公交站点车辆停靠问题的最优控制模型与实现技术

本文从公交站点的停靠线路数和各停靠线路的运行特征着手,以各线路车辆合理、顺序、无延误地到达站点和从站点出发为优化目标,以公交站点的最大停靠能力和满足乘客的出行要求为约束建立优化模型,以确定各线路车辆在各时段的发车频率和依次占用站点停靠的时间段,并确定其合理的运行速度.最后通过某站点的调查数据来验证模型的实用性.     

集装箱班轮到港规律的耦合性特征及其应用研究

指出了集装箱班轮运行方式下船舶到港规律具有耦合性特征,建立了耦合度表达式和相应的爱尔朗分布族模型。通过对大连港集装箱码头连续3年1.56万个班轮到港记录的统计分析,证明了同一航线同一公司编组船队内部各船舶之间在到港规律上具有很强的耦合性。     

A hybrid model based method for bus travel time estimation

Providing accurate information about bus arrival time to passengers can make the public transport system more attractive. Such information helps the passengers by reducing the uncertainty on waiting time and the associated frustrations. However, accurate estimation of bus travel time is still a challenging problem, especially under heterogeneous and lane-less traffic conditions. The accuracy of such information provided to passengers depends mainly on the estimation method used, which in turns depends on the input data used. Hence, developing suitable estimation methods and identifying the most significant/appropriate input data are important. The present study focused on these aspects of development of estimation methods that can accurately estimate travel time by using significant inputs. In order to identify significant inputs, a data mining technique, namely the k-NN classifying algorithm, was used. It is based on the similarity in pattern between the input and historic data. These identified inputs were then used in a hybrid model that combined exponential smoothing technique with recursive estimation scheme based on the Kalman Filtering (KF) technique. The optimal values of the smoothing parameter were dynamically estimated and were updated using the latest measurements available from the field. The performance of the proposed algorithm showed a clear improvement in estimation accuracy when compared with existing methods.     

An adaptive hawkes process formulation for estimating time-of-day zonal trip arrivals with location-based social networking check-in data

Location-Based Social Networking (LBSN) services, such as Foursquare, Facebook check-ins, and Geo-tagged Twitter tweets, have emerged as new secondary data sources for studying individual travel mobility patterns at a fine-grained level. However, the differences between human social behavioral and travel patterns can cause significant sampling bias for travel demand estimation. This paper presents a dynamic model to estimate time-of-day zonal trip arrival patterns. In the proposed model, the state propagation is formulated by the Hawkes process; the observation model implements LBSN sampling. The proposed model is applied to Foursquare check-in data collected from Austin, Texas in 2010 and calibrated with Origin-Destination (OD) data and time of day factor from Capital Area Metropolitan Planning Organization (CAMPO). The proposed model is compared with a simple aggregation model of trip purposes and time of day based on a prior daily OD estimation model using the LBSN data. The results illustrate the promising benefits of applying stochastic point process models and state-space modeling in time-of-day zonal arrival pattern estimation with the LBSN data. The proposed model can significantly reduce the number of parameters to calibrate in order to reduce the sampling bias of LBSN data for trip arrival estimation.     

Controlled time of arrival windows for already initiated energy-neutral continuous descent operations

Continuous descent operations with controlled times of arrival at one or several metering fixes could enable environmentally friendly procedures without compromising terminal airspace capacity. This paper focuses on controlled time of arrival updates once the descent has been already initiated, assessing the feasible time window (and associated fuel consumption) of continuous descent operations requiring neither thrust nor speed-brake usage along the whole descent (i.e. only elevator control is used to achieve different metering times). Based on previous works, an optimal control problem is formulated and numerically solved. The earliest and latest times of arrival at the initial approach fix have been computed for the descent of an Airbus A320 under different scenarios, considering the potential altitudes and distances to go when receiving the controlled time of arrival update. The effects of the aircraft mass, initial speed, longitudinal wind and position of the initial approach fix on the time window have been also investigated. Results show that time windows about three minutes could be achieved for certain conditions, and that there is a trade-off between robustness facing controlled time of arrival updates during the descent and fuel consumption. Interestingly, minimum fuel trajectories almost correspond to those of minimum time.     

A model of bus bunching under reliability-based passenger arrival patterns

If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustrate when bus bunching might occur. We show that non-uniform arrival patterns can significantly influence the bus bunching process. With case studies we find that, even without exogenous delay, bunching can arise when the boarding rate is insufficient given the level of overall demand. Further, in case of exogenous delay, non-uniform arrivals can either worsen or improve the bunching conditions, depending on the level of delay. We conclude that therefore such effects should be considered when service control measures are discussed.     

清河站建桥合一结构的车致振动舒适度研究

清河站站房结构采用建桥合一的结构体系,列车高速通过时产生车致振动的舒适度问题需要重点研究。通过车辆—轨道模型得到列车对轨道的振动激励,将激励时程输入轨道—结构—环境土体模型,计算结构动力响应的研究方法,进行车致振动的舒适度评价,对清河站的研究得到:高铁列车在到发线进出站时,清河站候车层楼板最大预测Z振级满足规范要求;在正线高速通过时,候车层楼板最大预测Z振级超过规范限值,不满足要求,通过采取结构措施可达到舒适度要求。同时得出建桥合一结构体系在高铁列车通过时,正线位置的振动响应大于到发线,行车位置的响应大于其他位置,站台层的振动响应大于高架候车层和夹层的结论。     

公交到站时间预测研究现状与发展趋势

实时的公交到站时间预测是智能公交的重要组成部分,准确的预测有利于帮助居民进行出行规划和减少等待时间.通过研究公交到站时间预测的原理和方法,系统总结了基于GPS、APC等数据的统计学方法和分析模型.对历史平均法、神经网络、卡尔曼滤波、支持向量机和基于概率的预测模型等几种典型方法的预测原理进行了介绍,从预测精度、实时性、计算复杂性等几个方面对模型的优缺点进行了比较.分析了公交到站时间预测发展趋势,提出了该领域需要进一步研究的问题.     

A bi-objective user equilibrium model of travel time reliability in a road network

Travel time, travel time reliability and monetary cost have been empirically identified as the most important criteria influencing route choice behaviour. We concentrate on travel time and travel time reliability and review two prominent user equilibrium models incorporating these two factors. We discuss some shortcomings of these models and propose alternative bi-objective user equilibrium models that overcome the shortcomings. Finally, based on the observation that both models use standard deviation of travel time within their measure of travel time reliability, we propose a general travel time reliability bi-objective user equilibrium model. We prove that this model encompasses those discussed previously and hence forms a general framework for the study of reliability related user equilibrium. We demonstrate and validate our concepts on a small three-link example.     

信号交叉口车辆到达规律分析

信号交叉口是中断车流的重要结点,其车流到达规律的准确描述是交叉口信号控制设计的重要影响因素。信号交叉口车流的到达规律是随机且多样的,并服从一定的统计规律。本文对信号交叉口到达车流的到达时间间隔的统计分析进行拟合,发现信号交叉口车流的到达规律与其变异系数的平方存在耦合关联,并得出结论如下:对数正态分布的拟合范围为0.8874~0.9904,平均拟合度高达0.9489,拟合效果最佳;伽马分布的拟合度范围为0.5352~0.9449,平均的拟合度为0.8056,拟合效果次之;威布尔分布拟合度在0.1997~0.8991之间,总体波动较大,平均的拟合度为0.616;正态分布拟合范围为0.2585~0.6671,平均拟合度为0.6252;指数分布拟合度范围是0.0365~0.4077,平均拟合度是0.2317,拟合效果最差。