基于出行决策分析的发车频率计算

出行时间过长是公交出行率偏低的重要原因之一,而出行时间与公交线路发车频率密切相关,有必要研究发车频率对居民出行决策的影响。基于居民出行调查数据,分析出行决策影响因素,利用随机效用理论,建立选择方案为自行车与公交的BL模型,并在MATLAB环境下采用Newton．Raphson法编程求解,预测出行时间对公交出行率的影响;进而分析发车频率对公交出行时间的影响,最终得到公交出行率与发车频率的对应关系,由此计算给定公交出行率下的发车频率。文中通过计算实例说明该方法在计算发车频率及评价公交运营调度方案优劣上具有实用价值。     

私家车出行者ATIS信息选择影响因素研究——以大连市为例

私家车出行者对ATIS信息的选择意愿受到多种因素的影响。开展大连市私家车出行者ATIS信息需求意向调查,以探索性因子分析和累积Logit模型理论为基础,对ATIS信息内容进行分类,同时引入出行者性别、年龄、收入水平、交通补助情况等特性变量,建立私家车出行者ATIS信息选择模型。模型标定结果显示,私家车出行者个人特征与ATIS信息特性对ATIS信息选择意愿存在不同程度的影响：私家车出行者主要关注与出行质量相关的信息,收入水平、交通补助、驾照保有情况等对私家车出行者ATIS信息选择意愿影响显著。     

停车诱导系统的诱导效果分析

介绍了诱导后即有完整停车信息下的多项logit停车选择模型,其中共有4个停车场属性的影响因素;构建了诱导前即无停车信息下的停车选择模型,包括停车寻泊路径选择的logit概率模型和把不确定信息下转化为不完美信息的停车场选择方法。在此基础上对一个算例进行了模拟分析,得到了诱导前和诱导后各路段上的车辆数、各停车场的车位利用率以及排队等待入库的车辆数。     

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为了定量地研究大型枢纽机场的地面交通组织系统，首先阐明了单独研究机场可达性的意义，提出了使用通达成本来描述机场可达性的新的方法，从而用化为货币形式的成本来衡量可达性。主要从快捷性，经济性和舒适性三方面来计算成本。为了量化抽象的舒适性，提出了通过“旅行者的疲劳恢复时间”来间接转化的方法。最后按照人群，地区的划分计算总通达成本加权平均。在数据的处理上，提出了使用Logit模型对两个重要参数进行标定和校正。最后，给出了几个简化算例，重点对上海浦东国际机场进行了可达性评价，然后简要地将其与其他两个国际机场进行了横向比较。结果表明：舒适性是一项不可忽略的可达性衡量指标。我国机场的可达性较国外有待提高。     

An exploration of the relationships between socioeconomics,land use and daily trip chain pattern among low-income residents

Daily trip chain complexity and type choices of low-income residents are examined based on activity travel diary survey data in Nanjing, China. Statistical tests reveal that non-work trip chain complexity is distinctly distinct between low-income residents and non-low-income residents. Low-income residents are inclined to make simple non-work chains. Two types of econometric models, a stereotype logit model and mixed logit model, are then developed to investigate the possible explanatory variables affecting their trip pattern. The number of stops within a chain and chain types are considered as dependent variables, while independent variables include household and personal characteristics as well as land use variables. Results show that once convenient and flexible conditions are supplied, low-income residents are more likely to make multiple activities in a trip chain. Areas with high population and employment densities are associated with complex work trip chains and more non-work activity involvement.     

An improved Dial's algorithm for logit-based traffic assignment within a directed acyclic network

Abstract

Dial's algorithm is one of the most effective and popular procedures for a logit-type stochastic traffic assignment, as it does not require path enumeration over a network. However, a fundamental problem associated with the algorithm is its simple definition of ‘efficient paths’, which sometimes produces unrealistic flow patterns. In this paper, an improved algorithm based on the route extension coefficient is proposed in order to circumvent this problem, in which ‘efficient paths’ simultaneously consider link travel cost and minimum travel cost. Path enumeration is still not required and a similar computing efficiency with the original algorithm is guaranteed. A limitation of the algorithm is that it can only be applied to a directed acyclic network because a topological sorting algorithm is used to decide the order of the sequential calculation. A numerical example based on the Beijing subway network illustrates the effectiveness of the proposed algorithm. It is found that it is able to exclude most unrealistic paths, but include all reasonable paths when compared with path enumeration and the original Dial's algorithm.     

Have tropical marine protected areas worked? An initial analysis of their success

A multinomial choice framework was used to analyze data from hypothetical storm forecast scenarios administered via mail survey to a random sample of U.S. Gulf Coast residents. Results indicate that the issuance of a mandatory evacuation notice and the presence of higher wind speeds had the largest influence on increasing the likelihood of evacuation. Age, race, disability, distance, and education were significant in explaining one's decision to wait relative to choosing to evacuate. Blacks and disabled individuals were strictly less likely to wait and more likely to make an immediate evacuation decision. Hurricane Katrina evacuees and those with an evacuation destination identified were also more likely to decide to evacuate, but were also more likely to wait before deciding. Results indicate that residents of mobile homes were more likely to either evacuate or wait before making a decision, but strictly less likely not to evacuate. Respondents very confident in being rescued were strictly more likely not to evacuate. Results indicate that not having an evacuation destination identified was the most influential factor regarding the likelihood of not knowing what choice to make.     

An analysis of bicycle route choice preferences in Texas,US

In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling). The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities, (4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics. The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs, red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle facility on the route.

Specification of the cross-nested logit model with sampling of alternatives for route choice models

We present an operational estimation procedure for the estimation of route choice multivariate extreme value (MEV) models based on sampling of alternatives. The procedure builds on the state-of-the-art literature, and in particular on recent methodological developments proposed by Flötteröd and Bierlaire (2013) and Guevara and Ben-Akiva (2013b). Case studies on both synthetic data and a real network demonstrate that the new method is valid and practical.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.