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1.
ABSTRACTThe advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics. 相似文献
2.
Two-dimensional and three-dimensional Green-Naghdi (GN) models equipped with a numerical wave-absorbing beach have been developed to simulate nonlinear, regular, and irregular wave propagation. The numerical beach is introduced near the downstream boundary to absorb outgoing waves. An appropriate amount of numerical damping and an appropriate length of numerical beach are investigated using numerical experiments. The results show that the GN models with a numerical beach work very well in simulating wave propagation in water in a small computational domain. 相似文献
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Energy costs account for an important share of the total costs of urban and suburban bus operators. The purpose of this paper is to expand empirical research on bus transit operation costs and identify the key factors that influence bus energy efficiency of the overall bus fleet of one operator and aid to the management of its resources.We estimate a set of multivariate regression models, using cross-section dataset of 488 bus drivers operating over 92 days in 2010, in 87 routes with different bus typologies, of a transit company operating in the Lisbon’s Metropolitan Area (LMA), Rodoviária de Lisboa, S.A.Our results confirm the existence of influential variables regarding energy efficiency and these are mainly: vehicle type, commercial speed, road grades over 5% and bus routes; and to a lesser extent driving events such as: sudden longitudinal decelerations and excessive engine rotation. The methodology proved to be useful for the bus operator as a decision-support tool for efficiency optimization purpose at the company level. 相似文献
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车务可视化信息系统通过三维模型及虚拟漫游的展现形式,将铁路运行及运营的动态信息进行集成和柔性展示,实现旅客服务信息及运输管理相关数据的整合,通过可视化的展现方式既方便旅客及管理人员,又充分展示铁路信息化建设的成果。 相似文献
6.
Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data
Accurately modeling traffic speeds is a fundamental part of efficient intelligent transportation systems. Nowadays, with the widespread deployment of GPS-enabled devices, it has become possible to crowdsource the collection of speed information to road users (e.g. through mobile applications or dedicated in-vehicle devices). Despite its rather wide spatial coverage, crowdsourced speed data also brings very important challenges, such as the highly variable measurement noise in the data due to a variety of driving behaviors and sample sizes. When not properly accounted for, this noise can severely compromise any application that relies on accurate traffic data. In this article, we propose the use of heteroscedastic Gaussian processes (HGP) to model the time-varying uncertainty in large-scale crowdsourced traffic data. Furthermore, we develop a HGP conditioned on sample size and traffic regime (SSRC-HGP), which makes use of sample size information (probe vehicles per minute) as well as previous observed speeds, in order to more accurately model the uncertainty in observed speeds. Using 6 months of crowdsourced traffic data from Copenhagen, we empirically show that the proposed heteroscedastic models produce significantly better predictive distributions when compared to current state-of-the-art methods for both speed imputation and short-term forecasting tasks. 相似文献
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为了更好地模拟城市信号交叉口集聚车辆的跟驰行为,进而应用于城市信号交叉口信号配时和交通流理论研究,采用一种基于视频的交通流数据采集方法来采集信号交叉口的微观交通行为数据.运用灰色关联分析方法对采集到的微观交通数据进行分析,挖掘出其中的有用信息,从而寻求能够最大程度反映信号交叉口集聚车辆跟驰行为的影响变量.构建城市信号交叉口车辆集聚过程中的跟驰模型并进行参数标定、效果验证和比较分析.研究表明,新提出的跟驰模型能够很好地拟合信号交叉口集聚车辆的跟驰行为实测数据,其拟合性和稳定性优于重新标定后的扩展GM模型. 相似文献
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合流区域是高速公路常见的事故多发区域,车辆在该区域行驶时,易引起跟驰风险和变换车道风险.本文以临界加速度作为依据,结合驾驶员对向后加速度的生理心理效应,提出跟驰风险指数和变换车道风险指数的计算方法,用于定量描述单起交通行为的风险大小.最后提出平均行车风险值的概念,用于评价合流区域的安全水平. 相似文献
9.
传统的灰色聚类评价方法在确定灰类白化值时,由于受到样本数据的约束,使得评价只是在样本范围内进行比较,没有真正达到评价的目的。针对这一不足,对传统的灰色聚类评价方法进行改进,通过确立合理有效的评价指标体系,并通过相关规范标准确定灰类白化值,改变传统方法确立灰类白化值的模式,以获得一个更加合理的评价标准,使评价结果更加准确、合理。改进的灰色聚类评价方法有理论依据、算法简单、可操作性强,评价结果能更好的反映道路交通安全状况。将该方法用于3个城市的道路交通安全评价,取得了良好的效果。 相似文献
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