Mining factors affecting taxi drivers’ incomes using GPS trajectories

Taxis provide essential transport services in urban areas. In the taxi industry, the income level remains a cause of concern for taxi drivers as well as regulators. Mining underlying factors affecting the income level will not only benefit the newcomers and low-income drivers but also assist in developing effective optimization algorithms for taxi operations. This paper intends to disclose the factors affecting incomes along with their quantitative influence by mining over 167 million GPS records from nearly 8000 taxis in Shanghai. We first identify a marked difference in drivers’ incomes and categorize drivers into three income levels accordingly. We next investigate the overall search-delivery process, thereby defining several factors that may affect the income level. We then develop a generalized multi-level ordered logit (GMOL) model to find the significant factors that influence incomes. Finally, we compute the elasticity for those significant factors and present their contributions, as well as challenge some preconceived ideas regarding how to earn high incomes.     

Constraint reformulation and a Lagrangian relaxation-based solution algorithm for a least expected time path problem

Using a sample-based representation scheme to capture spatial and temporal travel time correlations, this article constructs an integer programming model for finding the a priori least expected time paths. We explicitly consider the non-anticipativity constraint associated with the a priori path in a time-dependent and stochastic network, and propose a number of reformulations to establish linear inequalities that can be easily dualized by a Lagrangian relaxation solution approach. The relaxed model is further decomposed into two sub-problems, which can be solved directly by using a modified label-correcting algorithm and a simple single-value linear programming method. Several solution algorithms, including a sub-gradient method, a branch and bound method, and heuristics with additional constraints on Lagrangian multipliers, are proposed to improve solution quality and find approximate optimal solutions. The numerical experiments investigate the quality and computational efficiency of the proposed solution approach.     

Equity-oriented skip-stopping schedule optimization in an oversaturated urban rail transit network

In this study, we focus on improving system-wide equity performance in an oversaturated urban rail transit network based on multi-commodity flow formulation. From the system perspective, an urban rail transit network is a distributed system, where a set of resources (i.e., train capacity) is shared by a number of users (i.e., passengers), and equitable individuals and groups should receive equal shares of resources. However, when oversaturation occurs in an urban rail transit network during peak hours, passengers waiting at different stations may receive varying shares of train capacity leading to the inequity problem under train all-stopping pattern. Train skip-stopping pattern is an effective operational approach, which holds back some passengers at stations and re-routes their journeys in the time dimension based on the available capacity of each train. In this study, the inequity problem in an oversaturated urban rail transit network is analyzed using a multi-commodity flow modeling framework. In detail, first, discretized states, corresponding to the number of missed trains for passengers, are constructed in a space-time-state three-dimensional network, so that the system-wide equity performance can be viewed as a distribution of all passengers in different states. Different from existing flow-based optimization models, we formulate individual passenger and train stopping pattern as commodity and network structure in the multi-commodity flow-modeling framework, respectively. Then, we aim to find an optimal commodity flow and well-designed network structure through the proposed multi-commodity flow model and simultaneously achieve the equitable distribution of all passengers and the optimal train skip-stopping pattern. To quickly solve the proposed model and find an optimal train skip-stopping pattern with preferable system-wide equity performance, the proposed linear programming model can be effectively decomposed to a least-cost sub-problem with positive arc costs for each individual passenger and a least-cost sub-problem with negative arc costs for each individual train under a Lagrangian relaxation framework. For application and implementation, the proposed train skip-stopping optimization model is applied to a simple case and a real-world case based on Batong Line in the Beijing Subway Network. The simple case demonstrates that our proposed Lagrangian relaxation framework can obtain the approximate optimal solution with a small-gap lower bound and a lot of computing time saved compared with CPLEX solver. The real-world case based on Batong Line in the Beijing Subway Network compares the equity and efficiency indices under the operational approach of train skip-stopping pattern with those under the train all-stopping pattern to state the advantage of the train skip-stopping operational approach.     

An innovative method for the analysis of vehicle movements in roundabouts based on image processing

The objective of this paper is to propose a method, based on the image processing of field survey data, to analyze vehicles movements into roundabouts. This research study consisted of three stages: a field survey to collect vehicular flow images captured by video cameras, the processing of these images using a proprietary software (VeTRA—Vehicle Tracking for Roundabout Analysis), and finally, the analysis of the collected data. The main feature of the software is that it allows the automatic computation of the main variables necessary to rank and evaluate a generic roundabout: the entry/exit (E/E) matrix with classification of vehicles (e.g., heavy, light, and motorbikes), vehicle trajectories, and vehicular speed diagrams along the paths inside the roundabout. The processing system is robust enough to withstand classic problems affecting image processing such as variable wind conditions, cloud cover, shadows, and obstructions. Calibration and error evaluation have been deduced from data collected by a high precision Real Time Kinematic GPS video recording system mounted on a probe vehicle. Data of E/E matrices generated by VeTRA are compared with those manually counted on the corresponding video images. A case study of an existing roundabout is featured in the paper. The results indicate that the software has a high capability of generating the E/E matrix. The analysis of vehicular trajectories with both the plot of curvature diagrams and the corresponding speed diagrams enable the evaluation of driver behavior relative to the geometric shape of the roundabout. Copyright © 2011 John Wiley & Sons, Ltd.     

Convection and the seeding of the North Atlantic bloom

Observations of vertical velocities in deep wintertime mixed layers using neutrally buoyant floats show that the convectively driven vertical velocities, roughly 1000 m per day, greatly exceed the sinking velocities of phytoplankton, 10 m or less per day. These velocities mix plankton effectively and uniformly across the convective layer and are therefore capable of returning those that have sunk to depth back into the euphotic zone. This mechanism cycles cells through the surface layer during the winter and provides a seed population for the spring bloom. A simple model of this mechanism applied to immortal phytoplankton in the subpolar Labrador Sea predicts that the seed population in early spring will be a few percent of the fall concentration if the plankton sink more slowly than the mean rate at which the surface well-mixed layer grows over the winter. Plankton that sink faster than this will mostly sink into the abyss with only a minute fraction remaining by spring. The shallower mixed layers of mid-latitudes are predicted to be much less effective at maintaining a seed population over the winter, limiting the ability of rapidly sinking cells to survive the winter.     

Enrichment, concentration and retention processes in relation to anchovy (Engraulis ringens) eggs and larvae distributions in the northern Humboldt upwelling ecosystem

A Lagrangian model is used to simulate and quantify in the northern Humboldt upwelling ecosystem the processes of enrichment, concentration and retention, identified by Bakun [Bakun, A., 1996. Patterns in the ocean. Ocean processes and marine population dynamics. University of California Sea Grant, California, USA, in cooperation with Centro de Investigaciones Biologicas de Noroeste, La Paz, Baja California Sur, Mexico, 323 pp.] as being important for the survival and recruitment of early life stages of pelagic fish. The method relies on tracking the positions of particles within water velocity fields generated by a three-dimensional hydrodynamic model. Simple criteria for considering particles as participating to enrichment, concentration or retention are used to derive indices of the three processes. We analyse the spatial distribution of and seasonal variability in these indices. The results are discussed in relation to anchovy (Engraulis ringens) eggs and larvae distributions off Peru, and to a comparable study conducted in the southern Benguela upwelling ecosystem.     

A variational formulation for higher order macroscopic traffic flow models of the GSOM family

The GSOM (Generic second order modelling) family of traffic flow models combines the LWR model with dynamics of driver-specific attributes and can be expressed as a system of conservation laws. The object of the paper is to show that a proper Lagrangian formulation of the GSOM model can be recast as a Hamilton–Jacobi equation, the solution of which can be expressed as the value function of an optimal control problem. This value function is interpreted as the position of vehicles, and the optimal trajectories of the optimal control formulation can be identified with the characteristics. Further the paper analyzes the initial and boundary conditions, proposes a generalization of the inf-morphism and the Lax–Hopf formulas to the GSOM model, and considers numerical aspects.     

局部桩基础和复合地基上的土石坝三维分析

结合太仓市第二水厂蓄淡避咸水库大坝的地基加固处理工程,针对桩基础和桩长纵向渐变复合地基,应用三维快速拉格朗日法对较大规模群桩进行计算,分析了不同桩径、桩距和桩长复合地基对坝体和坝基的应力、位移的影响。     

考虑旅客需求的停站方案与列车运行图一体化模型与算法

考虑高速铁路旅客出行的时空敏感性较高的特点,将旅客运输状态引入运输时空网络,构建三维的时间-空间-状态网络,提出基于旅客需求的停站方案与列车运行图综合优化0-1整数规划模型,实现旅客分配、停站方案与列车运行图编制的一体化。设计拉格朗日松弛求解算法,将复杂的列车间强耦合问题分解为单列车的最短路径子问题集合,从而降低模型求解难度。以京沪高铁北京南-曲阜东区段为背景进行验证和分析,结果表明模型不仅实现了较低的运营成本,还能够有效满足旅客需求,实现客流分配、停站方案与列车运行图编制的有机联动。     

基于多次波形匹配的高速铁路动检数据里程误差评估与修正

获取具有准确里程信息的动检车检测数据,是实现高速铁路线路的高效养护维修与分析其状态演变规律的基本前提。针对当前处理动检数据里程误差的不足,如区段内数据波形重复性差或依据单次检测数据处理误差等会造成错误修正,通过引入约束条件、动态尺度系数以识别、处理特殊区段并综合考虑多次检测数据,提出一种更可靠的里程误差评估模型,采用拉格朗日乘子法求解该模型并基于线性变换与插值方法修正里程误差,最后应用该方法编制了动检数据分析软件。结合某高速铁路动检数据研究发现:不合理的模型尺度参数会降低修正精度,建议取40~120m;在99.7%置信度下,任意两次动检数据间里程误差可控制在0.54m内;本文方法能有效处理实际工程中动检数据的里程误差问题,结合数据点标准差方法可实现快速定位线路几何状态波动明显的位置并准确评估线路养护维修作业效果。