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.     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.     

Travel analytics: Understanding how destination choice and business clusters are connected based on social media data

Understanding how destination choice and business clusters are connected is of great importance for designing sustainable cities, fostering flourishing business clusters, and building livable communities. As sharing locations and activities on social media platforms becomes increasingly popular, such data can reveal destination choice and activity space which can shed light on human-environment relationships. To this end, this research models the relationship between characteristics of business clusters and check-in activities from Los Angeles County, California. Business clusters are analyzed via two lenses: the supply side (employment data by industry) and the demand side (on-line check-in data). Spatial and statistical analyses are performed to understand how land use and transportation network features affect the popularity of the identified clusters and their relationships. Our results suggest that a cluster with more employment opportunities and more types of employment is associated with more check-ins. A business cluster that has access to parks or recreational services is also more popular. A business cluster with a longer road network and better connectivity of roads is associated with more check-ins. The visualization of the common visitors between clusters reveals that there are a few clusters with outstanding strong ties, while most have modest ties with each other. Our findings have implications on the influence of urban design on the popularity of business clusters.     

高架快速路上跨宝鸡东编组站方案比选

宝鸡市斗中路高架快速路,跨越宝鸡东编组站的10股轨道线和铁路专用线,同时桥下的城市主干路以框架桥的形式下穿宝鸡东编组站。桥位处需保留现状的地面交通、铁路框架桥和周围的高层建筑,桥址处空间局促,建设条件复杂,导致桥梁墩位布置困难。桥梁的布置方案与施工方案相互影响和制约。上跨方案是控制整条快速路的关键节点。综合考虑主墩的合理位置、恰当的孔跨布置和适宜的施工方案,对矮塔斜拉桥、刚构桥等方案进行详细的对比分析,确定采用(97+97)m的转体刚构桥方案。该方案的安全性和经济性均较优。该桥方案的研究过程和方法,为类似的复杂城市环境下,建设高架桥梁跨越铁路编组站提供参考和借鉴。