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Driving behavior differences between crash-involved and crash-not-involved drivers using urban traffic surveillance data

机译:使用城市交通监控数据,撞车和不撞车驾驶员的驾驶行为差异

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With technology such as in-vehicle data collection systems, driving data including mileage, speed, acceleration can be collected and analyzed by many researchers. However, in these studies, data could be collected only from a few selected drivers. In addition, drivers knowing that they were participating experiments might drive differently from natural. Furthermore, few researches took advantage of headway, which requires data from not only objective vehicles but also vehicles nearby. Many urban traffic surveillance systems built in recent years have brought new opportunities for researches. In this paper, urban traffic surveillance data at both intersections and road segments were used, so that data of numerous vehicles including objective vehicles and vehicles nearby could be collected, and indicators such as headway of vehicles could be calculated. The differences of driving behavior between crash-involved and crash-not-involved drivers were then analyzed. It was found that crash-involved drivers tended to keep less headways than crash-not-involved drivers when driving through intersections in everyday driving behavior. In the days before the crashes, this tendency of male drivers was stronger than female drivers. For road segments, compared with crash-not-involved drivers, crash-involved drivers' headways were seen less, and crash-involved drivers' speeds under free flow condition were seen larger at certain time frames. The result suggests that there is a great potential to taking advantage of urban traffic surveillance data to identify at-risk drivers.
机译:利用诸如车载数据收集系统之类的技术,许多研究人员可以收集并分析包括里程,速度,加速度在内的驾驶数据。但是,在这些研究中,只能从几个选定的驱动程序中收集数据。此外,知道自己正在参加实验的驾驶员可能会与自然驾驶有所不同。此外,很少有研究利用车距,这不仅需要目标车辆的数据,而且还需要附近车辆的数据。近年来建立的许多城市交通监控系统为研究带来了新的机会。本文利用交叉口和路段的城市交通监控数据,可以收集包括目标车辆和附近车辆在内的众多车辆的数据,并可以计算出车辆的行驶距离等指标。然后,分析了撞车驾驶员和不撞车驾驶员之间的驾驶行为差异。研究发现,在日常驾驶行为中,在交叉路口行驶时,与撞车有关的驾驶员比未撞车的驾驶员趋向于保持更少的行驶距离。在撞车事故发生的前几天,男性驾驶员的这种趋势要强于女性驾驶员。对于路段,与不涉及碰撞的驾驶员相比,在某些时间范围内,与碰撞无关的驾驶员的行驶距离较小,并且在自由流动条件下,与碰撞相关的驾驶员的速度较大。结果表明,利用城市交通监控数据来识别高风险驾驶员具有很大的潜力。

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