Traffic conflicts are heavily correlated with traffic collisions and may provide insightful information on the failure mechanism and factors that contribute more towards a collision. Although proactive traffic management systems have been supported heavily in the research community, and autonomous vehicles (AVs) are soon to become a reality, analyses are concentrated on very specific environments using aggregated data. This study aims at investigating –for the first time- rear-end conflict frequency in an urban network level using vehicle-to-vehicle interactions and at correlating frequency with the corresponding network traffic state. The Time-To-Collision (TTC) and Deceleration Rate to Avoid Crash (DRAC) metrics are utilized to estimate conflict frequency on the current network situation, as well as on scenarios including AV characteristics. Three critical conflict points are defined, according to TTC and DRAC thresholds. After extracting conflicts, data are fitted into Zero-inflated and also traditional Negative Binomial models, as well as quasi-Poisson models, while controlling for endogeneity, in order to investigate contributory factors of conflict frequency. Results demonstrate that conflict counts are significantly higher in congested traffic and that high variations in speed increase conflicts. Nevertheless, a comparison with simulated AV traffic and the use of more surrogate safety indicators could provide more insight into the relationship between traffic state and traffic conflicts in the near future.

交通冲突与交通冲突密切相关，并且可以提供有关故障机制和对冲突有更大贡献的因素的深入信息。尽管研究社区已经大力支持了主动交通管理系统，并且自动驾驶汽车（AVs）很快成为现实，但分析却使用聚合的数据集中在非常特定的环境中。这项研究的目的是调查城市之间使用车辆与车辆之间的互动的第一时间-后端冲突频率，并将频率与相应的网络流量状态相关联。冲突时间（TTC）和避免崩溃的减速度（DRAC）度量标准用于估计当前网络状况以及包括AV特性的方案的冲突频率。根据TTC和DRAC阈值，定义了三个关键冲突点。提取冲突后，在控制内生性的同时，将数据拟合到零膨胀模型和传统的负二项式模型以及拟泊松模型中，以调查冲突频率的成因。结果表明，拥塞流量中的冲突计数显着更高，并且速度的高度变化会增加冲突。但是，与模拟AV流量进行比较以及使用更多替代安全指标可以在不久的将来提供对交通状态与交通冲突之间关系的更多了解。在研究内生性的同时，将数据拟合到零膨胀模型和传统的负二项式模型以及拟泊松模型中，以研究冲突频率的成因。结果表明，拥塞流量中的冲突计数显着更高，速度的高度变化会增加冲突。但是，与模拟AV流量进行比较以及使用更多替代安全指标可以在不久的将来提供对交通状态与交通冲突之间关系的更多了解。在研究内生性的同时，将数据拟合到零膨胀模型和传统的负二项式模型以及拟泊松模型中，以研究冲突频率的成因。结果表明，拥塞流量中的冲突计数显着更高，速度的高度变化会增加冲突。但是，与模拟AV流量进行比较以及使用更多替代安全指标可以在不久的将来提供对交通状态与交通冲突之间关系的更多了解。