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.     

Emission rates of intermodal rail/road and road-only transportation in Europe: A comprehensive simulation study

Intermodal rail/road transportation combines advantages of both modes of transport and is often seen as an effective approach for reducing the environmental impact of freight transportation. This is because it is often expected that rail transportation emits less greenhouse gases than road transportation. However, the actual emissions of both modes of transport depend on various factors like vehicle type, traction type, fuel emission factors, payload utilization, slope profile or traffic conditions. Still, comprehensive experimental results for estimating emission rates from heavy and voluminous goods in large-scale transportation systems are hardly available so far. This study describes an intermodal rail/road network model that covers the majority of European countries. Using this network model, we estimate emission rates with a mesoscopic model within and between the considered countries by conducting a large-scale simulation of road-only transports and intermodal transports. We show that there are high variations of emission rates for both road-only transportation and intermodal rail/road transportation over the different transport relations in Europe. We found that intermodal routing is more eco-friendly than road-only routing for more than 90% of the simulated shipments. Again, this value varies strongly among country pairs.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

扎（木）墨（脱）公路病害分析与处治

文章结合扎墨简易公路便道整修工程实践,介绍了扎墨公路沿线地质的工程特性、分类以及该路线上的公路病害情况,提出了相应的病害处治措施及在扎墨公路沿线区域进行公路工程施工应注意的问题。     

旧路加宽路面纵向开裂原因分析与防治

针对公路改建工程中出现的沥青路面纵向开裂这一常见现象,结合省道改建工程的设计特点与施工要点,重点就加宽路基部位与路面各结构层的施工质量控制方面进行分析和阐述,提出施工控制方法及相应的处理措施。     

广东省道路交通安全目标管理体系研究

安全目标管理是现代化管理技术在安全管理上的应用,在进行广泛调查和专家咨询的基础上,结合广东省道路交通安全实际,提出了构建广东省道路交通安全目标控制指标体系,并讨论了该体系的实施和评价等相关问题.     

城市地下道路入口智能控制系统设置及技术研究

当前城市地下道路建设越来越多,在城市交通体系中承担着重要作用,然而在水淹、火灾等紧急情况下,因未及时管控地下道路车辆而造成人员伤亡、财产损失的问题也时有发生,地下道路的运行安全面临挑战。通过对地下道路入口控制方法、总体方案、设备要求等开展研究,提出地下道路关闭多级预警、建立物理拦截需求和安全高效的控制系统等建议。通过文献、需求调研、技术比选验证,提出了包含物理控制设施、车道信号灯、交通感知设施、信息发布设施、声光警示设施的地下道路入口智能控制系统、控制流程及其主要的技术要求等方案,并结合广州南沙横沥岛尖地下环路的实例开展了方案设计和工程应用。研究提出的地下道路入口智能控制系统可以提升紧急工况下地下道路入口的交通控制效率,提升地下道路安全水平。     

上拔、水平联合荷载对桩基承载性能影响的现场试验及数值模拟

通常桩基受力作用分别确定上拔、水平2个方向的承载力,不考虑其相互影响,不能准确反映桩基的真实受力状况.为研究桩基上拔、水平荷载的耦合作用对桩基上拔、水平向承载性能的影响,开展了大型现场试验及数值模拟研究.研究结果表明:上拔、水平联合荷载对桩基承载性能的影响与上拔、水平向荷载的比例有较大关系,当该比例小于2时,联合荷载作...     

土体固结剂(HEC)在军事工程中的应用探讨

根据高强高耐水土体固结剂(HEC)的性能和特点,结合现代军事工程的要求,分析了HEC在军用道路工程、野战防护工程以及海岸港口等军事工程的应用可行性,探讨了如何在军事工程中的应用问题。