基于节点可达度的公交多路径搜索算法

针对公交网络路径搜索问题,以复杂网络的角度进行了相关研究。根据出行者实际需求,提出一种基于节点可达度的公交多路径搜索算法。采用复杂二分网络模型来描述公交网络,将公交线路和公交站点分别看做一类节点,每条公交线路与它所经过的公交站点之间存在连边;在分析网络社团结构的基础上定义了节点可达度,算法根据节点可达度逐步搜索直至目的节点,搜索过程保留可能存在的多条最佳路径。实验结果表明,该方法能够得到最小换乘的多条有效路径。     

Toward Universal Design in Public Transportation Systems: An Analysis of Low‐Floor Bus Passenger Behavior with Video Observations

This study aims to investigate the relationship between ergonomic comfort and the provision of accessibility features for mobility‐impaired persons in the use of public transportation systems in Korea. To deal with mobility issues in a public transportation environment, we chose the low‐floor bus as our research subject because it is the representative of a barrier‐free design solution. We collected data via video observation, which can overcome the limitations of traditional accessibility‐focused studies and laboratory studies by providing data on real usage patterns. We developed a framework to analyze the gathered data which includes user, space, tools, activities, and context. As a result, we observed existing difficulties of mobility‐impaired persons in terms of moving and supporting their bodies on the bus, despite the application of accessibility features. Furthermore, the design only for accessibility of mobility‐disabled persons can cause unexpected predicaments for the passengers who do not have physical handicaps. Drawing on these findings, we concluded that the concept of universal design in public transportation environments must be introduced in Korea. This study suggests video observation as a useful methodology for collecting data in dynamic environments. Additionally, our study is expected to contribute to how the concept of universal design can be implemented, and stimulate issues for ergonomic research based on our behavior pattern analysis.     

一种动态和自适应公交到站时间预测方法

公交到站时间预测是实现智能化公交信息服务的基础,可靠地预测公交到站时间有利于提高公共交通的服务水平,以吸引更多的城市居民选择公共交通.以某城市公交系统海量的历史数据为基础,建立了基于SVM的集合了静态和动态数据的公交预测模型,该模型引入上游路段速度、下游路段最新速度、下游路段最新花时、时间段和路况拥挤程度等动态信息作为模型特征.在此基础上,根据大量公交到站时间历史数据的波动性,提出了一个基于波动性的自适应预测模型.实验结果表明,自适应预测模型优于现有模型,提高了预测的精确度和效率.     

太原市公交查询系统的设计及实现

从太原市公交查询系统建立的必要性出发,进行了公交查询算法的研究,主要探讨了包括最短路径查询及最少花费查询及数据库管理的公交查询系统的实现。该系统采用了VISUAL BASIC6．0为开发工具,MICROSOFT ACCESS2003为后台数据库,开发了基于太原市公交线路的公交查询系统。具有线路查询、换乘查询、站点查询、数据管理等一系列功能。     

A Two-Stage Urban Bus Stop Location Model

This research analyses optimal bus stop location using a sequentially applied two-stage model. During the first stage the bus stops are strategically located throughout the public transport system on a macroscopic scale while at the same time the social cost of the network is minimized. The second stage, on a more tactical level, uses the previously obtained macroscopic solution to microscopically locate the stops along specific urban routes whilst maximizing the commercial speed of the public transport service. The proposed model is applied to a real case; sensitivity analysis studies variations in bus stop location using different traffic flows, bus flows and signalling sequences. The results obtained show important differences in the commercial speed of the buses depending on the final location of the stops.     

Intelligent bus routing with heterogeneous human mobility patterns

Optimal planning for public transportation is one of the keys helping to bring a sustainable development and a better quality of life in urban areas. Compared to private transportation, public transportation uses road space more efficiently and produces fewer accidents and emissions. However, in many cities people prefer to take private transportation other than public transportation due to the inconvenience of public transportation services. In this paper, we focus on the identification and optimization of flawed region pairs with problematic bus routing to improve utilization efficiency of public transportation services, according to people’s real demand for public transportation. To this end, we first provide an integrated mobility pattern analysis between the location traces of taxicabs and the mobility records in bus transactions. Based on the mobility patterns, we propose a localized transportation mode choice model, with which we can dynamically predict the bus travel demand for different bus routing by taking into account both bus and taxi travel demands. This model is then used for bus routing optimization which aims to convert as many people from private transportation to public transportation as possible given budget constraints on the bus route modification. We also leverage the model to identify region pairs with flawed bus routes, which are effectively optimized using our approach. To validate the effectiveness of the proposed methods, extensive studies are performed on real-world data collected in Beijing which contains 19 million taxi trips and 10 million bus trips.     

智能交通动态调度优化模型与评价方法

为了降低大城市市民出行成本,缓解公交企业运力压力,提出一种智能交通出行OD(Origin Destination,出行地和目的地)的公交调度优化算法,以公交出行OD客流预测和计划排班发车时间间隔为出发点,运用公交出行OD客流推导理论,构建智能交通出行OD的公交调度优化模型。通过获取个人OD数据,利用单条线路公交OD方法,实现全市公交OD矩阵推算。根据全市公交出行OD推算结果,求解公交调度模型,解决智能交通调度多目标规划和公交线网优化问题。通过仿真模拟试验,分析智能公交排班计划评价指标,计算车辆营运效率占比:自动排班仿真数据为79%,实际运营数据为73%;统计车辆高峰时段与全天营运车次占比:自动排班仿真数据为36.75%,实际运营数据为37.37%,满足智能公交计划排班评价指标的要求,实例证明模型和算法具有实用性和可靠性。     

A novel data collection mechanism for smart grids using public transportation buses

In this study, we propose a novel solution for collecting smart meter data by merging Vehicular Ad-Hoc Networks (VANET) and smart grid communication technologies. In our proposed mechanism, Vehicular Ad-Hoc Networks are utilized for collecting data from smart meters, eliminating the need for manpower. To the best of our knowledge, this is the first study proposing the utilization of public transportation vehicles for collecting data from smart meters. With this work, the use of the IEEE 802.11p protocol has been proposed for the first time for use in smart grid applications. In our scheme, data flows first from smart meters to a bus through infrastructure-to-vehicle (I2V) communication and then from the bus to a bus stop through vehicle-to-infrastructure (V2I) communication. The performance of our proposed mechanism has been investigated in detail in terms of end-to-end delay and delivery ratio by using Network Simulator-2 and with different routing protocols.     

ACCESS: An agent-based model to explore job accessibility inequalities

This paper presents ACCESS, an agent-based model for exploring job accessibility inequalities among different social groups. ACCESS allows for investigation on the impact of public transport and land use policies on the residential location of the working population and their accessibility to job opportunities. ACCESS can be adapted to different realities, allowing to represent societies with diverse socioeconomic disparities. A utility function composed of job accessibility and neighborhood status is maximized by agents during the residential location choice process. The model outputs include Lorenz curves considering the accessibility dimension, as well as Gini metrics to support the analysis of interventions impacts on accessibility inequalities. An empirical case study is performed on the municipality of Sao Paulo, which is characterized by high levels of inequality. Five experiments were simulated considering three different socio-occupational groups. The first experiment includes (i) new public mass rail transport lines, and the other four experiments consider the new transport infrastructure from the first experiment and add (ii) new social housing location strategies; (iii) new job locations; (iv) new jobs and different social housing supplies and location strategies; and (v) provision of social housing based on a government housing program. The results show that ACCESS allowed the residential location of different social status groups to be depicted with a high correlation to the observed situation. Regarding the case study, the results indicate that only having interventions on transport system is insufficient to provide a significant change in terms of inequality. Better results that impact inequality are reached with public mass rail transport interventions associated with land use policies with different social housing and job location programs.     

Predicting the passenger demand on bus services for mobile users

Public transport, especially the bus transport, can reduce the private car usage and fuel consumption, and alleviate traffic congestion. However, when traveling in buses, the travelers not only care about the waiting time, but also care about the crowdedness in the bus itself. Excessively overcrowded bus may drive away the anxious travelers and make them reluctant to take buses. So accurate, real-time and reliable passenger demand prediction becomes necessary, which can help determine the bus headway and help reduce the waiting time of passengers. Based on a large database from a real bus system, this paper aims to present a passenger demand prediction system for mobile users. The system includes a server-side bus information data stream processing and mining program and a client-side mobile application for Android smartphones. The server program continuously monitors for each bus stop the number of passengers waiting at the bus stop, the number of passengers that will pass the bus stop, as well as the traffic conditions in the area around the stop. It delivers real time bus and traffic information to mobile users via restful web services. The client-side location-based mobile application consumes these services to help mobile users make informed transportation choices. For example the availability of buses might be a deterrent when they are too crowded. However, there are three major challenges for predicting the passenger demands on bus services: inhomogeneous, seasonal bursty periods and periodicities. To overcome the challenges, we propose three predictive models and further take a data stream ensemble framework to predict the number of passengers. We develop a prototype system with different types of Android based mobile phones and comprehensively experiment over a 22-week period. The evaluation results suggest that the proposed system achieves outstanding prediction accuracy among 86,411 passenger demands on bus services, more than 78% of them are accurately forecasted.     

公交车辆用可燃气体检测仪

以可编程门阵列器件FPGA和气体传感器MQ-3为核心,设计了能检测可燃物挥发气的车载式检测仪.为了保证灵敏度,采用了差动集气管结构;为了免人工维护,采用了气泵正、反转集气、吹扫双功能;所有部件小巧,适合安装在车门附近的狭小空间内.最后对差动集气管效果、敏感探测距离进行了实验.     

Assessing accessibility with local coefficients for the LUTI model MARS

Accessibility-based land use and transport interaction (LUTI) models are tools for policy assessments that facilitate coherent implementation of sustainable strategic urban plans. This study aims to improve one of those LUTI models introducing the different impact of factors influencing residential and workplace choice by computing local coefficients. In particular, this research explores the methodology of integrating the public choice model into the MARS (Metropolitan Activity Relocation Simulator) model using a complex accessibility indicator. We established a new approach to input the variation of the influence of each public service across space with the use of Geographically Weighted Regression (GWR). The model update and extension of MARS are all based on the Region of Madrid, Spain. Using the new accessibility indicator yielded better results and corrected some under estimation and overestimations in the number of workplaces. The correlation using the new accessibility indicator is significantly higher than the one using the old one. The prediction using the new indicator achieves better results for the whole area whatever the zone is small or large. The analysis evidences the convenience of GIS and LUTI combination to improve model accuracy and precision. Using the new accessibility indicator based on local coefficients, MARS model fits better with the real data in respect of the distribution of workplaces and residents, which are the key representatives of the land use sub-model.     

基于Space-P复杂网络模型的城市公交网络特性分析

针对城市公交网络中换乘网络的整体性能分析问题,提出一种基于复杂网络理论的分析方法。首先,基于图论思想,将公交网络建模成由Space-P方法表示的公交换乘网络拓扑模型;然后,统计分析了公交换乘网络的度分布、平均最短路径长度、聚类系数、紧密中心性和介数中心性等特性。以北京市的公交网络为例进行了相关分析,从宏观角度说明北京公交网络具有小世界网络特点,市民出行需要换乘的概率较大,但换乘较为便捷;同时,给出了相关站点的具体地理信息,为公交规划部门优化公交网络提供了参考。     

基于天地图的智慧公交移动APP设计与实现

针对太原市智慧公交系统建设的需求,基于天地图移动API和IOS平台,研发了一款智慧公交移动APP.APP提供静态公交查询、实时公交查询、周边公交查询和公交换乘查询等公交查询服务和周边兴趣点查询、天气查询和交通管理通知公告等增值服务.解决传统公交运营管理不能满足公众对出行信息的需求问题,做到了智慧出行.     

School bus routing—a column generation approach

The School Bus Routing Problem (SBRP), a generalization of the well‐known Vehicle Routing Problem, involves the routing, planning, and scheduling of public school bus transportation. The problem can be divided into several subproblems, including bus stop selection, assigning students to buses, and determining the bus routes. This work presents an exact branch‐and‐price framework for the SBRP, with a strong emphasis on efficiency issues inherently related to column generation (CG). Experiments are conducted on a set of 128 SBRP instances. Many of these instances are solved optimally; for the remaining instances, strong lower bounds have been derived. Furthermore, better integer solutions were found for a number of instances reported in the literature. Both lower bounds computed on the optimum solution and stabilization added to the CG procedure significantly improved computation times.     

贵阳公交复杂网络抗毁性分析

城市公共交通系统可以抽象为由公交线路和停靠站点构成的网络,公交网络构成了一个典型的复杂网络。复杂网络的研究在过去几年得到了迅速发展,其中复杂网络的抗毁性是研究焦点之一。在本文中,以贵阳市的公共汽车交通系统中的停靠站点网络为研究对象,测试了网络在随机攻击和选择性攻击情况下的抗毁性。结果表明,该网络对节点的随机攻击具有较强的抗击能力,而对选择性攻击的抗击能力较弱。     

基于城市公共交通移动模型的协作延迟容忍网络路由策略

如何利用有限的传输机会可靠地传送车载服务感知信息是智能交通发展的“瓶颈”问题,利用公共交通中车辆的运动规律,提出基于节点之间机会接触来进行消息的逐跳转发策略,同时结合公共交通系统自身的特点,设计了一种基于公共交通移动模型的协作延迟容忍网络（DTN）路由算法TF。首先,根据公共交通移动模型自身的特点,将公交、长途客车等节点按其运动路径进行分组,提出一种基于固定运动路径分组的DTN路由算法;然后,将出租车、行人类节点定义为自由节点,并设计了一种基于转发因子控制的DTN路由策略作为分组路由机制的补充。仿真结果表明,与Epidemic、Prophet以及SAW路由算法相比,TF路由算法具有较高的消息投递率和较低的平均延迟。     

Data-driven shuttle service design for sustainable last mile transportation

Last mile transportation is important in both freight and passenger transport as it accounts for a large portion of the costs and emissions in the transportation industry. In urban transport, the continuously growing travel demands and the rapid development of mass transit systems place a high stress on last mile transportation, which is a vital but underdeveloped part of urban transportation systems. This underdevelopment greatly impedes the further improvement of bus sharing rates and the realisation of sustainable transportation. Therefore, this research proposes a data-driven method to design shuttle services to improve the efficiency and convenience of last mile transportation. Specifically, a unified tool is developed to identify the last mile travel demands from various data sources. Based on these demands, the locations of bus stop are planned through an improved clustering algorithm, and the routing and scheduling of shuttle services are designed using a data-driven method. In addition, a simulation-based cost-benefit analysis is conducted to evaluate the performances of shuttle services in different areas. Finally, a case study using bicycle-sharing data in Shanghai is presented to demonstrate the working process of the proposed method and verify its performance.     

Measuring accessibility of urban scales: A trip-based interaction potential model

In the interaction process of city space and citizens’ activity pattens, the regular travel behavior under the cumulative impacts of urban land use is required to be assessed. The aim of this study is to formulate and estimate attraction choice models that provide measurements of accessibility on various scales reflecting the choice of people to travel to facilities or activity places and characterize the interaction between land use patterns and transportation facilities. Based on a dataset inclusive of big data from varied sources, measurement methodologies are proposed encompassing the multidimensional aspect of the accessibility estimation issues. We sketch the characteristics of service facilities and travel impedance in the calibration processes. Logit models and gravity models are applied to simulate the impacts of different scales of trip length on the accessibility scores. Accessibility is aggregated over spatial elements of different scales and trips and herein the spatial accessibility of study zones is estimated as well as the potential of citizens’ travel choices and activity patterns. Such spatial interaction models have potential implication for enhancing our understanding of the cumulative environmental influences on citizen’s travel behavior and vice versa. It can be a substantial part of a more composed proposal of life convenience of residential citizens reflecting the happiness of living in an urban community.