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.     

真空断路器凸轮操作机构的优化

基于对真空断路器凸轮操作机构的分析,建立了相应的数学模型,并通过所建立的模型,对凸轮机构进行了优化设计。结果表明,所建立的数学模型为真空断路器凸轮操作机构提供了一种有效的优化设计方法。     

惯性摩擦制动对铜基粒子材料摩擦磨损性能的影响

采用粉末冶金工艺制备了多组元的铜基摩擦材料,利用GF150D型摩擦试验机,分别在不同的摩擦方式和不同的摩擦条件下,探讨了材料的摩擦磨损性能.结果表明:惯性摩擦条件下,随着摩擦压力提高,磨损量增加,摩擦系数降低.且在其他摩擦条件相同时惯性摩擦条件下的摩擦系数低于定速.惯性试验湿摩擦的摩擦系数比干摩擦的摩擦系数有显著提高,摩擦顺序为高速到低速时的摩擦系数的稳定性都高于摩擦顺序为低速到高速.     

山区高速公路桥隧相连技术的研究与应用

通过研究山区高速公路隧道洞口桥隧相连的有关技术及其在实际工程中的合理选择与应用,分析其优缺点,并总结经验,对类似条件下桥梁与隧道的建设具有一定的指导意义。     

干线公路沥青路面养护大中修工程方案设计探讨

结合某干线路面大中修工程方案设计中的路况调查结果,对其路面使用品质加以评价,有利于得出合理的路面大中修方案。     

智慧校园环境下课程资源建设的实践研究 ——以汽修专业《汽车空调原理与检修》课程建设应用为例

为研究智慧环境下课程资源建设,文章以《汽车空调原理与检修》课程建设应用为例,通过建设该教学平台,实现线上线下教学的有机结合,可以有效提升教师的教学质量及教学效率,还可以为那些渴望更深层次知识的学生提供一个良好的学习平台.在"智慧校园"的建设和发展过程中,需要不断更新与教学相关的信息,因此建设《汽车空调原理与检修》课程教...     

浅谈紧凑型SUV车发盖电泳二次流痕的成因与解决

对紧凑型SUV车发盖电泳二次流痕缺陷的形成原因进行了描述和分析,探讨了导致紧凑型SUV车发盖电泳二次流痕缺陷形成的机理.主要从涂装工艺、车身产品结构以及工件夹层涂黑胶工艺等多方面对电泳二次流痕缺陷形成进行探讨和分析,并提供了一些预防及解决方法.     

基于三维模型重构技术的公路预制构件尺寸检验评价方法

为使公路工程异形混凝土预制构件的制造尺寸检验评价适应工业化建造要求,应用三维模型重构技术检验评价了异形混凝土预制构件尺寸,提出了高精度、自动化异形混凝土预制构件尺寸检验评价方法,包括三维模型重构、点云数据处理和检验评价体系3个环节;总结了基于三维摄影的点云模型重构技术的原理和关键环节,研究了基于坐标转换和包围盒的无关点云自动剔除算法,并通过2个实例验证了该算法的效果;研究了点云整体配准和3类局部配准方法,针对不同形状的构件和不同位置的细部构造,结合工程需求进行对照;考虑工程需求并与配准方法对应,提出了基于彩色误差云图和数理统计方法进行构件尺寸检验评价的3种判异原则,包括误差均值和标准差判异原则、误差极值判异原则、综合判异原则;综合分析彩色误差云图和误差分布,利用判异原则对箱型涵洞侧墙和管型涵洞侧墙实例的尺寸进行了检验评价。研究结果表明：3种判异原则分别适合对预制构件进行整体宏观、局部单项和先整体后局部的检验评价;采用三维模型重构技术建立的异形混凝土预制构件点云模型,与实际构件相比其长度和宽度的误差均值约为1.5 mm,三维模型重构技术可以替代人工测量;能够自动化剔除无关点云,并执行更为严格且符合工程需求的构件尺寸检验评价。     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

Integrated vehicle and powertrain optimization for passenger vehicles with vehicle-infrastructure communication

This research proposes an optimal controller to improve fuel efficiency for a vehicle equipped with automatic transmission traveling on rolling terrain without the presence of a close preceding vehicle. Vehicle acceleration and transmission gear position are optimized simultaneously to achieve a better fuel efficiency. This research leverages the emerging Connected Vehicle technology and utilizes present and future information—such as real-time dynamic speed limit, vehicle speed, location and road topography—as optimization input. The optimal control is obtained using the Relaxed Pontryagin’s Minimum Principle. The benefit of the proposed optimal controller is significant compared to the regular cruise control and other eco-drive systems. It varies with the hill length, grade, and the number of available gear positions. It ranges from an increased fuel saving of 18–28% for vehicles with four-speed transmission and 25–45% for vehicles with six-speed transmission. The computational time for the optimization is 1.0–2.1 s for the four-speed vehicle and 1.8–3.9 s for the six-speed vehicle, given a 50 s optimization time horizon and 0.1 s time step. The proposed controller can potentially be used in real-time.