Exploring public transport sustainability with neutrosophic logic

Sustainable transportation is a significant component of overall sustainable development. Increasingly, evaluation and decision-making with respect to major complex projects (for example, transportation and land use projects), a multiple attribute perspective is taken. This paper illustrates a multiple attribute decision-making approach for selecting sustainable public transportation systems under uncertainty, that is, with partial or incomplete information represented by single-valued neutrosophic sets (SVNSs). A SVNS is a generalization of a classical set, a fuzzy set, and an intuitionistic fuzzy set. Here, SVNSs and SVNS connectives are illustrated in the context of a ‘Public Transit Sustainable Mobility Analysis Tool’ (PTSMAT) which involves a composite (multiple attribute) sustainability index. A case study of PTSMAT is provided for the UBC Corridor study in Vancouver, Canada. As expected, similar results are obtained to the original study, though the neutrosophic formalism opens a wide range of possibilities for recognition of uncertainty in sustainability assessment.     

Effects of new bus and rail rapid transit systems – an international review

Cities worldwide are implementing modern transit systems to improve mobility in the increasingly congested metropolitan areas. Despite much research on the effects of such systems, a comparison of effects across transit modes and countries has not been studied comprehensively. This paper fills this gap in the literature by reviewing and comparing the effects obtained by 86 transit systems around the world, including Bus Rapid Transit (BRT), Light Rail Transit (LRT), metro and heavy rail transit systems. The analysis is twofold by analysing (i) the direct operational effects related to travel time, ridership and modal shifts, and (ii) the indirect strategic effects in terms of effects on property values and urban development. The review confirms the existing literature suggesting that BRT can attract many passengers if travel time reductions are significantly high. This leads to attractive areas surrounding the transit line with increasing property values. Such effects are traditionally associated with attractive rail-based public transport systems. However, a statistical comparison of 41 systems did not show significant deviations between effects on property values resulting from BRT, LRT and metro systems, respectively. Hence, this paper indicates that large strategic effects can be obtained by implementing BRT systems at a much lower cost.     

Market dynamics and indirect network effects in electric vehicle diffusion

The diffusion of electric vehicles (EVs) is studied in a two-sided market framework consisting of EVs on the one side and EV charging stations (EVCSs) on the other. A sequential game is introduced as a model for the interactions between an EVCS investor and EV consumers. A consumer chooses to purchase an EV or a conventional gasoline alternative based on the upfront costs of purchase, the future operating costs, and the availability of charging stations. The investor, on the other hand, maximizes his profit by deciding whether to build charging facilities at a set of potential EVCS sites or to defer his investments.The solution of the sequential game characterizes the EV-EVCS market equilibrium. The market solution is compared with that of a social planner who invests in EVCSs with the goal of maximizing the social welfare. It is shown that the market solution underinvests EVCSs, leading to slower EV diffusion. The effects of subsidies for EV purchase and EVCSs are also considered.     

Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach

This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a d_p-efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed.     

Empirical analysis of free-floating carsharing usage: The Munich and Berlin case

Carsharing has become an important addition to existing mobility services over the last years. Today, several different systems are operating in many big cities. For an efficient and economic operation of any carsharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of a German free-floating carsharing system.The objectives of this paper are to describe carsharing usage and to identify factors that have an influence on the demand for carsharing. Therefore, the booking data are analyzed for temporal aspects, showing recurring patterns of varying lengths. The spatial distribution of bookings is investigated using a geographic information system and indicates a relationship between city structure and areas with high demand for carsharing. The temporal and spatial facets are then combined by applying a cluster analysis to identify groups of days with similar spatial booking patterns and show asymmetries in the spatiotemporal distribution of vehicle supply and demand.Influences on demand can be either short-term or long-term. The paper shows that changes in the weather conditions are a short-term influence as users of free-floating carsharing react to those. Furthermore, the application of a linear regression analysis reveals that socio-demographic data are suitable for making long-term demand predictions since booking numbers show quite a strong correlation with socio-demography, even in a simple model.     

Marine Shoreline Management—A 35-Year Evaluation of Outcomes in San Juan County,Washington, US

In 1976, Washington became the first state to implement the federal Coastal Zone Management Act (CZMA) primarily through the 1971 WA Shoreline Management Act (SMA). However, there has been little effort in Washington to evaluate outcomes of shoreline protection programs post SMA. In 2006–2008, we characterized shoreline conditions in San Juan County over three time periods spanning pre and post SMA and engaged community members to improve effectiveness of shoreline protection. We found modest improvements in forest retention on marine shorelines between pre and post 1977, but few other improvements through time. While we could not measure shoreline construction rates, construction practices for shore armor and overwater structures (docks) have changed very little, despite the increased regulatory standards. The vast majority of shore armor constructed post SMA occurred without mandatory county or state permits likely due to: widespread perception that permits were unnecessary and that permit standards were arbitrary and inconsistently applied; poor understanding of shoreline ecology by community members; lack of county or state enforcement authority and shoreline monitoring programs; and poor permit tracking systems.     

基于群体公平差异的公交网络双层优化模型

为准确刻画公交网络优化对不同居民群体的公平性影响,建立了考虑不同群体的人均道路占有面积、出行成本差异等因素的公交网络双层优化模型。上层模型以出行成本剥夺系数与道路面积基尼系数最小化为目标,用于求解考虑交通公平约束的公交网络优化方案;下层模型为多模式多用户随机均衡交通分配模型,用于描述上层给出的公交优化方案中不同群体对于不同交通方式的复杂选择行为。采用非劣排序遗传算法-Ⅱ求解模型,并以一个简单网络进行算例分析。结果表明：公交网络优化前,小汽车、公交车与自行车的出行分担率分别为42%,47%,11%;优化后,各出行方式的分担率分别为7%,82%,11%,部分拥有小汽车的高、中收入用户改用公交出行,3类群体的出行成本剥夺系数下降了20.68%,道路面积基尼系数下降了87.76%,低收入群体的交通公平感受与客观资源分配均显著改善。研究结果可为公交网络优化提供理论依据与模型基础,是改善交通规划方案公平性的全新尝试。     

基于铁路智能运输系统架构的货运服务系统逻辑框架建设

基于发展先进货运服务系统的迫切要求,从系统科学的思维角度出发,采用面向过程的研究方法,通过分析整套货物运输作业流程,提出了基于铁路运输系统面向货主的货运服务系统需求分析表。在充分考虑货运服务需求和系统智能化发展需求的基础上,借鉴企业架构规划思想,运用模糊聚类分析方法,构建了基于铁路智能运输系统（RITS）货运服务系统的综合服务框架,并完成了货运服务系统顶层逻辑框架DFD图,实现了RITS货运服务系统的逻辑框架功能模块的划分。     

分布式处理技术下公交信息感知挖掘系统设计

采取集中式处理技术对大规模公交信息进行处理时,传输与运算耗时长,不利于实现公交信息实时发布的需求。相比之下,公交车载智能终端可以针对单车信息进行独立感知与挖掘。由此构建基于分布式处理技术的公交信息感知与挖掘系统框架,包括公交车载智能终端、公交信息服务平台、公交调度中心三大模块。进而明确系统实施流程,并探讨公交信息挖掘软件的信息映射模型。由于分布式处理技术下的公交车载智能终端与调度中心可联网共享及交互信息,因此该系统除了实现公众信息实时发布之外,还能为交通部门的公交优先管制技术提供基础数据支撑。     

新型城镇化与交通发展

城镇化是21世纪中国发展的重大趋势。首先指出中国城镇化呈现规模巨大、高速增长的态势,同时面临城市管理者赶超心理、公共服务发展滞后的挑战。探讨中国行政管理体制下城市发展模式导致的城市面积迅速扩大、城市成本增加、引发地方发展隐性债务危机等问题。重点从交通与区域发展、交通与服务业发展、交通与城市成本、交通与房地产、交通资源配置与市场、交通配置标准与城市发展、交通港站与城市发展七方面论述新型城镇化与交通发展的关系。