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Time-Space Relationship Analysis Model on the Bus Driving Characteristics of Different Drivers Based on the Traffic Performance Index System

机译:基于交通绩效指标体系的不同驾驶员公交驾驶特性时空关系分析模型

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With the extensive application of the concept of green traffic, the relationship between the driving characteristics of different drivers and energy consumption and traffic performance conditions, etc. is gradually becoming a research hotspot. Based on bus status data recorded by travel data recorders with a vehicle-mounted satellite positioning function and in view of external bus behaviours and driver’s performance, a bus driving characteristic model of drivers is established. A time-space analysis model of the driving characteristics of different drivers based on traffic performance index is also established through fuzzy association rules and a type-2 fuzzy set prediction algorithm. Test results show that the prediction algorithm can accurately describe the time-space relationship between the traffic congestion index and bus driving characteristic model and achieve relatively high prediction accuracy. The problem of the lagging release of traffic performance index caused by massive calculation for floating vehicle data can be effectively solved through this algorithm, which can serve as an important reference for analyzing traffic performance conditions, as well as the energy conservation and emission reduction of buses.
机译:随着绿色交通概念的广泛应用,不同驾驶员的驾驶特性与能量消耗和交通性能状况等之间的关系逐渐成为研究热点。基于具有车载卫星定位功能的行驶数据记录器记录的公交车状态数据,并考虑外部公交车行为和驾驶员的性能,建立了驾驶员的公交车行驶特性模型。通过模糊关联规则和2型模糊集预测算法,建立了基于交通绩效指标的不同驾驶员驾驶行为时空分析模型。测试结果表明,该预测算法可以准确地描述交通拥堵指数与公交车行驶特性模型之间的时空关系,并具有较高的预测精度。通过该算法可以有效解决因浮动车辆数据的大量计算而导致的交通绩效指标滞后释放的问题,可为分析交通绩效状况以及公交车的节能减排提供重要参考。 。

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