Abstract

A deep understanding of driver behavior is an important step to improve road safety and environmental performance. Volatility can be defined as the extent of variations in driving, which can be characterized by accelerations/braking, lane change, and unusual high speed for roadways conditions. There is a lack of knowledge on what concerns the relationship between driver’s volatility and exhaust emissions and how driving volatility can be used as safety eco-indicator. This article explores a driving volatility concept for assessing tailpipe emissions and driving behavior classification. For that purpose, an empirical approach that combined vehicle activity and emission rates for light duty vehicles was used. Field measurements were collected from four probe vehicles in one partly urban/rural, and two highway routes using Portable Emission Measurement Systems, Global Positioning System receivers, and On-board Diagnostic scan tool, to measure real-world tailpipe emissions, position and engine activity data. Acceleration-based parameters, including relative positive acceleration and mean of positive acceleration, acceleration, vehicular jerk, and power demand thresholds were used to detect differences in emissions for different driving styles. Results indicated that vehicular jerk impacted carbon dioxide and nitrogen oxides per unit distance regardless of driving style and route type, especially from negative to null jerk values and during positive accelerations. There is potential to incorporate the analyzed thresholds into a driver decision support algorithm by considering safety and environmental aspects through warning messages.

摘要

深入了解驾驶员行为是改善道路安全和环境绩效的重要一步。波动性可以定义为驾驶变化的程度，其特征可以是加速/制动、车道变换和道路状况的异常高速。对于驾驶员的波动性与废气排放之间的关系以及如何将驾驶波动性用作安全生态指标缺乏了解。本文探讨了用于评估尾气排放和驾驶行为分类的驾驶波动性概念。为此，使用了一种将轻型车辆的车辆活动和排放率相结合的经验方法。现场测量是从四辆探测车中收集的，其中一部分是城市/农村，两条高速公路使用便携式排放测量系统、全球定位系统接收器和车载诊断扫描工具来测量现实世界的尾气排放、位置和发动机活动数据。基于加速度的参数，包括相对正加速度和正加速度平均值、加速度、车辆抖动和功率需求阈值，用于检测不同驾驶方式的排放差异。结果表明，无论驾驶方式和路线类型如何，车辆的颠簸都会影响每单位距离的二氧化碳和氮氧化物，尤其是从负颠簸值到零颠簸值以及正加速期间。通过警告消息考虑安全和环境方面，有可能将分析的阈值纳入驾驶员决策支持算法。