Using survival models to estimate bus travel times and associated uncertainties

Transit agencies often provide travelers with point estimates of bus travel times to downstream stops to improve the perceived reliability of bus transit systems. Prediction models that can estimate both point estimates and the level of uncertainty associated with these estimates (e.g., travel time variance) might help to further improve reliability by tempering user expectations. In this paper, accelerated failure time survival models are proposed to provide such simultaneous predictions. Data from a headway-based bus route serving the Pennsylvania State University-University Park campus were used to estimate bus travel times using the proposed survival model and traditional linear regression frameworks for comparison. Overall, the accuracy of point estimates from the two approaches, measured using the root-mean-squared errors (RMSEs) and mean absolute errors (MAEs), was similar. This suggests that both methods predict travel times equally well. However, the survival models were found to more accurately describe the uncertainty associated with the predictions. Furthermore, survival model estimates were found to have smaller uncertainties on average, especially when predicted travel times were small. Tests for transferability over time suggested that the models did not over-fit the dataset and validated the predictive ability of models established with historical data. Overall, the survival model approach appears to be a promising method to predict both expected bus travel times and the uncertainty associated with these travel times.     

《铁路信号显示的发展与思考》之二——多种显示制式的混用

由于混运、兼运的需求,再加故障备用模式,导致在同一线路上显示制式常常混用,情况复杂。不同的显示制式有不同显示方式,原则和规定,与行车有关的人员应当熟悉。     

Identifying multiclass vehicles using global positioning system data

It has been previously evidenced that global positioning system (GPS) data can be used to distinguish passenger cars from delivery trucks. In this paper, a machine learning approach is proposed to use GPS data to identify multiclass vehicles, including passenger cars, single unit trucks, and multi-trailer trucks. The method is acceleration and deceleration-based since it considers the variations of acceleration and deceleration as the most effective features to classify vehicles. The overall classification result for the three vehicle classes is about 75%. The major challenge is to distinguish single unit trucks from multitrailer trucks due to their somewhat similar mobility patterns. The paper also explores the impacts of GPS sampling frequency on vehicle classification. It is found that the proposed multiclass vehicle classification can be reasonably conducted if the data are collected frequently enough (i.e., every five seconds or more frequently) to capture the major acceleration and deceleration processes. The proposed method can be considered as a low-cost and non-intrusive approach to collect vehicle class information and to potentially supplement the existing classification schemes in urban areas.     

Development and evaluation of bus lanes with intermittent and dynamic priority in connected vehicle environment

Exclusive bus lanes provide a very high level of priority for transit operations, especially for Bus Rapid Transit and Express service, but these lanes could be underutilized and be a source of extra capacity if they could be shared in an intelligent way. This article explores the benefits of providing intermittent priority, called bus lane with intermittent and dynamic priority, of these exclusive bus lanes. Intermittent and dynamic priority can be implemented by allowing vehicles to use the lane when Bus Rapid Transit or Express bus is not present. Drivers can be alerted when a bus is in the lane using either infrastructure-based signs, or in the future using infrastructure-to-vehicle, or connected vehicle communications. Some critical operating parameters for implementing bus lane with intermittent and dynamic priority system including clear distance, degree of saturation (volume-to-capacity ratio), connected vehicle penetration, and bus departure/headway frequency have been investigated in this paper.     

整车排气系统匹配研讨

发动机被公认为汽车的心脏,随着法规及人类环境意识的增强,针对发动机排放提出的要求也越来越高。排气系统对降低排气损失、保证发动机良好的性能、合理控制及减少污染物排放、发动机排气噪声控制都起到了关键性作用。因此排气系统匹配对整车来说至关重要,本文研讨了整车排气系统的基本匹配方法,为以后其它产品的开发提供了参考。     

河北省高速公路机电系统养护项目入库研究

河北省对高速公路机电工程养护项目进行了分类,统一了入库名称和入库原则,避免了同样的内容不同的提法,使每条路段有章可循。同时,根据每年的实际情况,辅以应急项目、调整项目等措施,提高了项目管理的效率,保证了养护资金的投入和使用。     

基于模糊理论的运输质量自动评价系统

针对公路货物运输企业的主要特点,结合公路货物运输企业运输质量评价指标体系,运用模糊评价理论对运输质量的综合评价进行分析,并根据上诉评价方法给出建立一套公路货物运输企业运输质量自动评价系统的总体结构,对公路货物运输企业的运输质量管理有一定的参考价值。     

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在城市交通网络中,每个交通小区的交通发生量以及吸引量与其经济发展水平、土地利用、人口数量等因素密切相关,通常能够较为准确的预测,而小区之间的交通需求很难准确的预测. 本文假定所有起讫点的交通发生量和吸引量是确定的,而OD需求不确定且属于一个有界区间,利用鲁棒优化的方法建立OD需求不确定环境下考虑用户均衡约束的交通网络设计极小极大模型,并提出了灵敏度分析结合相继平均法(MSA)的求解算法. 数值算例表明,利用鲁棒优化方法得到的网络设计方案较传统的确定性网络设计方案具有更高的可靠性.     

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交通拥挤不仅是当今许多大城市日益严重的社会问题,同时也给国家和城市造成巨大的经济损失.引发拥挤的直接原因是机动车辆保有量的迅速增加和交通设施/服务的相对落后,但对于不同的城市和地区,其深层原因存在差异.本文定位于研究宏观路网交通拥挤内在成因和演化规律,采用地理建模的仿真平台,使用地理信息系统（GIS）技术将FCD数据与深圳市地图匹配,得到城市路网不同时间点的拥挤状态,定性分析区域内交通拥挤的成因.另外,研究针对路段拥挤的相似程度,提出相关性算法进行定量分析,揭示交通拥挤的时空演变规律,为及时采取预防和疏导措施提供指导.该算法可编程实现,对交通拥挤进行统一管理与控制,提高整个交通系统的效率.     

基于GPS技术的运输管理系统在钢铁企业中应用研究

如何应用基于GPS技术的运输管理系统对物流运输车辆进行有效指挥、协调控制和管理已经成为现代物流企业面临的一个重要课题。本文介绍了GPS基本组成与功能,分析了基于GPS技术的运输管理监控系统的原理,结合实际案例阐述了基于GPS技术的运输管理系统在现代物流企业中的应用及效果评价。