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.     

铁岭市县乡公路网分析与评价

针对影响现状公路交通特征参数较多且各指标之间又具有相关性的实际特点，应用模糊数学基本原理建立关系矩阵，对铁岭市县乡公路网进行综合评价。     

基于神经——模糊控制的船舶操纵系统研究

本文针对船舶操纵这种非线性、时变参数控制对象，提出了一种采用神经—模糊控制的方案，给出了神经—模糊控制器的基本设计方法。仿真结果表明，这种控制器与一般自适应模糊控制器相比，船舶操纵系统的性能有明显提高。     

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.     

模糊控制变增益在曲柄箱油雾浓度检测系统中的应用

由于曲柄箱油雾浓度变化范围很大，在计算机控制系统中，必须根据油雾浓度变化而改变增益，以保证A／D转换精度，本文介绍了采用模糊算法控制增益的方法。     

模糊数据库技术在航海避碰决策支持系统中的应用

将航海避碰案例规范化 ,并根据案例中部分信息的不精确性 ,在数据库系统的数据表示和查询中引入模糊技术 ,从而形成了一个模糊关系型的避碰案例数据库系统 ,并将其嵌入到航海避碰决策支持系统当中 ,为安全航行提供了更丰富的决策信息。     

铁路隧道工程可行性研究阶段风险评估研究

风险评估对于铁路隧道工程的建设和项目选线具有重要意义。针对铁路隧道工程风险评估在可行性阶段对应的风险类别与风险因素,建立基于AHP法的多因素模糊综合评价体系以及相应的隧道风险等级定量评判标准。模型根据专家对各风险类别和风险因素相对发生概率的定性评判,通过AHP法计算得到各风险类别和风险因素在整个风险评估体系中发生的相对概率,并将风险事件发生后果等级赋予相应的风险分值。最终结合得到的概率与风险分值通过模糊综合评价得到隧道综合风险评估分值和其对应的风险等级,从而对铁路隧道工程风险进行综合、定量、直观的评估。将A隧道运用该体系进行分析评价,得到其在可行性研究阶段的综合风险评估值为4. 774,风险等级为中度。     

可编程逻辑控制器在上海轨道交通6号线设备监控系统中的应用

随着城市轨道交通的快速发展,设备监控系统越来越受到人们的关注。上海轨道交通6号线设备监控系统采用可编程逻辑控制器作为系统的核心部件。介绍了基于工业以太网构建的系统平台,分析了该系统的特点,并结合上海轨道交通6号线的具体情况,对工业以太网的实时性进行分析。     

应用模糊自适应PID和预瞄策略的自主车辆转向控制

文中结合智能车辆路径跟踪过程中转向控制方面的特点，提出了一种将模糊逻辑、预瞄规律和自适应PID控制相结合的控制策略，建立起了相应的模型，验证了该方法的可行性和有效性，并提出了进一步改进的方向。     

汽车车速巡航模糊控制

汽车巡航控制系统是一种汽车辅助驾驶系统，可以在40～200km／h的车速范围内，启动该系统，人为设定一个车速，驾驶员将不需再操控油门，系统即可自动控制汽车恒速行驶。由于汽车巡航控制系统的强非线性，以及受外界负荷的扰动、复杂的运行工况等因素影响，该系统较适合采用模糊自整定HD控制方法，以保证系统具有良好的动态稳定性。