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.     

A new solution for two-bag air suspension system with leaf spring for heavy-duty vehicle

The design problem of a two-bag air suspension system for heavy-duty vehicles is formulated as a two-level (suspension system level and component level) optimization problem. At the suspension system level, optimal stiffness matrix of leaf spring, characteristics of damper and upper rod layout are determined by solving a multi-objective constrained optimization problem with response surface. At the component level, shape and thickness of the leaf spring are formed using cubic-spline curves to make the stiffness matrix as close to the target values cascaded from suspension system level as possible. Simulations using a vehicle model described by multi-body model and FEM of the novel leaf spring validate the suspension system thus derived.     

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.     

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。     

Hierarchal assessment of noise pollution in urban areas – A case study

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors.     

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。     

基于群决策层次理论的预防性养护方案决策

基于高速公路预防性养护决策方案选择的特性,使用群决策理论的层次分析法,通过对决策组成员意见的集合,得到了各成员动态权重,减少主观误差,提高决策方案结果的客观可靠性。通过案例,将措施费用、行车特征、技术因素、施工因素等作为目标层,对4种备选方案进行分析,得出最佳措施。案例结果证明群决策方法的有效性与可靠性,为选择合理的养护措施提供参考。     

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.     

改进的道路交通安全灰色聚类评价方法

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。