Laureshyn Aliaksei, Goede Maartje de, Saunier Nicolas, Fyhri Aslak
Dept. of Technology & Society, Faculty of Engineering, LTH, Lund University, Box 118, 22100 Lund, Sweden; Institute of Transport Economics, Gaustadalléen 21, NO-0349 Oslo, Norway.
Traffic Behaviour, TNO, Kampweg 5, 3769 DE Utrecht, The Netherlands.
Accid Anal Prev. 2017 Aug;105:11-20. doi: 10.1016/j.aap.2016.04.035. Epub 2016 Jun 8.
Relying on accident records as the main data source for studying cyclists' safety has many drawbacks, such as high degree of under-reporting, the lack of accident details and particularly of information about the interaction processes that led to the accident. It is also an ethical problem as one has to wait for accidents to happen in order to make a statement about cyclists' (un-)safety. In this perspective, the use of surrogate safety measures based on actual observations in traffic is very promising. In this study we used video data from three intersections in Norway that were all independently analysed using three methods: the Swedish traffic conflict technique (Swedish TCT), the Dutch conflict technique (DOCTOR) and the probabilistic surrogate measures of safety (PSMS) technique developed in Canada. The first two methods are based on manual detection and counting of critical events in traffic (traffic conflicts), while the third considers probabilities of multiple trajectories for each interaction and delivers a density map of potential collision points per site. Due to extensive use of microscopic data, PSMS technique relies heavily on automated tracking of the road users in video. Across the three sites, the methods show similarities or are at least "compatible" with the accident records. The two conflict techniques agree quite well for the number, type and location of conflicts, but some differences with no obvious explanation are also found. PSMS reports many more safety-relevant interactions including less severe events. The location of the potential collision points is compatible with what the conflict techniques suggest, but the possibly significant share of false alarms due to inaccurate trajectories extracted from video complicates the comparison. The tested techniques still require enhancement, with respect to better adjustment to analysis of the situations involving cyclists (and vulnerable road users in general) and further validation. However, we believe this to be a future direction for the road safety analysis as the number of accidents is constantly decreasing and the quality of accident data does not seem to improve.
依靠事故记录作为研究自行车骑行者安全的主要数据源存在诸多弊端，比如漏报程度高、缺乏事故细节，尤其是缺乏导致事故的交互过程信息。这也是一个伦理问题，因为人们必须等待事故发生才能对自行车骑行者的（不）安全状况发表看法。从这个角度来看，基于交通实际观测的替代安全措施的使用前景广阔。在本研究中，我们使用了挪威三个十字路口的视频数据，所有数据均分别采用三种方法进行分析：瑞典交通冲突技术（Swedish TCT）、荷兰冲突技术（DOCTOR）以及加拿大开发的概率性替代安全措施（PSMS）技术。前两种方法基于对交通中关键事件（交通冲突）的人工检测和计数，而第三种方法考虑每次交互的多条轨迹的概率，并生成每个地点潜在碰撞点的密度图。由于大量使用微观数据，PSMS技术严重依赖视频中道路使用者的自动跟踪。在这三个地点，这些方法显示出相似性，或者至少与事故记录“兼容”。两种冲突技术在冲突的数量、类型和位置方面相当吻合，但也发现了一些无明显解释的差异。PSMS报告了更多与安全相关的交互，包括不太严重的事件。潜在碰撞点的位置与冲突技术所表明的情况相符，但由于从视频中提取的轨迹不准确而可能产生的大量误报使比较变得复杂。所测试的技术仍需改进，以便更好地适用于涉及自行车骑行者（以及一般弱势道路使用者）的情况分析，并进行进一步验证。然而，我们认为这是道路安全分析的未来方向，因为事故数量在不断减少，而事故数据的质量似乎并未提高。
