城市居民出行特性比较分析

在综合分析国内外城市的社会经济发展和居民出行调查资料的基础上,从居民人均出行次数、出行目的分布和出行方式构成等3个方面入手,将国内城市居民出行特征与发达国家城市进行分析比较,又对国内相同城市不同时期的调查结果进行对比研究,目的在于把握城市居民出行特性的发展变化趋势。研究结果发现,我国城市居民出行特征随着社会经济和城市的发展发生了显著的变化,国内经济比较发达地区大城市的部分出行特征已经开始与发达国家状况相似,中小城市和欠发达地区城市的出行特征则与国外差别较大。研究同时发现了国内城市居民出行结构中的隐患,指出了发展的方向。     

基于出行生成约束模型的交通需求预测方法研究

针对传统城市交通需求预测方法在解决交通供需平衡关系的缺陷,文章结合OD反推技术建立了交通出行生成约束模型,在西安曲江新区综合交通规划中的应用实例表明,模型可对城市交通需求预测中的路段交通量、机动车拥有量、停车需求进行合理预测,可改善城市交通供需平衡等问题.     

Multimode trip information detection using personal trajectory data

Handheld global positioning system (GPS) devices can serve as a new tool to collect an individual's trip information with advantages of low cost, accurate data, and intensive spatial coverage. Various machine learning algorithms have been explored to detected trip train information in previous studies; however, few of them focused on the evaluation and comparison of the performance and applicability of different models. Meanwhile, according to previous studies, car and bus mode detection is a thorny issue due to their similar travel characteristics, and algorithms still need to be well explored and improved to solve this problem. In this article, an innovative method is proposed to detect trip information, including trip modes, mode-changing time and location, and other attributes, from personal trajectory data. The method is a two-step process. A machine learning algorith-based module (including artificial neural network, support vector machine, random forests, and Bayesian network) is firstly used to identify walk, bicycle, and motorized trip modes (bus or car); we thoroughly compared the performance of these four algorithms. Then a second module, using critical points on the GPS trajectories, is further developed to distinguish car and bus mode, incorporated with GIS map information. Field test results show that the proposed machine learning models can all be applied for walk, bicycle, and motorized mode detection with high detection rates exceeding 90%; however, the algorithms work relatively poorly for bus and car mode detection, with results mostly below 75%. The proposed two-step method can greatly improve bus and car mode detection accuracy by 14–30%. As a result, the average mode detection rates for all the four modes are above 90%. Compared with mode detection results by using only the machine learning algorithm, the proposed two-step method has much better performance in both accuracy and consistency.     

组团式城市居民出行特征变化趋势分析

随着全国城市化率的不断提高,城市空间布局由单中心集聚逐渐向多中心组团式发展,从而居民出行特征也发生了相应的变化。本文通过应用纵向和横向对比研究方法来更准确把握组团城市居民出行特性的发展变化趋势。首先对国内石家庄市在2000和2007年不同时期的居民出行特征进行纵向比较分析,其次又对石家庄和广州两个组团城市居民出行特征作横向比较分析,从而看出组团式城市的居民出行特征指标随着城市规模、布局的变化而变化,并呈现出一定的规律性。相应的结论有助于城市综合交通规划的设计和研究,并且对同类城市起到借鉴意义。     

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节假日出行活动与日常出行活动差别较大,从而节假日交通与平日交通相比呈现出明显的不同于平日的特征和规律。本文通过北京市黄金周出行问卷调查结果,构建节假日出行的活动模式,采用交叉列联分析方法探讨节假日活动模式与个人属性相关性,分析个人属性中的性别、职业、年龄、是否拥有小汽车、受教育程度的不同所引起的个体活动模式的差异,并对比个人属性对节假日出行和日常出行典型活动模式选择影响的差异。得出个人属性与节假日出行典型活动模式选择的相关性和各属性下的显著影响活动模式,为节假日交通对策的制定提供给出依据。     

出行距离分布模型及参数研究

为研究城市交通规划中出行距离的分布特征,在一定假设条件下,运用概率统计理论推导出行距离的概率分布函数形式,用10座城市的居民出行资料对其进行拟合,验证了该假设条件的合理性,分析了函数参数的相关影响因素,如城市规模、城市形状和交通结构等,对其进行量化与非线性回归,得到出行距离的概率分布函数的一般形式,最后,就不同规模城市分析了分布函数参数的取值范围。研究结果表明:出行距离的分布符合瑞利分布,特大城市和大中城市分布函数参数的取值范围分别为0.035～0.076和0.042～0.100。     

Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips

This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data, here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk (23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially families with children. An environment that attracts people’s interest and provides activity opportunities encourages people to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts encouraging the use of non-automobile alternatives.

快速公交（BRT）线路布局优化研究

为探讨现有公共交通线网结构下BRT线路布设优化问题,对快速公交线路布设的内部条件和外部条件进行了分析;在此基础上依据快速公交的发展特点,以乘客总出行时耗最小和车公里成本投入最小为目标,建立了快速公交布局优化的模型,并且给出了优化目标和相应约束条件的函数表达式。通过事例分析对BRT线路布设优化算法进行说明,从而得知优化模型具有较高的应用价值。     

基于居民出行特征分析的常熟市交通发展对策研究

居民出行调查是城市交通规划、建设和管理的基础依据。通过对常熟市2007年居民出行调查的有关数据的深入分析,总结归纳出常熟市城市居民出行的规律、变化特征及其原因,并针对其出行特性,提出常熟市未来交通发展的对策和建议,具有一定的理论价值和实际意义。     

不同出行距离的客货运量分布研究

根据客货出行的随机性以及组成理论中的最复杂原理,可推导出客货出行距离的概率分布,得出客货出行的规律,从而为交通规划以及运输规划提供依据,同时也为客货出行特性的研究提供新的思路。