Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles
Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles
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DOI：
10.1016/j.trc.2017.08.004
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发表时间：
2017-11
影响因子：
8.3
通讯作者：
A. Khattak;Behram Wali
中科院分区：
文献类型：
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作者：
A. Khattak;Behram Wali
驾驶波动捕捉车辆行驶时速度变化的程度。极端的纵向变化表示硬加速或硬制动。向驾驶员发出警告和警报可以减少这种不稳定性，从而可能提高安全性、能源使用和排放。本研究发展了对危险预测和通知系统所需的瞬时驾驶决策的基本理解，并区分了正常驾驶和异常驾驶。在本研究中，驾驶任务被划分为不同的但未被观察到的状态。研究问题是表征和量化典型驾驶周期中的这些制度以及每个制度的相关波动性，探索制度何时发生变化以及与每个制度相关的关键相关因素。使用来自密歇根州安娜堡安全试点模型部署的基本安全信息（BSM）数据，对在不同道路类型上进行的几次行程进行了两态和三态动态马尔可夫切换模型的估计。虽然数千辆带有车对车（V2V）和车对基础设施（V2I）通信系统的仪表化车辆正在接受测试，但本研究分析了71辆仪表化车辆进行的184次行程中近140万条bsm记录。然后对43个随机选择的行程（N = 714,340条BSM记录）进行了更详细的分析，这些行程是在不同的道路类型上进行的。结果表明，加速和减速是两种不同的状态，与加速相比，驾驶员的减速率更高，制动明显比加速更不稳定。探讨了两种机制与瞬时驱动环境的不同相关性。使用更通用的三工况模型规范，结果显示高速加速、高速减速和巡航/恒定是典型驾驶循环的三种不同工况。此外，在高速行驶的情况下，司机的平均减速速度往往高于加速速度。重要的是，与巡航/恒定模式相比，无论是在“高速”加速还是“高速”减速模式下，驾驶员的瞬时驾驶决策都更加不稳定。该研究有助于分析短期驾驶决策的波动性，以及如何将驾驶制度的变化映射到车辆周围当地交通状态的组合。
Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.