Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The 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.     

Development of Green-Naghdi models with a wave-absorbing beach for nonlinear, irregular wave propagation

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.     

高速公路路堤填土工程适宜性评价方法的探讨

路堤填筑是高速公路路基工程的一个重要环节，路堤填土工程适宜性研究尤为重要，基于高速公路路堤填土工程性质的分析，提出了填土工程适宜性评价的一种方法，分析了其可行性和难点，以广东西部沿海高速公路某试验段为例，进行了工程适宜性评价。这将对高速公路路基施工提供新的理论依据。     

灰铸铁摩擦楔的整体表面淬火强化

介绍了货车转向架减振器铸铁摩擦楔在结构上采用倾斜面单一接触面方案,在工艺上采用整体表面淬火的效果。     

基于灰色评价理论的自适应最优路径选择

充分考虑了驾驶员在路径选择中的不同要求,依据层次分析法和灰色评价理论建立了一种根据驾驶员的偏好自适应选择最优路径的方法,并设计了相应的决策支持系统,为智能交通流诱导系统的进一步发展铺平了道路。     

路段动态特征中的交通组成因素研究

基于对交通流建模过程中将车型单一考虑为标准小汽车,忽略了现实交通量中车型的不同构成,本文通过对不同车型的动力特性进行标定,将其特性反映在跟车模型与车道变换模型中,并且利用交通仿真技术,分析了交通量构成对路段行程时间、车速、延误等动态特性指标的影响。     

Influential vectors in fuel consumption by an urban bus operator: Bus route,driver behavior or vehicle type?

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.     

车务可视化信息系统设计与实现

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。     

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.     

基于灰色关联度的船舶风险控制方案多指标评价模型

分析了仅依靠成本效益评估而选择的船舶风险控制方案的片面性,综合考虑安全、环保、经济收益、成本等多因素对方案所表现的影响,建立了基于灰色关联度的船舶风险控制方案多指标评价模型。论文所建立的该模型可以充分利用各方案的指标取值所包含的信息,并考虑专家主观因素对指标重要度的影响,通过主客观综合赋权的方法突出某个指标在方案排序中的作用。以国际海事组织对液化天然气船的综合安全评估报告所提供的风险控制措施为例,使用该模型进行方案优选,并与仅用成本效益评估所得结果比较;分析比较表明:论文所建立的多指标评价模型可以更全面评估风险控制方案,方法合理,使用简便可靠。