In search of surrogate safety indicators for vulnerable road users: a review of surrogate safety indicators

Surrogate indicators are meant to be alternatives or complements of safety analyses based on accident records. These indicators are used to study critical traffic events that occur more frequently, making such incidents easier to analyse. This article provides an overview of existing surrogate indicators and specifically focuses on their merit for the analyses of vulnerable road users and the extent to which they have been validated by previous research. Each indicator is evaluated based on its ability to consider the collision risk, which can be further divided into the initial conditions of an event, the magnitude of any evasive action and the injury risk in any traffic event. The results show that various indicators and their combinations can reflect different aspects of any traffic event. However, no existing indicator seems to capture all aspects. Various studies have also focused on the validity of different indicators. However, due to the use of diverse approaches to validation, the large difference in how many locations were investigated and variations in the duration of observation at each location, it is difficult to compare and discuss the validity of the different surrogate safety indicators. Since no current indicator can properly reflect all the important aspects underlined in this article, the authors suggest that the choice of a suitable indicator in future surrogate safety studies should be made with considerations of the context-dependent suitability of the respective indicator.     

载人潜器人因工程研究

对载人潜器人因工程的研究现状、研究范畴、技术手段和发展趋势进行梳理和总结,旨在为指导载人潜器设计总体集成优化、提高潜器综合效能、节省全寿命周期费用及缩减潜器人员编制提供参考。     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

客滚码头前沿功能区布置及交通组织仿真优化

以安全事故频发的客滚码头前沿区域作为研究对象,提出通过将该区域进行精细化布置以及合理交通组织的方式,提高码头前沿作业的安全性与便捷性。为获得区域行人密度、在港时间、行走距离及卸船作业时间等评价指标,建立客滚码头前沿作业系统微观仿真模型。并以某客滚码头泊位为例,分析码头前沿功能区布置及交通组织方案对客滚码头前沿作业评价指标的影响,并给出推荐方案。实例证明,客滚码头前沿功能区精细化布置及合理交通组织有利于减少安全事故,并提升前沿作业便捷性。     

多智能体仿真在LNG码头选址及港口规划中的应用

液化天然气(LNG)船舶进出港进行的严格交通管制会影响港口的运营,因此在港口规划阶段须审慎决策LNG码头选址及布局问题。应用自主开发的《基于多智能体信息交互的港口运营系统仿真软件(简称:APSS)V1.0》,建立可模拟涵盖LNG船舶通航影响机制的港口运营系统仿真模型;以实际工程为例,系统探讨LNG船舶通航对近、远期港口运营影响问题的思路和方法;结合水域通航环境特点提出远期优化措施。研究结果可辅助港口规划制定。     

城市交通感应控制综述

城市交通感应信号控制是一种重要的交通信号控制方法,目前被国内外许多中小城市广泛应用。简略介绍了传统的感应控制方法,重点论述了基于绿时有效利用率的感应控制、基于模糊控制和绿时有效利用率的全感应控制、具有相序优化功能的全感应控制等几种改进的感应控制算法的基本原理、控制过程及线圈安装位置,分析了各种感应控制方法的延时策略。分析了定时信号控制和感应信号控制的优缺点,最后对感应信号控制的进一步研究提出了几点看法。     

城市交叉口交通流特征与短时预测模型

时间尺度大于15 min的城市交通流预测模型已无法满足交通信号实时控制和交通信息实时发布的需求,通过对广州市中心区交叉路口交通流长期观察和数据采集,分析了各种时间尺度的交通流特性,提出以路口信号周期作为时间尺度,绿灯流率作为变量的ARIMA(p,d,q)短时交通预测模型。以1个和3个信号周期的时间尺度为例,对城市交叉路口不同时间段交通流进行建模和预测。结果表明ARIMA(p,d,q)预测模型结构稳定,算法简单,时间尺度为3个信号周期的预测模型可以很好地保持交通流特征,均方根误差为0.015 9,预测精度较高。