山地城市居民出行特征分析

在归纳山地城市形态和道路网结构特征的基础上,根据2010年攀枝花市居民出行调查数据,对攀枝花市居民出行方式、出行时耗、出行时空分布等特征进行了分析,发现城市形态与路网结构对于居民出行特征有着重要影响.     

A hybrid machine learning model for short-term estimated time of arrival prediction in terminal manoeuvring area

4D trajectory prediction is the core element of future air transportation system, which is intended to improve the operational ability and the predictability of air traffic. In this paper, we introduce a novel hybrid model to address the short-term trajectory prediction problem in Terminal Manoeuvring Area (TMA) by application of machine learning methods. The proposed model consists of two parts: clustering-based preprocessing and Multi-Cells Neural Network (MCNN)-based prediction. Firstly, in the preprocessing part, after data cleaning, filtering and data re-sampling, we applied principal Component Analysis (PCA) to reduce the dimension of trajectory vector variable. Then, the trajectories are clustered into several patterns by clustering algorithm. Using nested cross validation, MCNN model is trained to find out the appropriate prediction model of Estimated Time of Arrival (ETA) for each individual cluster cell. Finally, the predicted ETA for each new flight is generated in different cluster cells classified by decision trees. To assess the performance of MCNN model, the Multiple Linear Regression (MLR) model is proposed as the comparison learning model, and K-means++ and DBSCAN are proposed as two comparison clustering models in preprocessing part. With real 4D trajectory data in Beijing TMA, experimental results demonstrate that our proposed model MCNN with DBSCAN in preprocessing is the most effective and robust hybrid machine learning model, both in trajectory clustering and short-term 4D trajectory prediction. In addition, it can make an accurate trajectory prediction in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) with regards to comparison models.     

Experimental and numerical investigations on laser-welded corrugated-core sandwich panels subjected to air blast loading

Experimental investigations on the laser-welded triangular corrugated core sandwich panels and equivalent solid plates subjected to air blast loading are presented. The experiments were conducted in an explosion tank considering three levels of blast loading. Results show that the maximum deflection, core web buckling and core compaction increased as the decrease of stand-off distance. Back face deflections of sandwich panels were found to be nearly half that of equivalent solid plates at the stand-off distances of 100 mm and 150 mm. At the closest stand-off distance of 50 mm, the panel was found to fracture and fail catastrophically. Autodyn-based numerical simulations were conducted to investigate the dynamic response of sandwich panels. A good agreement was observed between the numerical calculations and experimental results. The model captured most of the deformation/failure modes of panels. Finally, the effects of face sheet thickness and core web thickness on the dynamic response of sandwich panel were discussed.     

基于手机信令数据的城市通勤出行特征研究

通勤交通出行特征是研究城市交通规划的重要数据基础,如何有效提取通勤出行特征成为研究城市居民通勤出行的关键。文章通过分析手机信令数据特性和通勤出行特征,利用手机信令数据挖掘的相关技术,建立通勤出行特征提取模型并进行实例研究,与传统的居民出行调查分析进行对比,验证利用手机信令数据进行通勤出行特征研究的可行性。     

黑龙江省新农村建设金融有效供给分析

新农村建设离不开资金的投入。银行、财政的扶持有限,农民自我积累较弱等原因导致黑龙江省新农村建设所需的物力、人力、技术、信息等资源配置的不充分和不合理。因此,要充分发挥农村金融的筹资融资、调节经济和资源配置功能。但农村金融体系不完善、业务种类单一、信用环境缺失等因素制约着金融对农业的有效供给。因此,应加快推进农村金融体制改革,完善农村金融体系,创新金融服务,促进黑龙江省新农村建设。     

Freeway path travel time prediction based on heterogeneous traffic data through nonparametric model

Providing reliable travel time prediction is very much needed for commuters for their upcoming trips to reduce travel time and relieve traffic congestion. This article proposes an integrated model for path and multi-step-ahead travel time prediction on freeways using both historical and real-time heterogeneous traffic and weather data. The model's performance is investigated in a case study under various traffic scenarios. Results indicate that the proposed model provides satisfactory prediction results in various performance tests. For practical purposes, general guidelines for selecting the model's parameter sets as well as the efficient size of historical data are also presented.     

小汽车与轨道交通出行方式选择行为分析

研究出行方式选择行为有助于引导私人小汽车出行者改乘轨道交通出行。以上海世博期间驾驶人的通勤出行为研究对象,通过RP和SP调查采集驾驶人实际通勤出行情况和世博期间的出行方式选择行为,得到小汽车相比轨道交通的出行时间节省量和费用差与是否选择轨道交通存在联系。应用离散选择模型分析出行方式选择的影响因素,建立二项Logit模型。结果表明,驾龄较短和低收入的驾驶人更愿意选择轨道交通,年轻驾驶人（相比年长者）、频繁使用小汽车者更愿意选择小汽车出行。     

The opening of the Amsterdam Ring Road

This paper presents the results of a major before-and-after study carried out to establish the short term effects of the removal of a severe bottleneck in the road network around Amsterdam. An important focus in the study was on measuring changes in the timing of travel, as well as changes in route choice, mode choice, destination choice and frequency of travel. The results of the study indicated that, in the short run, there was little or no change in mode choice, nor was there significant emergence of new induced trips. On the other hand, large shifts in time of travel as well as route choice were reported, emphasising the importance of alterations to the timing and routes of existing trips when congestion is relieved, and the need to consider the benefits these bring in evaluating the impact of any road investment.     

Effects of Friends' Information Interaction on Travel Decisions

Many existing studies focus on the effects of traffic information from ATIS on travel choices. Research on the effect of friends' travel information on people's travel choice is uncommon, yet needed. In this paper, behavioral experiments are conducted to discuss what the effects of information interaction with friends can bring on individual travel decision behavior. The experimental results concluded that when the rate of friends' information interaction reaches 33.3%, the whole system is at an optimal level. Furthermore, users reach an optimum when the rate of friends' travel information interaction is 75%. The average time and cost per person is increasing when the whole system optimum transfers to the user optimum. Moreover, adjustments of departure time at the system optimum are more dispersed than at the user optimum, while travel choice changes are more concentrated.