高速货车风险行为分析模型

整合高速公路货车信息、收费站通行交易等多源数据，覆盖车牌、时间、位置等维度，通过车牌、时间日期筛选，构建货车车辆风险行为分析，支持单车辆全路网行程统计分析。内容包括月活跃天数、总里程次数、总行驶里程数、通行总时长、单次平均出行里程、平均速度、连续8小时疲劳驾驶次数、后半夜（23-05）行驶里程、夜间（19-05）行驶里程、通行路径TOP5。This dataset integrates multi-source data including highway truck information and toll station passage transaction records, covering dimensions such as license plate, timestamp, and geographic location. By filtering with license plate and date-time information, it enables the construction of freight vehicle risky behavior analysis and supports full-road network trip statistical analysis for individual vehicles. The dataset includes the following indicators: monthly active days, total trip times, total driving mileage, total passage duration, average single-trip mileage, average speed, number of consecutive 8-hour fatigued driving incidents, driving mileage during late night (23:00–05:00), driving mileage during night period (19:00–05:00), and TOP5 most frequent travel routes.

搜集汇总

背景与挑战

背景概述

该数据集专注于高速货车的风险行为分析，旨在通过数据驱动的方法识别和评估货车在高速行驶过程中的潜在安全隐患。它可能包含货车行驶轨迹、速度变化、驾驶操作等多维度数据，用于构建分析模型以提升交通安全和运营效率。数据集适用于交通运输行业的风险管理、智能监控和算法开发等应用场景。