Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology,application and impact evaluation

This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework’s ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.     

The generators of paratransit trips by persons with disabilities

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.     

对农村金融的差异需求与分层供给行为选择的模型分析——基于机制设计理论的视角

文章基于机制设计理论的思想和框架,建立了农村金融市场上差异需求与分层供给行为选择的相关约束机制模型,分析了相关约束机制变量对农村金融供求行为选择的影响,从而提出了通过进一步改进和完善农村金融市场相关机制变量,促进我国农村金融供求者的匹配性行为选择,改善农村金融市场效率,加强金融对“三农”支持力度的政策建议。     

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交通需求管理（TDM）已成为保障奥运会期间突增交通需求的必要手段。本文在综合奥运会交通需求特性和对比往届奥运会TDM政策要点的基础上,从控制机动车使用、设置奥运专用道、公共交通保障、错时上下班及人性化保障等5个方面阐述TDM政策在北京奥运会中的应用,并从政策综合性、可操作性、接受程度及政策实施效果等4个角度对该TDM政策进行效果评价。数据表明：TDM政策的实施使道路交通流量下降22.5%,早高峰路网平均车速提高28.5%,122报警量下降,公共交通客运量大幅上升,且公共交通的出行比例达45%以上,有效均衡了交通需求,达到预期目标。     

深圳市交通需求管理政策的法治思考

深圳市制定和实施了若干小汽车交通需求管理政策,完善相关政策的法制保障成为政策实施的关键问题。首先结合深圳市交通需求管理实践经验,梳理小汽车增量调控、停车收费政策的制定与实施情况。指出交通需求管理政策的制定与实施面临经济杠杆存在法理争议、行政手段法律依据不足和程序合法性存疑等法治障碍。进而提出在国家层面构建交通管理法治体系、在地方层面完善法律法规以及规范交通需求管理政策出台程序等完善路径。     

从供需角度看独立审计质量

随着我国市场经济的持续稳定发展,资本市场对注册会计师独立审计服务的需求与日俱增.然而近年来,大量的审计失败案例表明目前的审计服务存在着严重的质量问题.文章从经济学供需角度分析了审计服务质量低下的原因,并提出相应改进措施.     

混合能源控制技术及应用

本文介绍了混合能源控制器的功能和特点,以及多种能源混合供电的工作流程,并对混合能源的典型应用场景进行分析说明.     

2006年武汉市城市交通状况分析

从机动车保有量持续增长、私人小汽车进入家庭的步伐不断加快的问题入手,对2006年武汉市城市交通状况进行了分析:城市公共交通虽然有了一定进步,但仍然存在不少问题;城市停车缺口将继续扩大,2007年停车难将进一步加剧;重点地区如中心区、商业区与过江交通拥堵加剧,并且问题越来越严重.在此基础上,对城市交通问题提出了思考与对策,从交通供给与需求、居住与就业、交通管理与公共交通策略等几方面进行了论述,指出优先发展城市公共交通是"实施国家可持续发展、建设资源节约型社会、环境友好型社会、构建和谐社会等重大战略的重要组成部分".     

Identifying transit deserts for low-income commuters in Wuhan Metropolitan Area,China

The rapid expansion of many Chinese cities has put increasing pressure on existing urban transportation systems. Using Baidu users’ location data, this research analyzes the spatial patterns of the transit systems and commuter flows in Wuhan Metropolitan Area, China, and identifies transit deserts affecting low-income commuters. The results show that, first, most transit demand are generated by trips between neighboring communities, while large transit supply tends to occur between distant communities in the region. Second, about 11.21% of low-income commuters are affected by transit deserts in Wuhan Metropolitan Area. In detail, 61.30% of them commute within the city centers and 36.06% of them commute within the suburbs. Only about 2.64% of them actually travel between city centers and suburbs. Third, for low-income suburban commuters, transit deserts occur when they are surrounded by low-density transit infrastructure and low-frequency transit services, which makes it very difficult for them to connect to rest of the region. However, for low-income commuters residing in the city centers, transit deserts are mainly caused by the large numbers of transit-dependent people competing for limited transit supply in the areas. This research explores the relationship between transit systems and commuting demand in a major Chinese metropolitan area. The findings could help guide future transit system planning in China and beyond.     

Electric vehicle charging station locations: Elastic demand,station congestion,and network equilibrium

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design details, with applications that reflect the costs of installing, operating, and maintaining service equipment, including land acquisition. Fast electric vehicle charging stations (EVCSs) are placed across a congested city's network subject to stochastic demand for charging under a user-equilibrium traffic assignment. BEV users’ station choices consider endogenously determined travel times and on-site charging queues. The model allows for congested-travel and congested-station feedback into travelers’ route choices under elastic demand and BEV owners’ station choices, as well as charging price elasticity for BEV charging users.Boston-network results suggest that EVCSs should locate mostly along major highways, which may be a common finding for other metro settings. If 10% of current EV owners seek to charge en route, a user fee of $6 for a 30-min charging session is not enough for station profitability under a 5-year time horizon in this region. However, $10 per BEV charging delivers a 5-year profit of $0.82 million, and 11 cords across 3 stations are enough to accommodate a near-term charging demand in this Boston-area application. Shorter charging sessions, higher fees, and/or allowing for more cords per site also increase profits generally, everything else constant. Power-grid and station upgrades should keep pace with demand, to maximize profits over time, and avoid on-site congestion.