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.     

船舶浮态计算方法及船舶浮态图谱

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填石路堤原位抗剪试验研究

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基于零和灰色博弈模型的高速公路入口车辆冲突研究

基于灰色思想和博弈理论分析高速公路入口冲突车辆受到的不确定性因素,提出冲突车辆选择策略时受到区间灰数的约束,建立冲突车辆的零和灰色博弈模型。算例计算表明,零和灰色博弈模型客观反映了高速公路入口车辆的冲突,与实际情况很相符。     

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基于均衡流量的城市停车费用优化模型

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清水冲刷河床调整过程试验研究

通过沙质河床清水冲刷水槽试验,对河床纵剖面的调整、沙波尺度、粗化层厚度及其与沙波运动关系、粗化层级配、推移质级配等进行了观测分析,进一步揭示了清水冲刷,河床重建平衡的机理。水槽试验表明,沙质河床清水冲刷,上游河段比降调平,床沙粗化,沙波发育,河床阻力增大,水深增大,流速减小,导致河床供沙能力削弱,输沙能力降低,冲刷向不冲刷转化。     

Equilibrium analysis and route guidance in large-scale networks with MFD dynamics

Recent studies have demonstrated that Macroscopic Fundamental Diagram (MFD), which provides an aggregated model of urban traffic dynamics linking network production and density, offers a new generation of real-time traffic management strategies to improve the network performance. However, the effect of route choice behavior on MFD modeling in case of heterogeneous urban networks is still unexplored. The paper advances in this direction by firstly extending two MFD-based traffic models with different granularity of vehicle accumulation state and route choice behavior aggregation. This configuration enables us to address limited traffic state observability and to scrutinize implications of drivers’ route choice in MFD modeling. We consider a city that is partitioned in a small number of large-size regions (aggregated model) where each region consists of medium-size sub-regions (more detailed model) exhibiting a well-defined MFD. This paper proposes a route guidance advisory control system based on the aggregated model as a large-scale traffic management strategy that utilizes aggregated traffic states while sub-regional information is partially known. In addition, we investigate the effect of equilibrium conditions (i.e. user equilibrium and system optimum) on the overall network performance, in particular MFD functions.     

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.     

Dynamic activity-travel assignment in multi-state supernetworks

The integration of activity-based modeling and dynamic traffic assignment for travel demand analysis has recently attracted ever-increasing attention. However, related studies have limitations either on the integration structure or the number of choice facets being captured. This paper proposes a formulation of dynamic activity-travel assignment (DATA) in the framework of multi-state supernetworks, in which any path through a personalized supernetwork represents a particular activity-travel pattern (ATP) at a high level of spatial and temporal detail. DATA is formulated as a discrete-time dynamic user equilibrium (DUE) problem, which is reformulated as an equivalent variational inequality (VI) problem. A generalized dynamic link disutility function is established with the accommodation of different characteristics of the links in the supernetworks. Flow constraints and non-uniqueness of equilibria are also investigated. In the proposed formulation, the choices of departure time, route, mode, activity sequence, activity and parking location are all unified into one time-dependent ATP choice. As a result, the interdependences among all these choice facets can be readily captured. A solution algorithm based on the route-swapping mechanism is adopted to find the user equilibrium. A numerical example with simulated scenarios is provided to demonstrate the advantages of the proposed approach.