基于线性诱导的公路隧道入口区域交通安全优化研究

为达到驾驶人早发现隧道洞门、早适应环境变化、早决策驾驶行为的目的，通过分析隧道入口区域行车环境下的视距视区与交通安全问题，借鉴常见的线条形视线诱导设施（如反光环、反光条、弹性交通柱等），构建隧道线性诱导系统，并提出基于线性诱导的隧道入口区域改善方法。另外，通过室内模拟试验，采集白天与夜间环境下注视点的位置数据； 将注视区域分为5类，并分析注视点在各区域的视觉转移特性，评价隧道入口区域改善前后的效果。结果表明： 1）隧道线性诱导系统具备形式多样、较大尺寸、可以勾勒轮廓、发光分散等特点，同时可以以低成本提升隧道光环境的安全性。2）隧道入口区域改善前，驾驶人的注视点以较大概率出现在前方近处。3）改善后，驾驶人的注视点以较大的概率出现在前方远处，表明改善方案使得驾驶人的视距充足； 改善后注视点在主要分布区域的注视概率变动比改善前更为缓和，表明驾驶人的视区变化得到缓解。     

Real-time bus route state forecasting using particle filter and mesoscopic modeling

In the absence of system control strategies, it is common to observe bus bunching in transit operations. A transit operator would benefit from an accurate forecast of bus operations in order to control the system before it becomes too disrupted to be restored to a stable condition. To accomplish this, we present a general bus prediction framework. This framework relies on a stochastic and event-based bus operation model that provides sets of possible bus trajectories based on the observation of current bus positions, available via global positioning system (GPS) data. The median of the set of possible trajectories, called a particle, is used as the prediction. In particular, this enables the anticipation of irregularities between buses. Several bus models are proposed depending on the dwell and inter-stop running time representations. These models are calibrated and applied to a real case study thanks to the high quality data provided by TriMet (the Portland, Oregon, USA transit district). Predictions are finally evaluated by an a posteriori comparison with the real trajectories. The results highlight that only bus models accounting for the bus load can provide valid forecasts of a bus route over a large prediction horizon, especially for headway variations. Accounting for traffic signal timings and actual traffic flows does not significantly improves the prediction. Such a framework paves the way for further development of refined dynamic control strategies for bus operations.     

Eco-driving training of professional bus drivers – Does it work?

The drive to reduce fuel consumption and greenhouse gas emissions is one shared by both businesses and governments. Although many businesses in the European Union undertake interventions, such as driver training, there is relatively little research which has tested the efficacy of this approach and that which does exist has methodological limitations. One emerging technology employed to deliver eco-driving training is driver training using a simulator. The present study investigated whether bus drivers trained in eco-driving techniques were able to implement this learning in a simulator and whether this training would also transfer into the workplace. A total of 29 bus drivers attended an all-day eco-driving course and their driving was tested using a simulator both before and after the course. A further 18 bus drivers comprised the control group, and they attended first aid courses as well as completing the same simulator drives (before-after training). The bus drivers who were given the eco-driving training significantly improved fuel economy figures in the simulator, while there was no change in fuel economy for the control group. Actual fuel economy figures were also provided by the bus companies immediately before the training, immediately after the training and six months after the training. As expected there were no significant changes in fuel economy for the control group. However, fuel economy for the treatment group improved significantly immediately after the eco-driving training (11.6%) and this improvement was even larger six months after the training (16.9%). This study shows that simulator-based training in eco-driving techniques has the potential to significantly reduce fuel consumption and greenhouse gas emissions in the road transport sector.     

浅议快速公交系统发展中优先路权的保障

建设快速公交系统的核心要素是道路资源的优先使用,即道路优先通行权.只有为快速公交提供道路优先通行权,才能发挥其快速、便捷、集中的优势,体现其价值.本文为道路优先通行权制度的构建提出了相应的保障措施.     

公交企业在公交都市建设中的地位与任务

建设公交都市已成为大都市缓解城市交通拥堵的发展方向。本文在公交都市建设实践及研究成果的基础上，分析了常规公交在公交都市中的地位及公交企业的使命，提出了公交企业在公交都市建设中的任务体系，对公交企业的经营管理有一定的指导作用。     

面向高速公路车辆切入场景的自动驾驶测试用例生成方法

为在自动驾驶汽车基于场景的测试中生成涵盖相应场景中复杂多变的真实交通运行过程的测试用例,从highD数据集中提取车辆切入场景的多个实际样本,通过分析运动参数和参与车辆之间的位置关系,建立车辆切入场景的描述模型,根据切入点的碰撞时间评估该方案的风险程度,并结合描述模型中参数的分布,采用蒙特卡罗方法生成测试用例。结果表明,生成的车辆切入测试用例能够覆盖所有风险等级,可较好地支持自动驾驶测试。     

Big data driven dynamic driving cycle development for busses in urban public transportation

Field-relevant reference driving cycles, equivalent to real-life operation, are a prerequisite for the consistent development and testing of vehicles, their components, and control algorithms. Furthermore they are the basis for certification and type testing. However, a static cycle can easily be detected during vehicle testing, so that optimized control parameters could be used to obtain improved emission results under test conditions. In this paper, a novel method is described and applied to generate a dynamic driving cycle that statistically matches the real-life operation of a vehicle. The analysis is performed based on an extensive field data set obtained during an automated measurement campaign of public busses for more than a full year with 27,365 h of operation and 315,583 km driven in the city of Hamburg (Germany). The data collected is statistically compared to the static reference cycles New European Driving Cycle (NEDC) and Worldwide harmonized Light Vehicles Test Procedure (WLTP). Two micro trip models with increasing complexity are described and fit to the data set. All models are quantitatively compared to the measured data set applying a Quality of Fit (QoF) indicator. Based on the highest consistency to field data, a non-deterministic driving cycle generator is developed and its output is statistically compared to the original measurement. In contrast to the existing reference cycles, the dynamic output of the non-deterministic driving cycle generator presented in this paper is statistically proven to be consistent with real-life operation of public busses in the urban environment of Hamburg.     

基于坐垫体压分布的驾驶员生理状态识别方法

提出一种基于坐垫体压分布识别长途驾驶过程中驾驶员生理状态的方法.开展长途驾驶模拟试验,采集9名被试者在驾驶过程中的坐垫体压分布数据,提取82维分类特征,再采用序列浮动前向选择算法从中选出55维最优特征子空间.试验结果表明,该方法能准确识别驾驶员生理状态,贝叶斯分类正确率可达93.37％.     

Economies of density and factor substitution in Dublin city bus services — a translog approach

The primary aim of the paper is to determine a short‐run cost function for Dublin City Bus Services (DCS), using a translog approach. The results show that there are significant economies of density in the transit operation. The results also indicate that the structure of DCS is characterised by a homothetic production function and that partial elasticities of substitution are non‐unitary.     

面向老龄化社会的常规公交系统问题与对策——基于老年人常规公交出行测量模型

我国已经进入老龄化社会,老年人由于生理特性的衰退、心理特性的改变,导致其搭乘常规公交时的行为特性与需求都与一般中、低龄者不同.因此,对老年人搭乘常规公交出行的需求进行了五点量表式问卷调查,获得老年人搭乘常规公交时感受到的交通环境问题,在对数据进行统计分析、信度检验和因素分析的基础上,建立简单的结构方程模型,模型经过拟合修正后,提取了影响显著的问题因子.最后分析老年人搭乘常规公交出行时的需求,并提出老龄化社会常规公交环境的改善措施.