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。     

铈锆氧化物固溶体制备方法的比较研究

分别采用均匀沉淀法和共沉淀法制备了铈锆氧化物固溶体,研究了制备方法对铈锆氧化物固溶体的晶体结构、比表面积以及储氧能力的影响。结果表明,均匀沉淀法制备的铈锆氧化物固溶体的比表面积小,储氧能力较强,所制得的三效催化剂具有良好的催化活性,但该方法所制备的铈锆氧化物固溶体耐高温性能较差。     

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.     

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。     

基于模糊模式识别的柴油机故障诊断研究

应用时序建模方法提取特征参数 ,在提出一种隶属函数计算方法的基础上 ,运用模糊模式识别方法进行燃油喷射系统故障诊断 ,并通过喷油泵试验台上的典型故障试验进行验证。