交通信息服务条件下的出行选择分析

首先 ,探讨了出行者的出行心理、行为以及信息之间的相互关系 ,在此基础上 ,简要分析了出行者的出行选择。其次 ,考虑在交通信息服务条件下 ,由于出行者本身以及信息方面的原因 ,出行选择可能出现过激反应、集聚反应等问题。最后 ,针对上述问题 ,提出应该加以重视的或有待进一步研究的几个问题。     

基于灰色评价理论的自适应最优路径选择

充分考虑了驾驶员在路径选择中的不同要求,依据层次分析法和灰色评价理论建立了一种根据驾驶员的偏好自适应选择最优路径的方法,并设计了相应的决策支持系统,为智能交通流诱导系统的进一步发展铺平了道路。     

边角后方交会与公路路线测设

常规的交会定点方法对交会图形有一定的要求。本文讨论了边角同测的后方交会观测方法、计算原理和点位精度分析，并通过理论和实例验证了该方法的可行性。本文所述方法具有操作简便、选点灵活和不受交会图形限制等优点。     

Introduction: Habitual travel choice

In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.     

高速公路路线方案优选模型及其应用

利用灰色物元分析法,建立高速公路路线方案的优劣排序模型,对各路线方案进行多因素综合评价,为择优选择路线方案提供一种科学的评价方法。     

高速公路可变收费标准模型研究

在介绍可变收费的理论基础上,分析影响高速公路可变收费标准制定的主要因素,并讨论不同时段收费费率同交通量的关系。在设定的可变收费方案下,建立了出行者选择的二元logit模型,根据调研样本,采用最小二乘法对模型参数标定并对设定的可变收费方案进行评价,结果证明可变收费能使交通流在各时段合理分布,从而提高了高速公路的服务水平。     

建筑物受深基坑开挖影响的显式差分分析

在基坑开挖过程中，临近重要建筑物的保护是一个重要的研究课题，通过天津地铁营口道车站深基坑开挖的模拟分析可以看出，地表沉降、墙体变位、基坑隆起三者之间存在着明显的关系，临近基坑建筑物沉降变形与其基坑的接近度有明显关系，施工过程中应综合考虑技术可行性、安全、环保、质量、工期、效益等因素采取保护措施。     

大断面地铁车站隧道软弱围岩渐进破坏规律模型试验研究

以贵阳市地铁2号线阳明祠车站为背景,采用室内模型试验模拟大断面地铁车站施工过程中隧道塌方破坏过程,明确施工期间大断面隧道塌方破坏过程机制,对比分析围岩和路面的变形。结果表明:通过围岩重力作用模拟隧道施工过程中塌方过程,与实际塌方过程基本吻合,弥补了常规加载破坏的不足;围岩渐进破坏过程表现为裂隙出现-裂隙发展-裂隙贯通-围岩塌方,支护渐进破坏过程表现为变形缓慢增加-变形快速增加-裂缝快速发展-支护破坏;围岩渐进破坏与支护渐进破坏相互作用,共同发展;在实际施工过程中,当支护变形大幅增加时,应增加支护强度,同时还应及时注浆、打设长锚杆,以减缓围岩裂隙发展,阻断围岩渐进破坏过程。     

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.     

Continuum theory for pedestrian traffic flow: Local route choice modelling and its implications

This contribution puts forward a novel multi-class continuum model that captures some of the key dynamic features of pedestrian flows. It considers route choice behaviour on both the strategic (pre-trip) and tactical (en-route) level. To achieve this, we put forward a class-specific equilibrium direction relation of the pedestrians, which is governed by two parts: one part describing the global route choice, which is pre-determined based on the expectations of the pedestrians, and one part describing the local route choice, which is a density-gradient dependent term that reflects local adaptations based on prevailing flow conditions.Including the local route choice term in the multi-class model causes first of all dispersion of the flow: pedestrians will move away from high density areas in order to reduce their overall walking costs. Second of all, for the crossing flow and bi-directional flow cases, local route choice causes well known self-organised patterns to emerge (i.e. diagonal stripes and bi-directional lanes). We study under which demand conditions self-organisation occurs and fails, as well as what the impact is of the choices of the different model parameters. In particular, the differences in the weights reflecting the impact of the own and the other classes appear to have a very strong impact on the self-organisation process.