Modeling the effects of traveler information on freeway origin–destination demand prediction

The primary focus of this research is to develop an approach to capture the effect of travel time information on travelers’ route switching behavior in real-time, based on on-line traffic surveillance data. It also presents a freeway Origin–Destination demand prediction algorithm using an adaptive Kalman Filtering technique, where the effect of travel time information on users’ route diversion behavior has been explicitly modeled using a dynamic, aggregate, route diversion model. The inherent dynamic nature of the traffic flow characteristics is captured using a Kalman Filter modeling framework. Changes in drivers’ perceptions, as well as other randomness in the route diversion behavior, have been modeled using an adaptive, aggregate, dynamic linear model where the model parameters are updated on-line using a Bayesian updating approach. The impact of route diversion on freeway Origin–Destination demands has been integrated in the estimation framework. The proposed methodology is evaluated using data obtained from a microscopic traffic simulator, INTEGRATION. Experimental results on a freeway corridor in northwest Indiana establish that significant improvement in Origin–Destination demand prediction can be achieved by explicitly accounting for route diversion behavior.     

多模式路径流量估计模型与算法

为了通过路段检测交通流量计算拥挤条件下多种交通模式需求, 提出了一个随机用户平衡条件下的多模式路径流量估计模型, 并给出了相应模型的增广拉格朗日乘子算法, 算法将模型中的路段容量、观测路段流量平衡与估计需求的范围等约束条件转化为相应的惩罚函数项, 并将原先的有约束优化流量估计模型转化为一个无约束优化模型, 最后应用一个简单的投影迭代算法求解无约束优化模型。仿真结果表明: 先验需求误差对模型的需求估计结果有重要影响, 误差越小估计结果越准确, 而先验需求误差对路段流量估计结果几乎没有影响, 因此, 模型和算法简单可用。     

集装箱航运市场运力供需与运价分析模型

根据船舶集装箱运输生产的航速和箱位两个要素, 定义了以每天每箱位投入燃油数和箱位数为自变量的航运生产函数; 推导出集装箱航运市场供方根据需求的变化而调整产量的扩张路径; 推导出供方短期单位总成本, 并求出边际成本曲线, 即供应函数。结果表明, 在大范围内, 边际成本对需求相对较不敏感, 运价相对稳定, 但当船队已完全利用, 边际成本及船东要求的运价上升很快。     

基于GPS数据的出租车出行需求预测研究

近年来“网约车”数量越来越多,“网约车”等待时间长与载客热区需求大等问题也逐步显现,乘车体验亟需改善。在成都市出租车GPS数据的基础上,研究出租车出行分布规律,划分工作日为早、晚、夜高峰相关时段,引入k-距离曲线改进DBSCAN空间聚类算法,对出租车上下客点进行聚类分析,并用数据挖掘得出载客热区。采用BP神经网络预测载客热区的出行需求,预测结果表明,早高峰时段BP神经网络模型的MAPE分别较随机森林模型、岭回归模型提高了3.25%和5.87%,晚高峰时段提高了2.98%和4.32%、夜高峰时段提高了1.44%和2.58%,验证了BP神经网络在出租车需求预测方面的可行性。

     

中国第三方物流的市场潜力及其开发策略

简要分析了中国传统物流业所处的困境及其原因, 指出提高服务质量、挖掘市场潜力才是摆脱困境的最根本途径; 根据调查所得数据, 对潜在需求的规模、没有走向市场的原因、第三方物流企业的目标市场以及市场需求的服务内容等进行了较深入的探讨, 并据此提出了第三方物流企业开发市场的基本策略     

需求响应机制下轨道交通出行预约与列车运行计划优化方法

轨道交通供给侧的计划性与需求侧的时变性相互冲突,为更好地协同供需双方,提出了需求响应机制下城市轨道交通列车运行计划的优化方法,包括出行预约和需求响应2个环节;建立了需求响应与列车运行计划协同优化模型,以最小化乘客出行成本和列车运行成本为目标,重点关注乘客由于预约行为产生的延误时间成本;考虑列车运行、运输能力、编组情况、客流分布等因素,设计了基于乘客优先级的自适应大规模邻域搜索算法,外层优化列车运行计划,内层优化客流分配方案,最终实现客流的供需匹配;以北京地铁八通线为例,按照需求响应机制对该线路全天的需求处理与运输组织进行数值试验,并对试验结果从车底运用、乘客等待时间和满载率分布三方面进行分析。研究结果表明：该优化方法可使开行的列车数降低13.8%,同时采用多编组模式,使用车辆数减少了29.8%,这能够有效压缩列车走行公里数,削减企业开支;能够在保证乘客基本出行的前提下,最高可将乘客平均在站等待时间缩短约35.3%,并且预约比例的提升对等待时间的削减效果明显;优化后的运行计划能控制列车满载率维持在设定水平,有效降低人员密度,避免人群大规模聚集,对城市轨道交通疫情的有效防控做出有益探索。     

Deciding whether and how to improve statewide travel demand models based on transportation planning application needs

Many states in the USA have developed statewide travel demand models for transportation planning at the state level and along intercity corridors. Travel demand models at mega-region and provincial levels are also widely used in Europe and Asia. With modern transportation planning applications requiring enhanced model capabilities, many states are considering improving their four-step statewide demand models. This paper synthesizes representative statewide models developed with traditional four-step, advanced four-step, and integrated micro-simulation methods. The focus of this synthesis study is as much on model applications and data requirements as on modeling methods. An incremental model improvement approach toward advanced statewide models is recommended. Review findings also suggest model improvement activities should be justified by planning application needs. For statewide model improvement plans to be successful and financially sustainable, the return on model improvement investment needs to be demonstrated by timely applications that rely on improved model capabilities.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

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随着社会经济的快速发展，北京市居民出行需求日益增长,机动车辆拥有量也随之迅猛上升。北京市1986年和2000年的居民出行调查结果表明，在过去的15年内，居民交通出行模式发生了变化，公交出行比例比原来略有减少，主要的变化是原来的自行车出行这部分中，有很大一部分转变为机动车出行。本文通过对类似规模的几个国际大都市交通出行结构演变过程的回顾，找出其关键之处在于采用政策策略促使居民出行选择有利于城市可持续发展模式；根据广泛调查和专家资讯，确定了一个北京城市交通出行各种方式的合理比例，作为发展目标；并参考发达国家和一些快速发展的国家和城市的经验，提出了达到这个目标的对策和策略。