Modeling duration choice in space–time multi-state supernetworks for individual activity-travel scheduling

Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies and emerging modalities. However, duration choice of activities and home-stay has not been incorporated in this formalism yet. This study models duration choice in the state-of-the-art multi-state supernetworks. An activity link with flexible duration is transformed into a time-expanded bipartite network; a home location is transformed into multiple time-expanded locations. Along with these extensions, multi-state supernetworks can also be coherently expanded in space–time. The derived properties are that any path through a space–time supernetwork still represents a consistent activity-travel pattern, duration choice are explicitly associated with activity timing, duration and chain, and home-based tours are generated endogenously. A forward recursive formulation is proposed to find the optimal patterns with the optimal worst-case run-time complexity. Consequently, the trade-off between travel and time allocation to activities and home-stay can be systematically captured.     

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.     

Incorporating space–time constraints and activity-travel time profiles in a multi-state supernetwork approach to individual activity-travel scheduling

Activity-travel scheduling is at the core of many activity-based models that predict short-term effects of travel information systems and travel demand management. Multi-state supernetworks have been advanced to represent in an integral fashion the multi-dimensional nature of activity-travel scheduling processes. To date, however, the treatment of time in the supernetworks has been rather limited. This paper attempts to (i) dramatically improve the temporal dimension in multi-state supernetworks by embedding space–time constraints into location selection models, not only operating between consecutive pairs of locations, but also at the overall schedule at large, and (ii) systematically incorporate time in the disutility profiles of activity participation and parking. These two improvements make the multi-state supernetworks fully time-dependent, allowing modeling choice of mode, route, parking and activity locations in a unified and time-dependent manner and more accurately capturing interdependences of the activity-travel trip chaining. To account for this generalized representation, refined behavioral assumptions and dominance relationships are proposed based on an earlier proposed bicriteria label-correcting algorithm to find the optimal activity-travel pattern. Examples are shown to demonstrate the feasibility of this new approach and its potential applicability to large scale agent-based simulation systems.     

基于整体规划框架的区域综合货运规划建模方法研究

区域一体化快速发展背景下，如何系统谋划区域综合交通运输规划，使经济、土地/空间及交通与环境协调发展，是实现区域可持续发展亟需深入研究的课题。因此，本文统筹考虑经济、 土地/空间及交通和环境要素的动态交互关系，提出大区域综合货运整体规划模型的设计与开发方法。利用PECAS(Production, Exchange and Consumption Allocation System)理论框架分析生产者、消费者、交换商品、土地(空间)和运输方式之间的交互关系，并通过PECAS的集计经济流表设计模型结构，构建相应的宏观经济预测、社会经济活动空间分配、空间开发以及交通运输需求预测这4个模块，模拟区域社会经济活动增长及其空间分布与土地/空间开发及综合交通需求时变等特征之间的互动耦合关系。在社会经济发展目标、土地空间和环境等约束条件下，通过构建空间经济模型和综合交通一体化网络分配模型，实现面向多货品和多方式的综合货运整体规划建模方法，以辅助区域产业布局、土地利用与综合交通系统的整体规划。本文以长江经济带为研究案例，基于相关数据构建相应的大区域综合货运整体规划模型，分析评估2012—2035年模型预测结果。结果显示，预测得到的综合交通年平均日货运量拟合优度超过85%，分担率误差低于1%， 验证了本文建模方法的有效性。     

基于超网络的装备保障信息化模型构建及分析

装备保障信息化是由信息、技术、物资、装备和人员等诸多要素所构成,为清晰呈现装备保障信息化构成要素之间的关系,将装备保障信息化作为一个复杂系统,利用超网络相关理论进行分析,构建了装备研制子网络、装备使用子网络和装备维修子网络,描述各阶段人、技术、装备之间的相互关系;在此基础上形成装备保障信息化网络,覆盖装备研制-使用-维护-报废全寿命周期的过程,形象描述人、武器装备和人与武器装备结合的构成关系,对装备保障信息化的系统动力学研究提供了基于超网络的研究思路.