The role of alternative fuel vehicles: Using behavioral and sensor data to model hierarchies in travel

Greater adoption and use of alternative fuel vehicles (AFVs) can be environmentally beneficial and reduce dependence on gasoline. The use of AFVs vis-à-vis conventional gasoline vehicles is not well understood, especially when it comes to travel choices and short-term driving decisions. Using data that contains a sufficiently large number of early AFV adopters (who have overcome obstacles to adoption), this study explores differences in use of AFVs and conventional gasoline vehicles (and hybrid vehicles). The study analyzes large-scale behavioral data integrated with sensor data from global positioning system devices, representing advances in large-scale data analytics. Specifically, it makes sense of data containing 54,043,889 s of speed observations, and 65,652 trips made by 2908 drivers in 5 regions of California. The study answers important research questions about AFV use patterns (e.g., trip frequency and daily vehicle miles traveled) and driving practices. Driving volatility, as one measure of driving practice, is used as a key metric in this study to capture acceleration, and vehicular jerk decisions that exceed certain thresholds during a trip. The results show that AFVs cannot be viewed as monolithic; there are important differences within AFV use, i.e., between plug-in hybrids, battery electric, or compressed natural gas vehicles. Multi-level models are particularly appropriate for analysis, given that the data are nested, i.e., multiple trips are made by different drivers who reside in various regions. Using such models, the study also found that driving volatility varies significantly between trips, driver groups, and regions in California. Some alternative fuel vehicles are associated with calmer driving compared with conventional vehicles. The implications of the results for safety, informed consumer choices and large-scale data analytics are discussed.     

A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data

There are many systems to evaluate driving style based on smartphone sensors without enough awareness from the context. To cover this gap, we propose a new system namely CADSE system to consider the effects of traffic levels and car types on driving evaluation. CADSE system includes three subsystems to calibrate smartphone, to classify the maneuvers, and to evaluate driving styles. For each maneuver, the smartphone sensors data are gathered in three successive time intervals referred as pre-maneuver, in-maneuver, and post-maneuver times. Then, we extract some important mathematical and experimental features from these data. Afterwards, we propose an ensemble learning method on these features to classify the maneuvers. This ensemble method includes decision tree, support vector machine, multi-layer perceptron, and k-nearest neighbors. Finally, we develop a rule-based fuzzy inference system to integrate the outputs of these algorithms and to recognize dangerous and safe maneuvers. CADSE saves this result in driver’s profile to consider more for dangerous driving recognition. The experimental results show that accuracy, precision, recall, and F-measure of CADSE system are greater than 94%, 92%, 92%, and 93%, respectively that prove the system efficiency.     

快速换模在桥壳模具中的应用

在冲焊桥壳产品切换中,桥壳模具体积大、吨位重、造成换模速度慢,生产效率低。通过快速换模技术在桥壳模具中的应用,区分了内外变换操作,并采用平行作业,改善物流架起吊装置,增加定位销,使换模速度提升了50%以上,减少了不需的额外库存,提高了生产效率,并产生明显的经济效益。     

Crash prediction with behavioral and physiological features for advanced vehicle collision avoidance system

Real-time crash prediction is the key component of the Vehicle Collision Avoidance System (VCAS) and other driver assistance systems. The further improvements of predictability requires the systemic estimation of crash risks in the driver-vehicle-environment loop. Therefore, this study designed and validated a prediction method based on the supervised learning model with added behavioral and physiological features. The data samples were extracted from 130 drivers’ simulator driving, and included various features generated from synchronized recording of vehicle dynamics, distance metrics, driving behaviors, fixations and physiological measures. In order to identify the optimal configuration of proposed method, the Discriminant Analysis (DA) with different features and models (i.e. linear or quadratic) was tested to classify the crash samples and non-crash samples. The results demonstrated the significant improvements of accuracy and specificity with added visual and physiological features. The different models also showed significant effects on the characteristics of sensitivity and specificity. These results supported the effectiveness of crash prediction by quantifying drivers’ risky states as inputs. More importantly, such an approach also provides opportunities to integrate the driver state monitoring into other vehicle-mounted systems at the software level.     

高黎贡山隧道1#高地温斜井降温处理技术研究及比选

为解决高地温隧道工程中存在的作业环境差、机械设备故障多、劳动生产率低等高温热害问题,以大瑞铁路高黎贡山隧道1#长大斜井为背景，进行技术研究和降温方案比选。首先,分析热水源、监测隧道洞内外气象条件，通过加强通风措施改善人体的舒适度。其次，采用注浆封堵热水源，减少热水流量，控制施工环境的湿度和温度；采用冰块+射流风机+快热交换的处理措施，冰块吸收隧道内热量，降低局部环境温度；采用机械制冷设备进行强制降温，改善热害隧道施工环境；综合优化资源配置，采用增加作业人员和设备数量，倒班作业，缩短人员和设备作业时长等多种处理措施。最后，分析各种降温措施能够达到的施工效果。结果证明，针对以围岩、热水为主要热源的高地温隧道施工，采用“通风降温+注浆堵水+机械降温+合理施工组织”的处理方案，符合高地温隧道施工的技术要求。     

新能源汽车续驶里程焦虑及维修技术研究

续驶里程焦虑是新能源汽车售后市场抱怨最多的问题。文章从售后角度分析了导致续驶里程焦虑的原因及维修排查技术,提出了一些建议性措施。旨在为售后相关人员提供一定的理论指导,从而推动售后市场更好的发展。     

斜井盾构推进系统的栽头调整能力研究

为降低斜井掘进过程中盾构推进系统在栽头调整上存在的主观性与不确定性,从地基沉降量的角度入手,提出栽头的沉降量描述,并基于温克尔弹性地基模型,建立斜井盾构栽头的沉降量描述模型。然后结合载荷对于栽头调整的影响,进一步建立用于描述斜井盾构推进系统栽头调整能力的数学模型,并给出其上下限值的计算条件。基于栽头调整能力的数学模型,以内蒙古新街台格庙煤矿斜井工程为背景,研究隧道设计坡角变化对栽头调整能力的影响。结果表明： 1）随着下坡角度不断增大,推进系统的栽头调整能力的上下限不断下降; 2）随着下坡角度不断增大,盾构下滑力的迅速增长是造成推进系统栽头调整能力不断下降的主要原因。     

一种船舶可逆混合电力推进系统仿真研究

针对京杭大运河中运营的双燃料绿色动力船舶在低速推进运行时综合效率较低的情况,提出一种船舶双向可逆混合电力推进方案,可以有效减少机组的燃耗率和提高双燃料的替代率。设计了基于直接转矩控制方法的发电控制器和推进控制器。最后采用Simulink仿真整个系统运行,获得系统启动、加减速和平稳运行的波形,验证了系统的可行性。     

一种新结构重型汽车用平衡轴总成

由于重型自卸车承载力大且使用工况恶劣,导致整车后悬架平衡轴总成在使用过程中平衡轴断裂、平衡轴支架产生裂纹等故障频发,严重影响客户正常使用,同时使得售后维修及索赔成本增大;该文针对平衡轴总成在使用过程中的失效模式在原有技术及结构之上,设计一种新结构平衡轴总成,从而降低平衡轴故障率,最大程度的提高平衡轴使用寿命。     

盾构穿越对圆形风井结构的变形内力影响分析——以南京纬三路过江通道工程盾构穿越梅子洲风井为例

盾构进出工作井是盾构安全施工的关键。以南京市纬三路过江通道工程梅子洲圆形风井盾构穿越为研究背景,建立复杂的大型三维计算模型,对盾构穿越区域采用实体单元模拟、土弹簧释放开挖荷载的特殊模拟方法,首先对盾构破除素混凝土强度的选取进行优化分析,建议采用C15混凝土,既能减小盾构穿越施工的难度,又能保证围护结构的安全稳定;然后对盾构穿越前后风井地连墙、内衬墙和冠梁等重要围护结构的变形和内力变化规律进行了研究分析,盾构穿越前后,地连墙的变形和内力变化很大,最大增幅分别为45%和228%,内衬墙的环向弯矩和竖向最大正弯矩均存在较大变化,环向弯矩最大增幅200%,竖向弯矩最大增幅54%,冠梁的最大环向弯矩变化很大,最大增幅为1 160%。因此,工程设计时应对地连墙、内衬墙和冠梁内力较大区域加强配筋,以保证盾构安全顺利地通过。