基于实时交通信息的行程时间估算及路径选择分析

路段行程时间的估计和预测是诱导系统的关键技术之一。由于路网参数不断变化,路段行程时间的估计必须满足实时性的要求。以城市交通控制系统的基本设施为基础,根据我国城市交通目前的发展状况,分析了影响路段行程时间的各种因素和路段行程时间的组成。利用设置在路段上的车辆自动检测装置搜集到的实时交通流信息,并结合随机服务系统的相关理论建立了城市道路路段行程时间的动态计算模型,提出了一种具有真实最短路径意义的实时动态最短路径选择的方法。     

TSP系统在隧道工程施工地质预报中的应用和发展

TSP是瑞士Amberg测量技术公司专门为隧道施工地质超前预报而设计的地震探测仪器。该系统从数据采集、处理和成果解释及评估高度智能化，其特点是：预报距离大（隧道掌子面前方至少150m），无须利用掌子面，对隧道施工妨碍小，易于操作和快速评估。通过TSP的探测，能够提前了解到掌子面前方围岩的地质情况，为施工及确定合理的支护参数提供依据，确保隧道施工安全和质量。介绍了TSP系统在隧道施工地质超前预报中的应用事例及其技术的发展。     

人工神经网络在路堤沉降预测中的应用

以人工神经网络法为主，研究了多因素条件下的沉降预测问题，同时与浅岗法和S型曲线法这2种在近几年推广应用的预测方法进行了对比。结果表明，3种方法预测的最终沉降大体相近，它们之间的区别在于人工神经网络法预测的沉降较大（同时更接近实测值）；S型曲线法较小；浅岗法居中。由于神经网络是用实测数据直接建模，少了人为干扰因素，并且偏大的数值对工程来说是偏于安全的，所以选用人工神经网络预测沉降比较适宜。     

福宁高速公路声环境探讨

通过对福建省福鼎宁德段高速公路声环境现状的调查研究,采用类比分析的方法,确定其沿线所要保护的声环境敏感点,合理科学预测交通噪声对声环境的影响,提出减轻噪声污染的若干措施。     

里双桥重建工程道路改建方案设计

合理的横断面形式、平纵线形指标、路基路面设计是城市道路改建中的关键。结合苏州老城区道路改建项目,针对现状建设条件、交通量预测结果,推荐采用三块板断面布置形式。通过拆除原侧分带、压缩非机动车道形式,使现状双向四车道实现双向六车道,同时新建侧分带保留了四排绿化,充分考虑了老城区道路绿化景观需求。拓宽新建段一般路基设计采用20 cm C20混凝土处理,路面设计根据现状弯沉值推荐了两种方案,为城市道路改建工程提供经验参考。     

数据处理方法在路堤工后沉降预测中的应用

介绍了3种预测路堤工后沉降的模型及求解方法，并应用于工程实例中；把3种方法得到的结果与实测结果相比较，指出各种方法各有优点，各有其适用情况。     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Experimental and numerical investigation on the derailment of a railway wheelset with solid axle

This paper presents the results of an experimental and numerical investigation on the derailment of a railway wheelset with solid axle. Tests were carried out under quasi-steady-state conditions, on a full-scale roller rig, and allowed to point out the effect of different parameters like the wheelset's angle of attack and the ratio between the vertical loads acting on the flanging and non-flanging wheels. On the basis of the test results, some existing derailment criteria are analysed in this paper and two new criteria are proposed. A model of wheel–rail contact is proposed for the mathematical modelling of the flange climb process, and numerical vs. experimental comparisons are used to obtain model validation.     

Logistic曲线在间歇性路堤填筑下软基沉降预测中的应用

软土路基沉降的预测是高速公路建设的一个重要部分，目前预测方法越来越多，但由于路堤填筑受到自身或者外界因素影响，使得路堤处于间歇性填筑，因此选择合理科学的预测方法至关重要。在介绍软土沉降机理和Logistic曲线性质的基础上，结合西南地区遂（宁）—资（阳）—眉（山）高速公路遂宁至资阳段软土路基沉降预测工程实例，证明Logistic曲线在间歇性路堤填筑下软土路基沉降预测应用上具有科学合理性和适用性。     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.