The connected vehicle (CV) data could potentially revolutionize the traffic monitoring landscape as a new source of CV data that are collected exclusively from original equipment manufactures (OEMs) have emerged in the commercial market in recent years. Compared to existing CV data that are used by agencies, the new-generation of CV data have certain advantages including nearly ubiquitous coverage, high temporal resolution, high spatial accuracy, and enriched vehicle telematics data (e.g., hard braking events). This paper proposed a traffic profiling framework that target vehicle-level performance indexes across mobility, safety, riding comfort, traffic flow stability, and fuel consumption. The proof-of-concept study of a major interstate highway (i.e., I-280 NJ), using the CV data, illustrates the feasibility of going beyond traditional aggregated traffic metrics. Lastly, potential applications for either historical analysis and even near real-time monitoring are discussed. The proposed framework can be easily scaled and is particularly valuable for agencies that wish to systemically monitoring regional or statewide roadways without substantial investment on infrastructure-based sensing (and the associated on-going maintenance costs)
翻译:与各机构使用的现有CV数据相比,新一代CV数据具有某些优势,包括几乎无处不在的覆盖范围、高时间分辨率、高空间精确度、以及浓缩的车辆远程信息数据(例如,硬制动事件),本文件提议了一个交通特征分析框架,针对机动性、安全性、骑乘舒适、交通流量稳定性和燃料消耗等方面的车辆水平性能指数。对州际主要高速公路(即I-280 NJ)进行概念验证研究,利用CV数据,说明了超越传统的交通综合指标的可行性。最后,讨论了历史分析乃至近实时监测的潜在应用。拟议的框架可以很容易地扩大,对于希望对区域或全州公路进行系统性监测而不对基于基础设施的遥感进行大量投资的机构(以及相关的持续维护费用)来说,特别有用。