基于改进对比学习的道路裂缝图像分类

道路裂缝是路面破损的重要组成部分,而道路裂缝分类可以对道路养护策略的制定进行针对性的安排.针对人工标注分类耗时长,效率低等问题,本文提出了一个基于对比学习的道路裂缝图像分类方法,在传统的对比学习框架中,对特征提取部分进行改进,使得模型对细小裂缝的特征更敏感.首先对进行数据增强,其次在特征提取部分对ResNet50的部分进行改进,使用多尺度的方法提取特征;再使用多层感知机(MLP)对提取到的特征进行降维处理,并投影到向量空间;最后使用余弦相似度与用归一化温度标度的交叉熵损失对模型进行优化.实验结果表明,改进后的模型比原模型在裂缝图像上的分类效果提高了0.22%,达到了92.1%,对裂缝图像分类有较好的效果.     

Factors contributing to young moped rider accidents in Denmark

Young road users still constitute a high-risk group with regard to road traffic accidents. The crash rate of a moped is four times greater than that of a motorcycle, and the likelihood of being injured in a road traffic accident is 10–20 times higher among moped riders compared to car drivers. Nevertheless, research on the behaviour and accident involvement of young moped riders remains sparse.Based on analysis of 128 accident protocols, the purpose of this study was to increase knowledge about moped accidents. The study was performed in Denmark involving riders aged 16 or 17. A distinction was made between accident factors related to (1) the road and its surroundings, (2) the vehicle, and (3) the reported behaviour and condition of the road user. Thirteen accident factors were identified with the majority concerning the reported behaviour and condition of the road user. The average number of accident factors assigned per accident was 2.7. Riding speed was assigned in 45% of the accidents which made it the most frequently assigned factor on the part of the moped rider followed by attention errors (42%), a tuned up moped (29%) and position on the road (14%). For the other parties involved, attention error (52%) was the most frequently assigned accident factor. The majority (78%) of the accidents involved road rule breaching on the part of the moped rider.The results indicate that preventive measures should aim to eliminate violations and increase anticipatory skills among moped riders and awareness of mopeds among other road users. Due to their young age the effect of such measures could be enhanced by infrastructural measures facilitating safe interaction between mopeds and other road users.     

Effects of parallelogram-shaped pavement markings on vehicle speed and safety of pedestrian crosswalks on urban roads in China

The primary objective of this study was to evaluate the effects of parallelogram-shaped pavement markings on vehicle speed and crashes in the vicinity of urban pedestrian crosswalks. The research team measured speed data at twelve sites, and crash data at eleven sites. Observational cross-sectional studies were conducted to identify if the effects of parallelogram-shaped pavement markings on vehicle speeds and speed violations were statistically significant. The results showed that parallelogram-shaped pavement markings significantly reduced vehicle speeds and speed violations in the vicinity of pedestrian crosswalks. More specifically, the speed reduction effects varied from 1.89 km/h to 4.41 km/h with an average of 3.79 km/h. The reduction in the 85th percentile speed varied from 0.81 km/h to 5.34 km/h with an average of 4.19 km/h. Odds ratios (OR) showed that the parallelogram-shaped pavement markings had effects of a 7.1% reduction in the mean speed and a 6.9% reduction in the 85th percentile speed at the pedestrian crosswalks. The reduction of proportion of drivers exceeding the speed limit varied from 8.64% to 14.15% with an average of 11.03%. The results of the crash data analysis suggested that the use of parallelogram-shaped pavement markings reduced both the frequency and severity of crashes at pedestrian crosswalks. The parallelogram-shaped pavement markings had a significant effect on reducing the vehicle–pedestrian crashes. Two crash prediction models were developed for vehicle–pedestrian crashes and rear-end crashes. According to the crash models, the presence of parallelogram-shaped pavement markings reduced vehicle–pedestrian crashes at pedestrian crosswalks by 24.87% with a 95% confidence interval of [10.06–30.78%]. However, the model results also showed that the presence of parallelogram-shaped pavement markings increased rear-end crashes at pedestrian crosswalks by 5.4% with a 95% confidence interval of [0–11.2%].     

玄武岩纤维对老化沥青混合料路用性能的影响

为研究玄武岩纤维对老化沥青混合料路用性能的影响,通过车辙试验、低温弯曲小梁试验、浸水马歇尔试验和冻融劈裂试验研究了玄武岩纤维对沥青混合料抗老化性能的作用。试验结果表明:虽然玄武岩纤维沥青混合料的动稳定度随老化时间增加,但相对于普通沥青混合料而言,其增加的幅度减缓,提出采用相对变形率作为老化性能评价指标;玄武岩纤维延缓了沥青混合料老化性能的衰变,使得老化后的混合料低温抗裂性改善;经短期老化和长期老化后玄武岩纤维沥青混合料水稳定性能均优于普通沥青混合料,且玄武岩纤维显著降低了长期老化试件的未冻融劈裂强度,因此在应用中应适当增加碾压次数。     

道路常用温拌改性剂现状与路用性能评价

针对工程使用温拌剂时缺乏明确的参考依据,系统调查了国内外温拌剂应用状况,确定温拌改性技术主要分类以及目前常用温拌剂种类,全面评价了Sasobit、Aspha-min、Evotherm与EC120等4种常用温拌剂对沥青混合料高温性能、低温性能以及水稳定性等路用性能的影响。结果表明:几种温拌剂的降温效果均可达到30℃,Sasobit和EC120温拌剂对沥青混合料高温稳定性均有不同幅度提高,最大提高幅度在30%以上,4种温拌剂对沥青混合料低温性能略有影响,对水稳定性的影响均不大。     

浇注式沥青混凝土现状与发展

为进一步确定浇注式沥青混凝土科学合理的性能评价指标及要求,全面梳理了国内外浇注式沥青混凝土相关规范,对比评价了不同规范中的技术指标要求及级配范围,系统地调查了大量实体工程及研究动态,厘定了浇注式沥青混凝土钢桥面铺装结构层组合、原材料类型和技术指标要求及级配类型,为浇注式沥青混凝土规范完善与质量控制奠定了基础。结果表明:推荐钢桥面铺装结构层组合为30~35mm GA-10+35~40mm SMA-10,GA基础沥青为SBS改性沥青+TLA(15%~30%),采用2%降粘剂;推荐性能评价指标要求范围为油石比7.9%~8.5%、流动度10~17s、贯入度1.4~2.5mm、贯入度增量不超过0.25mm、弯拉应变不小于7 000με、动稳定度不小于1 000次/mm(参考指标);疲劳性能试验以控制应变模式进行,结果以实测为准。     

老化SBS改性沥青二次改性再生工艺及机理研究

为研究老化SBS改性沥青的二次改性再生效果,比较不同工艺对再生效果的影响,首先通过常规试验、SHRP试验选择恰当的SBS改性沥青老化模拟方式,然后对添加SBS改性剂、新沥青进行再生的3种工艺展开研究,并借助红外光谱试验分析不同掺加顺序对老化SBS改性沥青再生效果的影响,确定了改性剂及新、旧沥青的最佳比例和最佳工艺。结果表明:采用RTFOT试验进行老化模拟更加方便、科学,RTFOT试验5h获得的改性沥青指标与服务年龄为7年的SBS改性沥青一致;SBS改性剂、新沥青添加顺序与老化沥青再生效果关系密切,先将SBS改性剂和新沥青混合制备改性沥青,再将改性沥青与老化沥青混合的工艺可使再生沥青性能最佳,其中SBS最佳掺量为4%,新、旧沥青质量比为2。     

一种自适应的区域生长算法用于道路分割

针对汽车在高速公路上行驶的道路区域分割问题,以路面颜色特征为研究对象,提出了一种将聚类分析应用于区域生长准则的算法,实现道路分割.为了提高算法的精确度,对图像进行预处理,消除车道线对道路分割的干扰.根据图像预处理之后道路信息分布的特点,将图像分为3块子区域分别用不同的算法进行检测.对于道路信息丰富,非道路信息也较多的中...     

基于改进的Mean Shift方法的高分辨率遥感影像道路提取

遥感影像的道路提取长期以来一直是数字摄影测量未能解决的难题之一。本文在探讨了均值漂移、区域分割、边缘检测、轮廓跟踪的基础上,提出一种基于均值漂移和利用统计面积去除和合并小区域的道路提取算法,并采用数学形态学方法消除错误道路,利用轮廓跟踪法获取道路的边缘,实现道路的提取;通过与基于区域分割、边缘检测算法提取结果对比,结果表明,本文的算法进行道路提取的效果更好。     

融合纹理和形状特征的高分辨率遥感影像道路提取

提出一种结合纹理和形状特征提取道路信息的方法。首先利用灰度共生矩阵提取纹理特征,并将其应用于最大似然分类中提取面状道路,然后利用形态学方法分割道路与其相连地物,最后利用提出的3个形状指数(凹度、精密度、偏心角)有效地识别和区分了道路与非道路地物,并最终实现了提纯道路的目的。实验结果证明,该方法可以准确地提取主干道路网,剔除非道路地物的影响。