Analyzing travelers' attitude towards ride-hailing services in developing countries: Case of Lahore,Pakistan

Ride-hailing services are gaining momentum to meet the urban travel demand in the absence of proper public transport in developing countries. To the best of our knowledge, research on passenger's behavior and attitude towards the service quality of ride-hailing services and certainly studies focusing on developing countries are quite rare. Ride-hailing services were launched to meet the travel demand of residents throughout the city of Lahore, Pakistan in 2015. A revealed preferences study of 865 respondents consisting their demographic, travel information and perceptions related to selected attributes of service quality was carried out to examine their attitude and behavior towards the use of ride-hailing services in Lahore, Pakistan.Most of the users of these services are young, well-educated and have relatively high income. The travelers who were using Rickshaw services before are found to be the frequent users of these services and ride-hailing services have started replacing respondents' previous modes of travel. Exploratory factor analysis were employed on collected data to identify the factors effecting the traveler's perceptions regarding the use of ride-hailing services and structural model of users' satisfaction were constructed based on these factors later.The results exploratory factor analysis (EFA) and structural equation modeling (SEM) revealed that significant determinants of passenger's satisfaction with ride-hailing services are coverage and accessibility attributes (CAA), instrumental attributes (IA), service attraction attributes (SAA) and safety attributes (SA). The number of trips, trip purpose, income, education, time since the use of these services, profession and household size are also significant parameters in the determination of traveler's behavior and attitude towards the use of ride-hailing services in Lahore city. The commuter's overall satisfaction with service quality of app-based services have positive association with travelers intentions to continue use of app-based services and their believe that these services have filled the gap of public transport in the city and replacing previous modes of travel. The further improvements in attributes will enhance the traveler's satisfaction with these services. Insight into the attitude and perceptions of travelers would be useful for the transport planners, ride-hailing companies and policy makers for making appropriate improvements in the services and giving them space in existing transport system.     

Development of a behaviorally induced system optimal travel demand management system

The basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This “passive” way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, system optimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.     

Providing personalized system optimum traveler information in a congested traffic network with mixed users

The advancement of information and communication technology allows the use of more sophisticated information provision strategies for real-time traffic management in a congested network. This article proposes a personalized system optimum traveler information (PSOI) system under ubiquitous communication, which allows traffic system operators to fully optimize and coordinate individuals' trip plans according to the personal attributes, such as real-time location, value of time, allowable budgets for congestion tolling, and willingness to take detours. We also developed an efficient queue-based evaluation and solution heuristic algorithm using mesoscopic simulation models to solve for near-optimal PSOI strategies—route suggestions for each individual traveler. The simulation optimization algorithm can account for different information users and provide predictive information that robustly accounts for potential decisions of other travelers in real time. Case studies were carried out on a test network and a real-world network, and the proposed heuristic algorithm is proven effective. Also, sensitivity analyses show that PSOI not only is an effective traffic management method in reducing average system travel time, but also potentially provides travelers with reasonable or even shorter travel times compared with other information users. Further, simulation results showed that even in mixed traffic, PSOI is able to shorten travel times for both users without information and users of other information types. Thus, PSOI is recommended by this article as an advantageous way for next-generation advanced information systems and dynamic traffic management.     

私家车出行者交通信息需求研究

交通出行信息对私家车出行者行为选择存在不同程度的影响。通过对大连市私家车出行者交通出行信息使用意向调查,获取私家车出行者交通出行信息选择行为特性数据,引入因子分析方法对交通出行信息内容进行合理分类,建立交通出行信息选择累积Logistic回归模型,对私家车出行者交通出行信息需求进行研究。研究结果表明私家车出行者对交通出行信息内容存在不同程度的需求,其中与个人私家车出行质量相关信息的需求最高,面向私家车出行者的城市交通信息服务系统建设与运营应体现针对性。     

Modeling bus bunching using massive location and fare collection data

Bus bunching is a well-known phenomenon for operators, users and regulators of high-frequency bus services. Bus operations are usually affected by increasing differences in the time intervals (headways) between consecutive buses. The effect of this variability is that buses tend to group into bunches of two or more, which severely affects the quality of service and the operational efficiency. The aim of this paper is to analyze which factors are associated to the phenomenon, using massive data from high-frequency services available in Santiago (Chile) and common-route services in Gatineau (Canada). The data is obtained from the bus GPS and AFC systems and are processed to obtain headways between buses. Using data from one week, we develop models to explain the variation of the continuous and discrete indicators of bus bunching as a function of variables related to the operation, variables related to the demand structure, and variables related to the infrastructure. Some of the factors that contribute to increase bus bunching are: stops located toward the end of the route, high scheduled frequency, irregular bus dispatch headways, non-homogeneous fleet, high demand, and high variability of demand. The results are useful for the design of quality indexes to measure bunching in bus operations, and for the design and operation of bus routes, taking into consideration the potential bus bunching problems.     

Driving behavior in mixed traffic flow: A novel model for assessing bus movement considering the interaction with motorcyclists

Improving level of service (LOS) is an essential requirement for a sustainable public transport development of a city. A large number of previous studies have considered bus LOS on viewpoints of its users. It should, however, be noted that the viewpoint of non-bus travelers is also equally important because they are potential to be bus users. This paper suggests a novel model for transport planners to assess driving behavior of bus drivers through a consideration of bus movement in association with motorcyclists' interaction. Bus movement assessment is modelled based on GPS and traffic surveillance video data in correlation with the traffic density estimated under Kalman-filter algorithm. A case study in Hanoi, Vietnam showed an illustration to the model.     

拥堵收费对弹性出行的小汽车使用者出行方式选择影响研究

所有出行群体中,受拥堵收费政策影响最大的是弹性出行的小汽车使用者。引入相对拥堵费作为政策变量,表征拥堵收费政策对该群体出行方式选择的影响,并基于Nested Logit模型,建立了拥堵收费影响下的出行者出行方式选择模型。利用对南京新街口商圈区域弹性出行的小汽车使用者进行的RP和SP调查所获得的数据,对模型参数进行了估计,结果显示:女性、低收入者、IC卡持有者、短途和高频出行者在面对拥堵收费政策时,更容易放弃小汽车而转向公共交通出行。利用弹性理论,分析了不同拥堵费水平下出行者对出行时间和拥堵收费政策的弹性,结果发现:①出行时间的弹性反映了出行方式的总体服务水平;②出行者在出行方式选择时对拥堵收费变得“显著”敏感的临界值为13.25元/次。      

3G移动通信技术在城市交通信息系统中的应用研究

在探讨了出行者对交通信息需求特点的基础上，对交通信息分为动态、静态和关联三类。为了充分掌握动态交通信息，设计了基于第3代移动通信技术（3G）的城市交通信息系统3层平台方案，并对其结构与功能进行了研究，重点阐述了由服务器、数据库以及办公管理设备和网络设备组成的交通信息中心及其工作原理，最后以车载设备结合实时交通信息查找最短时间路线为例说明了基于3G技术的城市交通信息系统的功能和优势。该系统使出行者能够通过手持移动终端（手机、PDA等）或者车载设备实时地查询交通信息，因此更加适应交通信息的动态、时变的特性。     

Experimental Study of Effects of Travel Time Distribution Information on Dynamic Route Choice Behavior

This study focuses on the possibility that providing travelers with information on travel time distribution, along with the existing travel time information, might affect their decision making and enhance traffic control. As an initial step to confirm the effectiveness of travel time distribution information, we use a laboratory experiment to obtain panel data of route choices when information is provided. The rationality of the behavior of the respondents and the characteristics of the route choice are first analyzed by aggregation analysis and then statistically examined by specifying a mixed logit route choice model. As a result, it is revealed that both travel time information and maximum travel time information significantly affect route choice behavior when a penalty is imposed for late arrival.     

我国交通运输信息化进程中存在的问题和建议分析

交通运输系统承担着人流、物流移动的功能,维持着社会机能的正常运转。充分利用现代信息技术建立完善的交通信息系统、建设现代交通,是国家推进发展全局战略的迫切要求。分析了我国交通运输信息化的重要性及进程中存在的问题,提出了相应的建议及技术支持。     

交通信息提取计算理论及其技术框架与发展策略

在概要介绍信息提取计算技术(Granular Computing)的发展概况、有关概念、基本理念和技术要点的基础上,分析信息提取计算技术对于交通数据处理的适用性,将信息提取计算技术引入交通数据处理领域,从理论方法、支撑环境和应用技术三个方面,提出了交通信息提取计算技术的概念模型和技术框架,并在理论方法上进行了较大拓展,融入了传统数学方法、知识发现型方法和非量化方法。最后,分析并提出了交通信息提取计算技术的总体发展思路和推进策略。     

基于后悔理论的社交网络分享型交通信息的用户价值研究

以社交网络为平台的交通信息对出行者的决策有重要影响.为了研究社交网络分享型交通信息的用户价值,分析了社交网络中交通信息的产生与传播行为,并从信息行为的角度研究了社交网络中交通信息的特征.基于后悔理论建立了社交网络交通信息的用户价值评估模型,并给出出行者的路径选择效用以及交通信息的更新方法.在此基础上,从交通信息有效性与负效用的角度分析了社交网络交通信息的用户价值特征.基于不同的网络信息传播场景,对其中交通信息的用户价值进行了分析.结果表明,社交网络中的交通信息能够对出行者的决策起到辅助作用,在有效场景中出行者决策的后悔值降低了20%;但用户价值随其在社交网络中的持续传播而降低,且过度传播的交通信息将对出行者决策产生负效应.      

基于B/S结构的公安交警无线移动警务系统的设计与实现

利用公安系统现有的数据信息资源和无线应用协议，为公安交警研制了基于B／S结构，利用无线公共网络进行实时现场信息收集、传输与处理的公安交警无线移动警务系统．扩展了公安系统无线领域的应用范围。使公安交警可实时获取所需要的信息，同时可向公安数据服务中心传送数据和图片。最后，在多普达686PDA环境下验证了系统的性能。     

智能型手机应用程序对运具选择行为之影响

因应资通信技术发展,智能型手持设备逐渐普遍,应用程序蓬勃发展改变人类传统行为模式甚巨.其中,运输相关之应用程序多样化发展,功能包含地理信息系统的应用、交通信息的提供、车辆派遣的预约、交通票证的订定、观光游程的设计等.依据台北市交通局统计2013年民众透过智能型手机应用程序查询次数,每月已高达6 000万次以上,实有必要针对运输类应用程序所衍生之效果进行探究.论文主要研讨智能型手机应用程序所提供的交通运输信息对用户旅运行为之运具选择影响,透过问卷调查,进行个体运具选择模式之构建,以分析台北市旅运者在受智能型手机应用程序提供的实时交通信息对于运具选择行为转变之影响,期能了解ITS结合智能型手机应用程序的交通信息服务对于提高公共运输便利性之效益.      

Mobility as a service for road traffic safety in a high use of motorcycle environment

Mobility as a service is expected to contribute to a safer, more efficient and sustainable transport by putting the right modes in the right places and connecting them intermodally. The aim of mobility as a service in a local context (MaaS-LC) is to build safety awareness and enhance road traffic safety, and it was developed by combining both a Safety Index and a Walkability Index. The Safety Index was derived from traffic accidents and volume data while the Walkability Index is the result of connections and places in the surroundings. As a case study, a trial experiment was conducted in Phuket, Thailand, which depicted the characteristics of the South and Southeast Asia region. The results showed that the usability and useful information on the MaaS-LC application could influence and change the travel behavior of people. Moreover, the difference between transit users and private vehicle users was how they considered walkability. This study concluded that this app could raise people's safety awareness. Nonetheless, it has yet to show an influence on people regarding their choices of transportation.     

基于Logit模型的综合交通枢纽乘客出站设施选择

从选择方案特性和出行者特性两方面定性和定量地分析乘客出站设施选择的影响因素.基于Logit模型原理,选定年龄、属性、性别、负重和出行时间为特性变量,建立了乘客选择楼梯、自动扶梯或厢式电梯出站的路径选择模型.根据北京南站地铁出站乘客的RP调查数据,借助SPSS软件对模型进行了标定和检验,量化了影响因素对乘客选择行为的影响程度.所建模型准确率高达81.69%,模型结果表明,所研究的5种影响因素中,年龄、负重、属性和出站时间影响乘客出站设施选择,而性别对乘客出站设施选择基本没有影响.此研究为优化枢纽内部空间布局、评价和提高综合交通枢纽服务设施的效率提供理论依据.      

船舶航行交通事件实时检测技术研究现状与展望

船舶航行交通事件检测依赖基于历史数据的离线检测方法, 检测模型适用性差, 难以满足监管人员的实时监测需求。通过分析船舶异常行为检测、航行事故检测等现有交通事件检测技术, 可以发现: 在数据层面, 监测数据来源单一、环境信息缺失; 在方法层面, 基于统计、风险评估等经典模型的事件监测方法效率高但准确性低, 基于神经网络、图像识别等机器学习的检测方法准确性高但效率低; 多源数据融合、多项技术结合的交通事件检测方法成为实时检测方法的发展趋势。在此基础上, 梳理了实时船舶航行交通事件检测的3项关键技术: (1)海事大数据技术: 高效处理船舶运动数据和航行环境数据, 统一多源异构数据结构标准, 降低数据源单一造成的事件误报率; (2)船舶行为动态建模技术: 利用知识图谱等技术融合船舶航行情境信息, 在不同船舶运动环境下利用深度学习、语义关联、图神经网络等方法构建不同的船舶行为模型, 提高检测准确性; (3)实时分析和可视化技术: 结合平行系统进行虚实系统间信息传递, 定性分析检测结果, 实时显示检测全过程, 提升监管过程中的人机交互效率。然后, 提出了包括数据采集、后台服务和客户端应用3个功能模块的交通事件平行检测系统; 该系统具备实时接收并处理船舶航行数据、分析并预测交通状态、动态检测并预警交通事件和仿真结果展示等功能。从数据融合、交通状态感知和交通虚实映射3个方面, 展望了面向海事监测实务的实时检测技术发展方向。      

城市快速路基本路段运行状况评价方法研究

与传统的服务水平评价不同，采用能够综合反映道路管理者和道路使用者共同要求的评价指标——临界密度比对城市快速路基本段的运行状况进行评价；根据快速路交通信息采集系统提供的大量数据，比选了适合的交通流模型，并对临界密度进行标定；最后给出了评价指标的等级划分和对应状态的描述。     

公交站台区域电动自行车与行人通行冲突演化博弈模型

为探究公交站台区域进出站台行人与电动自行车发生冲突时，双方的通行策略选择机制，建立行人与电动自行车通行时间延误模型，分析2类出行者选择是否通行或穿越策略的时间收益，利用复制动态方程刻画2类出行者通行策略的博弈学习行为，建立该区域2类出行者之间的冲突演化博弈模型，结合稳定性分析可以得到该区域2类出行者发生冲突时的稳定通行选择策略。利用桂林市6个公交站台区域的实测数据对演化博弈模型进行实证分析，结果表明:选择“通行”策略的行人群体比例越大，其过街安全感越高；发生冲突时，电动自行车做出决策的时间较行人更短，且2类出行者分别做出“通行”或“穿越”的决策时间短于做出“等待”或“减速”的决策时间，电动自行车平均用时减少约23%，行人平均用时减少约24%。      

Modeling the Effects of Population Density on Prospect Theory-Based Travel Mode-Choice Equilibrium

In conventional transportation planning models, it was always assumed that the population density is given and fixed in the study areas. Therefore, the effects of population density on travel choice have not been explicitly incorporated into these existing models for long-term transportation planning. Meanwhile, travel choice models in previous studies are usually developed by using discrete choice theories or user equilibrium principle. Thus, many significant characteristics of travelers’ behaviors, such as risk preference and learning process over time, cannot be considered in these conventional models. This article proposes a convex prospect theory-based model to investigate the effects of population density on the travelers’ mode-choice behavior under an advanced transportation information system (ATIS) in a multimodal transportation corridor. It is shown that population density is closely co-related to the modal split results and dependent on the performance of the railway mode in the study corridor. The park-and-ride mode may not be suitable for areas with high population density. This article also investigates the travelers’ reference points on the generalized travel costs by modes. A numerical example is given to illustrate the properties of the proposed model together with some insightful findings.