共查询到19条相似文献,搜索用时 500 毫秒
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为体现出行者路径选择行为,准确评价路网行程时间可靠性,采用行程时间均值和行程时间均方差的加权和定义广义出行费用,以不同的加权系数反映出行者对待风险的态度。从路段层面定义行程时间可靠性,以广义出行费用最小化为目标构建SUE模型,建立基于广义出行费用的路网行程时间可靠性模型。结合模型特点,给出Monte Carlo仿真和交通规划模型相结合的求解算法。并在一个小型测试路网上进行了验证,结果表明:出行者对待风险的不同态度对行程时间可靠性具有明显的影响,保守型出行者将使路网行程时间可靠性有所提高;所建分配模型能够较真实地反映出行者的路径选择行为,使行程时间可靠性分析更加准确。 相似文献
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为了提高出行者的路径选择效率,从微观层面对随机动态路网条件下的单车辆路径选择问题进行深入研究。随机动态路网条件下,作为车辆路径构成单元的路段,不同时刻车辆在其上的行程时间具有明显的动态变化特征,若使用传统的最短路算法进行车辆路径选择,将某一时点的路段行程时间作为路段权值不能反映路段行程时间动态变化产生的影响,车辆路径选择结果容易造成误判。为解决此问题,按照集散波理论对于路段车辆运行状态的划分方式,首先以路段下游信号转换时刻目标车辆与排队车流队尾的相对位置关系为切入点,对路段行程时间进行分状态分类随机动态预测,然后建立对应可接受水平下的路段行程时间可靠性计算模型,最终分别针对简单网络和复杂网络的单车辆路径选择问题提出使用行程时间可靠性作为关键控制变量的三阶段车辆路径选择模型和权值异化的Dijkstra车辆路径选择算法。通过案例及对比分析表明,在出行者面临的简单网络中使用行程时间可靠性进行车辆路径选择可纠正仅仅按照单一行程时间进行车辆路径选择造成的选择误判,在复杂网络中使用行程时间可靠性作为路段权值异化的Dijkstra算法可迅速求出最可靠路径,有效解决了随机动态路网环境下的单车辆路径选择问题,是对路径选择问题研究的深入拓展。 相似文献
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供需不确定条件下的预算-超额用户平衡模型 总被引:1,自引:0,他引:1
为更加全面、准确反映随机路网中出行者规避风险的择路行为,以预算-超额行程时间作为出行者选择路径的依据,提出了一种供应及需求不确定条件下同时考虑可靠性和不可靠性的交通分配模型——预算-超额用户平衡模型,推导了需求服从Gamma分布、路段通行能力服从均匀分布条件下预算-超额行程时间的解析表达式,并以此为基础建立起用等价变分不等式表示的平衡模型。利用一个小型测试网络比较了用户平衡模型、基于可靠性的用户平衡模型以及预算-超额用户平衡模型的性能。研究结果表明:提出的模型是有效、可行的;其平衡流量模式不同于用户平衡模型和基于可靠性的用户平衡模型;随着需求水平、可靠度以及路段通行能力退化程度的增加,预算-超额行程时间随之增加。 相似文献
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目前对于交通网络上交通阻抗的选取一般选用时间、距离、费用等因素,其最优路径通常为最小阻抗路径。随着城市交通变得日益拥挤及影响出行因素的不可靠的增加,行程时间可靠性成为人们选择出行路径的一个重要影响因素。文中考虑这个因素,建立了行程时间可靠性函数,并对其进行变形处理,提出了行程时间可靠性费用的概念,将其作为路阻函数,将求解最大可靠性路径问题转化为求解最小行程时间可靠性费用问题,使路阻不但考虑了交通阻抗中最关键的因素即出行时间,又考虑了出行时间的不稳定性,更符合实际路网中出行者对于出行路径的选择行为,还能作为路阻费用在交通规划软件中方便使用;最后将该方法用于交通影响评价中交通影响范围的确定,并在TransCAD中进行了实现,将其结果与基于时间确定的交通影响范围进行比较,证明了该方法的可行性及实际应用价值。 相似文献
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为了研究在不确定性交通环境下路径选择问题,引入前景理论建立动态路径选择模型以规避出行风险,保障出行者准时稳定地到达目的地。首先介绍了前景理论,计算了以行程时间为指标路径前景值和在给定的预算时间内确定路径准时到达可靠度。考虑到绝大多数出行者属于风险规避型,定义可靠度最高的路径为基准路径,将二阶随机占优于基准路径的路径归入有效集。最后定义了延误风险,以有效集中延误风险最低的路径作为可接受的最优路径。通过一个简单测试网络算例,研究了考虑风险规避的动态路径选择,并分析了对路径选择的影响。研究结果分析显示,当考虑风险规避时,出行者不再以单一的期望行程时间为最优目标,而会综合考虑出行选择。 相似文献
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信息诱导是缓解交通拥挤的有效途径,为了描述道路拥挤程度对出行者路径选择决策的影响机理,基于累积前景理论分析了出行者的出行决策过程,分析了出行者拥挤认知模式以及不同出行方式的拥挤信息需求。解析了拥挤阈值的概念,将行程时间作为累积前景理论决策指标建立了拥挤阈值的计算模型,以1个简单路网进行算例分析,模拟驾驶员的拥挤认知及出行活动决策。算例结果揭示了拥挤阈值对路径选择决策行为的影响,同时验证了拥挤阈值是出行者在决策过程中的决策变化分界点。出行时间在拥挤阈值内出行者不改变出行路径;出行时间超过拥挤阈值,出行者将改变出行路径。 相似文献
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为了给出行者提供更准确的候选路径的行程时间可靠度,并克服缺乏完整观测样本的局限,介绍了一种符合对数正态分布假设和基于路段行程时间变异系数的路径行程时间可靠度评价方法,并解析了早到指数和迟到指数这2个符合概率特征的新指标.分别在仿真的城市信号灯路网和乌鲁木齐市内环快速路开展实证研究,验证该方法在城市道路上的路径行程时间可靠度估计的适应性.仿真结果证明,应用乌鲁木齐市少量浮动车数据的估计结果显示该方法简单实用,但是评价结果对各路段之间行程时间方差的差异程度较敏感,该方法易于夸大城市信控道路上的路径行程时间的不确定性. 相似文献
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出行者的路径选择行为是包括自身特性在内多种因素共同作用的结果。为分析出行者偏好对路径选择行为的影响,首先假设出行者从路网中获取的信息为不完全历史信息,建立了理解行程时间及其更新模型,然后给出了基于经验-加权吸引力(EWA)学习模型和累计强化学习模型的两种偏好动态更新规则,最后通过Dogit模型将理解行程时间和路径偏好共同纳入出行者的路径选择决策中。在此基础上,对比分析了不考虑路径偏好、路径偏好为固定值、基于EWA学习模型更新路径偏好和基于累计强化学习模型更新路径偏好4种不同偏好情况下网络交通流的演化情况。算例结果表明:相比利用Logit模型不考虑路径偏好的流量分配结果,利用Dogit模型考虑路径偏好的流量分配结果更为均衡,且在考虑偏好时,路径偏好为固定值、基于EWA学习模型更新路径偏好和基于累计强化学习模型更新路径偏好3种情况下路径的均衡流量间差异较小;偏好动态更新时,基于EWA学习模型的路径偏好动态更新规则较累计强化学习模型能更好地捕捉出行个体的路径偏好,但由累计强化学习模型得到的路网流量分配结果更为均衡;偏好为固定值时,路径的均衡流量介于EWA学习模型和累计强化学习模型两种偏好动态更新规则下路径的均衡流量之间。 相似文献
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出行者(特指私家车出行者)路径选择行为的研究对于城市的交通管理和交通组织都有着重要的意义,而且随着交通出行费用的不断增加,以及道路拥挤收费政策逐步实施,仅仅考虑距离最短、时间最短来对出行者路径选择行为模型进行研究,往往实用性欠佳。针对以往的研究中考虑因素单一、模型实用性不强这一问题,运用能有效描述出行者不确定性条件下决策行为的前景理论,综合考虑出行者的出行时间、出行费用以及出行者的个人偏好、出行经验等因素,建立一个更为贴合实际的出行者路径选择行为模型。以实际算例的形式对比分析了,不同收费标准对不同出行者人群、不同性质出行的路径选择行为的影响程度。结果表明:与拥挤收费政策实施前相比,收费3元时,高收入水平出行者购物出行时的路径发生变化,而对于通勤出行,当收费大于6元时出行路径才发生变化;对于中低收入水平出行者来说,因为其较高收入者对费用更为敏感,所以拥挤收费政策实施后他们的反应也不尽相同。 相似文献
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Recent studies have confirmed that travelers consider travel time reliability in addition to average travel time when making route choice decisions. In this study, we develop a bi-objective routing model that seeks to simultaneously optimize the average travel time and travel time reliability. The semi-standard deviation (SSD) is chosen as the reliability measure because it reflects travelers' concerns over longer travel time better than the commonly used standard deviation. The Pareto-optimal solutions to the bi-objective model are found by using an improved strength Pareto evolutionary algorithm. Tests on a real-world urban network with field measured travel time data have demonstrated good performance of the algorithm in the aspects, such as computational efficiency, quick convergence, and closeness to the global Pareto-optimal. Overall, the bi-objective routing model generates reasonable path recommendations. The SSD-based model is sensitive to the asymmetry of travel time distribution and tends to avoid paths with excessively long delays. This would be particularly helpful to those users placing high values on travel time reliability. 相似文献
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先进的旅行者信息系统对出行者选择行为的影响研究 总被引:11,自引:1,他引:11
目前研究先进的旅行者信息系统对出行者选择行为的影响主要集中在对路径选择行为的影响上,而忽略了对出行者出行终点和交通方式选择的影响。假定路网中的出行者一部分装有信息装置,另一部分没有装信息装置,利用离散选择理论中的层次选择结构模型和交通规划理论中的随机均衡方法,研究了先进的旅行者信息系统对出行者终点选择,方式分担和路径选择行为的综合影响,建立了一个与网络均衡条件等价的数学规划模型,设计了模型的求解算法,并用一算例分析了市场渗透率和信息质量对出行者选择行为的影响。 相似文献
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The decision making of travelers for route choice and departure time choice depends on the expected travel time and its reliability. A common understanding of reliability is that it is related to several statistical properties of the travel time distribution, especially to the standard deviation of the travel time and also to the skewness. For an important corridor in Changsha (P.R. China) the travel time reliability has been evaluated and a linear model is proposed for the relationship between travel time, standard deviation, skewness, and some other traffic characteristics. Statistical analysis is done for both simulation data from a delay distribution model and for real life data from automated number plate recognition (ANPR) cameras. ANPR data give unbiased travel time data, which is more representative than probe vehicles. The relationship between the mean travel time and its standard deviation is verified with an analytical model for travel time distributions as well as with the ANPR travel times. Average travel time and the standard deviation are linearly correlated for single links as well as corridors. Other influence factors are related to skewness and travel time standard deviations, such as vehicle density and degree of saturation. Skewness appears to be less well to explain from traffic characteristics than the standard deviation is. 相似文献
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ABSTRACTConventional travel time reliability assessment has evolved from road segments to the route level. However, a connection between origin and destination usually consists of multiple routes, thereby providing the option to choose. Having alternatives can compensate for the deterioration of a single route; therefore, this study assesses the reliability and quality of the aggregate of the route set of an origin-destination (OD) pair. This paper proposes two aggregation methods for analyzing the reliability of travel times on the OD level: 1) an adapted Logsum method and 2) a route choice model. The first method analyzes reliability from a network perspective and the second method is based on the reliability as perceived by a traveler choosing his route from the available alternatives. A case study using detailed data on actual travel times illustrates both methods and shows the impact of having variable departure times and the impact of information strategies on travel time reliability. 相似文献
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Under a stochastic roadway, drivers need a route guidance system incorporating travel time variability. To recommend a customized path depending on the trip purpose and the driver’s risk-taking behavior, various path ranking methods have been developed. Unlike those methods, our proposed disutility method can easily incorporate a target arrival time in the ranking process by measuring how late the travel is and by penalizing it depending on the severity of lateness. In addition, the disutility-based route guidance system can properly address travel time unreliability that causes unacceptable disruptions to the driver’s schedule (i.e., unexpected long delay). We compare the disutility-based path ranking method with other ranking methods, the percentile travel time, the mean excess travel time, and the on-time arrival probability. We show that the disutility has stronger discriminating power and requires less solution space to find an optimal path. The most important advantage is that it can estimate a driver’s risk-taking behavior for each trip purpose by using the discrete choice analysis. We construct a simulation framework to acquire the travel time data on a hypothetical roadway. We analyze the data and show how various ranking methods recommend a customized path. Using the data, we show the advantage of the disutiltiy method over the other methods, which is generating a customized path with respect to the target arrival time by properly penalizing the travel time lateness. 相似文献
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Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability. 相似文献