Within day rescheduling microsimulation combined with macrosimulated traffic

The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.     

(Unintended) Transport impacts of an energy-environment policy: The case of CNG conversion of vehicles in Dhaka

Motor vehicles are one of the major sources of air pollution in Dhaka, the capital of Bangladesh. The government took various policies to convert the petroleum vehicles on road to run on compressed natural gas (CNG), which allows both air quality improvements and energy security benefits. One of the market friendly policies to encourage the fuel switch was to increase the price differential between CNG and petrol and diesel. This has allowed a wide-scale adoption of CNG as the fuel of choice. However, several years into the policy, there is now a widespread belief among the policymakers that the CNG conversion may have increased car ownership and car travel due to their lower running costs, resulting in more congestion and a reversal of the strategy is on the cards. It is therefore important to test the hypothesis whether CNG conversion had genuinely increased car ownership and car travel in Dhaka city. This paper presents the results of a questionnaire survey and an econometric intervention analysis to understand the impact of CNG conversion on car ownership and car travel in Dhaka. Attention is also given to disentangle the self-selection and price-induced travel effects of CNG conversion. Results show that ownership did not increase, but travel of on-road vehicles increased due to the CNG policy. However, additional congestion costs are still around one half of the health benefits brought about by the policy.     

Privacy protection method for fine-grained urban traffic modeling using mobile sensors

With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors.     

装载机连杆机构优化设计

结合传统设计方法和现代优化方法有效地解决了原设计中装载机不能满足平移性和自动放平性的问题;在用作图法确定铰接点大致位置的基础上,建立了连杆机构参数化模型,并对模型进行了优化研究。结果表明:新机构能满足平移性和自动放平性要求。该方法对类似的机构优化问题有一定的参考价值。     

基于非集计与弹性联合模型的交通需求分析

随着我国交通事业的蓬勃发展,人们对交通方式的需求正在不断发生变化。基于科学研究的交叉性和外延性,将不同研究领域已经基本成熟的模型,即微观经济学中的费用效益弹性理论模型和交通方式分布中的非集计模型(Logit模型)有机地结合并融为一体,得到一种联合模型,使其更容易将数据定量化、具体化。通过这个联合模型来分析交通需求并将与交通需求相关的因素进行对比,得出交通因素发生变化对交通需求者和供给者的影响。     

基于浑沌神经网络的动态交通量预测方法研究

介绍了目前国内外道路交通量预测的方法、特点及实际的预测效果.由于城市道路交通的复杂性,使得一些现有交通量预测方法的预测精度不高.针对这些问题,应用混沌神经网络,建立了城市道路交叉口出口交通量的浑沌神经网络预测模型,并与传统的BP神经网络预测结果对比,表明此模型具有较好的预测效果.     

城市大断面明开平顶隧道结构设计浅述

该文以北京成府路隧道设计为例,介绍了该隧道的建设概况及主要设计原则,阐述了平顶隧道主体结构的确定及其计算,同时,通过对比介绍了该隧道的防水设计,最后对新材料、新工艺在平顶隧道结构中的应用进行了介绍和分析。     

粉煤灰加筋土挡墙工作机理的离心模型试验研究

将能够完全满足模型相似律的离心模型试验方法应用于粉煤灰加筋挡墙研究中。试验基于整体刚性面层加筋土挡墙结构研究了粉煤灰加筋土挡墙的工作机理、筋材中的应变分布、粉煤灰加筋挡墙的变形。结果表明,加筋土挡墙所发生的侧向位移量远小于素土无加筋挡墙的位移量,且加筋层竖向间距越小,加筋层越密,相对侧向位移量越小,加筋效果越明显;因粉煤灰填筑密度较轻,加筋后的挡墙所发生的相对侧向位移量较小,说明加筋效果明显。     

城市出租车交通分布预测模型

现有交通需求预测方法以居民出行分析为基础,预测得出的出租车交通分布量实质上是载客出租车的交通分布量,因此其预测值比实际值偏小.基于出租车的运行规律,提出了出租车出行概念,将系统中出租车总出行量分解为载客出租车出行量和空驶出租车出行量,并运用Logit概率选择模型,建立了载客出租车出行量与空驶出租车出行量之间的关系,从而得出了总体出租车的交通分布预测方法.该方法既可以模拟城市现状的出租车交通分布状况,也可以对规划年出租车的交通分布进行预测,避免了传统分析方法对空驶出租车交通量的疏漏.     

微观交通流仿真一体化环境研究

针对国内交通仿真研究的零散性和解决问题的单一性等特点，结合项目组开发的仿真软件，提出了微观交通流仿真一体化环境的结构和功能，按照面向对象、面向消息和模块化建模的思想对一体化仿真的理论框架以及构建一体化仿真环境的关键技术进行了探讨。