An activity-based approach of investigating travel behaviour of older people

The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.     

Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman in J Transp Econ Policy 48(3):367–384, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

高精度超短基线GAPS在水下定位中的应用

GAPS是法国IXSEA公司开发的勿需标定的便携式超短基线声学定位(USBL)惯性导航系统,集全球定位系统GPS、水下声学定位系统及姿态传感器于一体,具有安装方便、操作简单、精度高等特点.介绍高精度超短基线GAPS的安装方法、技术优势和工程中的实际应用,对使用过程中影响定位精度的主要因素、误差削弱方法进行简单分析.     

国外激光告警技术的设备与发展

激光告警技术在现代战争中发挥着越来越重要的作用。文章介绍了激光侦察告警技术的发展历程以及装备的研制、改进情况,指出了在现代战争中发展激光侦察告警技术的优势和重要性,重点探讨了几种激光侦察告警设备性能及其特点,最后论述了激光侦察告警技术与设备的发展动向与分析。     

网电一体战在现代海上作战中的应用

网电一体战在现代海上作战中的作战目标无疑是破坏和控制敌方的信息基础和战略命脉,摧毁和瘫痪敌方的作战指挥控制系统,而研究敌方的信息和作战指挥控制系统,首先要研究在现代海上作战中的大背景下,整个战场环境的特点和趋势,以便清楚地认识网电一体战的规律和特征,为信息作战的准备与实施找准依据。     

基于环境参数预测的VLF传播效应研究

基于传播媒质环境地-电离层参数的统计预测,对VLF电波的传播效应进行预测,为系统在运行中调整其可变参数或在特定参数条件下避开传播衰减与扰动,提供传播环境服务,使系统工作性能与信道特性达到良好匹配,从而提高水下通信效能。     

基于流形理论的数据分类挖掘

数据挖掘技术应用于作战指挥挖掘系统,能为指挥员的决策分析提供智能化的、自动化的辅助手段。在分析数据挖掘问题中的分类算法的基础上,利用流形结构对分类算法进行了改进。从而避免全局线性对分类信息造成的丢失,保留完整的数据结构信息,在一般意义下完成针对数据集的各项任务。     

数据挖掘技术在深度防御网络安全体系中的运用

随着攻击技术的日新月异及攻击数量的与日俱增,提高网络安全深度防御体系的效力是一个亟待解决的问题。将数据挖掘技术应用于网络安全深度防御体系中,在海量数据中挖掘有效信息、提高防御能力是一个新的思路。文章介绍了网络安全深度防御体系的概念及数据挖掘技术在网络安全深度防御体系构建中的应用。