在数量、周期、均值、随机性等方面以及基于现场冲突观测识别在主观性、可靠性、成本、指标全面性等方面存在的问题,提出基于冲突仿真的交叉口安全预评价分析方法:研究利用安全间接分析(SSAM)模型分析冲突的基本原理和冲突时间(TTC)、遭遇时间(PET)等分析指标的计算方法;以及利用VISSIM仿真软件进行冲突仿真分析应注意的策略。以邢台市某道路交叉口安全改善方案为例,进行改善前后冲突仿真的比较分析。研究结果表明,改善后在通行效率显著提升的同时,交叉、追尾、车道变换冲突的数量均显著减少,TTC值有所增加,说明改善后安全程度有所提升。笔者提出的方法和案例应用为道路交叉口改善措施的安全预评价提供了一种分析途径和有益借鉴。     

克拉玛依市区大气尘污染研究

对克拉玛依市区大气尘污染的特征及变化规律进行了全面的分析和研究。结果表明，市区的尘污染有加重的趋势，降尘属中度污染，道路尘污 染也较严重。提出了一些具体的防治对策。     

高速公路运营安全性评价

系统研究国内外道路运营安全评价先进技术,认为各种安全评价方法有其优缺点,单一方法使用时,难以得到全面、可靠的评价结果。在此基础上,结合我国高速公路运营状况,提出了运用速度协调性分析、事故调查与分析、设计符合性以及运营安全评价清单进行评价的高速公路运营综合安全评价方法。该方法能最大程度地发现事故隐患、预防事故的发生或减轻事故的严重程度。并运用该方法对某改建高速公路进行了运营安全评价,指出了该拟改建高速公路两处事故多发路段和3方面的安全隐患,证实了综合安全评价方法的有效性。     

辽宁省典型城市道路尘PM2.5成分谱研究

为构建辽宁省典型城市道路尘源成分谱，分别采集了鞍山市和盘锦市道路尘样品，分析了其化学组分特征，用富集因子法和比值法分析了其主要来源，用分歧系数法分析了两个城市成分谱的相似度.结果表明：盘锦市和鞍山市道路尘PM_2.5中的化学组成以有机碳组分（OC）和地壳类元素（Al、Ca、Mg、Fe和K）为主.除Cu和V元素外，其余元素均表现为鞍山市的富集因子大于盘锦市.由比值法可得，盘锦市和鞍山市OC/EC分别为（13.20±6.26）和（3.94±0.63），均存在二次污染现象；NO₃^-/SO₄^2-的均值分别为（0.52±0.55）和（0.46±0.13），说明其道路尘PM_2.5受固定源影响更大.盘锦市与鞍山市道路尘成分谱分歧系数为0.354，说明两个源成分谱可能相似.     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

高速公路交通流实时安全性评价

根据多条高速公路近3年的事故数据及实时交通流数据,分析了高速公路运营安全性的相关影响因素,在此基础上提出了车速变异系数指标及其分级标准,建立了考虑交通流量、平均车速、车速变异系数、天气条件等多因素的高速公路交通流运行风险预测多元模型,并提出了高速公路交通流实时行车风险指数TRI指标,制定了交通流状态实时安全性评价标准,最后给出了高速公路交通流混合交通状态下的实时安全风险评价流程。通过西攀高速公路的交通流实时数据,验证了模型的有效性。     

连续长坡路段驾驶员心率与平曲线半径关系研究

为研究公路连续长坡路段驾驶员心率与曲线半径的关系,提高行车安全,选取9名驾驶员进行实际道路试验.用多导生理记录仪采集驾驶员的心率数据,按上、下坡方向将试验路段的每个曲线划分为7个位置,分别对上、下坡方向每个位置驾驶员的心率增长率和曲线半径的关系进行回归分析,建立相应的模型,并对每个位置的模型进行分析,提出合理的曲线半径设置建议.综合上、下坡方向各位置的曲线半径研究结论提出合理的曲线半径取值建议,公路连续长坡路段曲线半径在r≥900 m和200 m≤r≤300 m内取值.     

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

驾驶员雨中面对不同颜色障碍物时制动点选择研究

为研究雨天驾驶员对障碍物颜色的感知特征,保障雨天驾驶安全,利用仿真驾驶平台,研究大雨、中雨、小雨3种状况下,驾驶员面对红、白、黑3种颜色障碍物时的鸣笛点(与障碍物距离设为L1)、刹车点(与障碍物距离设为L2)的选择和行驶初速度(V1)与通过障碍物最小速度(V2)的关系。最后,依据模拟驾驶采集得到的23位驾驶员经过各颜色障碍物的驾驶数据,通过SPSS分析L2,V1的拟合关系,结合安全制动距离模型,建立不同雨量下驾驶员受障碍物颜色影响的行车安全模型。结果表明:运行速度相同时,红色障碍物对应的L1,L2值明显大于黑色和白色对应的值;面对同种颜色的障碍物时,随着雨量的增加,V2值不断减小,而V1越大,V2值越大。     

绿灯倒计时信号对驾驶行为的影响

为揭示绿灯倒计时信号对交叉口交通安全的影响,针对不同交通负荷与信号控制方式下的驾驶行为开展研究。选择大连市内的倒计时信号交叉口与非倒计时信号交叉口各2处,开展车辆行驶速度及不良驾驶行为调查。用数理统计方法,对比分析2类交叉口在平峰与高峰时段的车辆行驶速度特性,同时对比分析上述不同条件下闯黄灯及违规变道行为的发生数量。研究表明,绿灯倒计时信号在绿灯时间末期,会诱发一部分驾驶员加速行驶通过交叉口;绿灯倒计时信号在平峰时段对闯黄灯行为数量的影响较小,而对违规变道行为的数量有显著影响。