基于大规模驾驶数据，量化五类典型驾驶行为的常态模式。
Summarizing Normative Driving Behavior From Large-Scale NDS Datasets for Vehicle System Development
- 用多源数据融合方法分析驾驶行为与道路、车型、人群的关系
- 3400多名司机行驶超3400万英里，发现年轻女性超速更频繁
- 提供可交互工具，支持跨群体驾驶行为对比分析
本文提出一种处理大规模自然驾驶研究（NDS）数据的方法，用于描述五项车辆指标（车速、超速、车道保持、跟车距离和车头时距）的规范性驾驶行为，结合道路特征、车辆类型和驾驶员人口统计信息。该方法基于第二阶段战略公路研究（SHRP 2）NDS数据，涵盖超过3400名驾驶员的3400万英里行驶记录。通过车辆、GPS和前向雷达数据生成各指标的汇总结果。同时开发了交互式在线分析工具，支持按动态筛选和分组进行行为对比。例如，在65 mph道路中，16-19岁女性驾驶员超速7.5至15 mph的情况比男性略多，且年轻驾驶员保持车头时距低于1.5秒的频率高于年长者。本研究为车辆系统与交通安全基础设施开发提供量化依据，并建立了一套可用于跨群体比较的NDS数据分析方法。
原文摘要 · Abstract (English)
This paper presents a methodology to process large-scale naturalistic driving studies (NDS) to describe the driving behavior for five vehicle metrics, including speed, speeding, lane keeping, following distance, and headway, contextualized by roadway characteristics, vehicle classes, and driver demographics. Such descriptions of normative driving behaviors can aid in the development of vehicle safety and intelligent transportation systems. The methodology is demonstrated using data from the Second Strategic Highway Research Program (SHRP 2) NDS, which includes over 34 million miles of driving across more than 3,400 drivers. Summaries of each driving metric were generated using vehicle, GPS, and forward radar data. Additionally, interactive online analytics tools were developed to visualize and compare driving behavior across groups through dynamic data selection and grouping. For example, among drivers on 65-mph roads for the SHRP 2 NDS, females aged 16-19 exceeded the speed limit by 7.5 to 15 mph slightly more often than their male counterparts, and younger drivers maintained headways under 1.5 seconds more frequently than older drivers. This work supports better vehicle systems and safer infrastructure by quantifying normative driving behaviors and offers a methodology for analyzing NDS datasets for cross group comparisons.
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