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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驾驶涉及碰撞和崩溃的司机之间的行为差​​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:利用如车载数据收集系统,可以通过许多研究人员收集和分析包括里程,速度,加速的驾驶数据。但是,在这些研究中,只能从一些选定的驱动程序收集数据。此外,司机知道他们正在参与实验可能会与自然不同。此外,很少有研究利用进展,这需要来自客观车辆的数据,而且需要附近的车辆。近年来建造的许多城市交通监测系统带来了新的研究机会。在本文中,使用了交叉口和道路段的城市交通监测数据,因此可以收集包括客观车辆和车辆的众多车辆的数据,并且可以计算车辆前进的指示器。然后分析了崩溃和崩溃的驱动器之间的驾驶行为的差异。有人发现,在日常驾驶行为中驾驶交叉口时,涉及碰撞的司机倾向于保持比碰撞的司机更少。在崩溃前的日子里,男性司机的这种趋势比女性司机强。对于道路段,与碰撞 - 不涉及的司机相比,在某些时间框架上看到缺陷的司机的头部被忽略较少,并且在自由流动条件下的崩溃驱动器的速度较大。结果表明,利用城市交通监测数据有很大的潜力,以确定风险司机。

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