舟山金塘港区集装箱卡车流量分析数据

通过对舟山金塘港区集装箱卡车流量分析数据分析集卡进出时间、在场时间、实时在场数量以及年月日的流量数据，港口管理者可以监控和优化港区内的交通流，减少拥堵，提高运输效率，同时合理规划堆场空间、装卸设备和人力资源，以应对高峰期的作业需求；同时对车辆在场状态进行判断，筛选出异常长时间停靠的车辆，从而进行针对性排查，及时发现和响应潜在的安全问题；同时集装箱卡车运输公司与司机也可根据港区集装箱卡车流量数据，合理规划集卡到达港区的时间，错开高峰时段，提高运输装卸效率，也进一步减轻港区高峰时段集装箱卡车流量过大的问题。1.数据采集处理：通过港口管理系统对集卡编号、集卡进场时间、集卡出场时间等数据进行采集整理汇总。
2.数据计算：车辆在场时间=实时更新时间-集卡进场时间，实时更新时间为最近一次的集卡出场或进场时间，即每次集卡进出更新实时在场数量和状态；实时在场数量=实时更新时间前或相同时间进场的集卡数量-实时更新时间前或相同时间出场的集卡数量，实时更新时间前或相同时间进场/出场的集卡数量通过COUNTIF函数进行筛选计数；根据集卡进场时间使用TEXT函数分别提取日期、年月、年份数据，得到流量结算日、流量结算月、流量结算年，日流量根据流量结算日使用COUNTIF统计对应日期的集卡数量即为对应时间的日流量，同理计算月流量、年流量；日均在场时间使用AVERAGEIF函数筛选对应的流量结算日的车辆在场时间的平均数，同理计算月均在场时间、年均在场时间；车辆在场状态在车辆在场时间>1.5倍年均在场时间时为异常，反之为正常。
3.数据应用：港口管理者能通过数据实时监控和优化交通流提升运输效率，合理规划应对高峰。

This dataset is derived from the traffic flow analysis of container trucks in Zhoushan Jintang Port Area, covering the entry and exit times of container trucks, their dwell time, real-time on-site quantity, and daily, monthly and annual flow data. Port managers can utilize this dataset to monitor and optimize port internal traffic flow, reduce congestion, improve transportation efficiency, and rationally plan yard space, loading and unloading equipment and human resources to address peak operation demands. Furthermore, the dataset enables the judgment of vehicles' on-site status, screening out trucks with abnormally long dwell times for targeted inspections, so as to timely detect and respond to potential safety hazards. Additionally, container truck transport companies and drivers can plan their arrival times at the port rationally based on the traffic flow data, stagger peak hours, enhance transportation and loading/unloading efficiency, and further mitigate the problem of excessive container truck flow during port peak periods.

1. Data Collection and Processing: Data including container truck ID, entry time and exit time are collected, sorted and aggregated via the port management system.

2. Data Calculation: Vehicle dwell time = Real-time update time - Container truck entry time, where the real-time update time refers to the most recent entry or exit time of the container truck, and the real-time on-site quantity and status are updated each time a truck enters or exits the port. Real-time on-site quantity = Number of trucks that have entered the port before or at the real-time update time - Number of trucks that have exited the port before or at the real-time update time. The counts of entering/exiting trucks before or at the real-time update time are conducted using the COUNTIF function. Date, year-month and year data are extracted from the container truck entry time using the TEXT function, to obtain the flow settlement day, flow settlement month and flow settlement year. The daily flow is the number of container trucks on the corresponding flow settlement day counted by COUNTIF, which serves as the daily flow at the corresponding time. Monthly and annual flows are calculated in the same manner. The average daily dwell time is the average of the vehicle dwell times of the corresponding flow settlement days filtered using the AVERAGEIF function, and monthly and annual average dwell times can be derived similarly. The on-site status of a truck is marked as abnormal if its dwell time exceeds 1.5 times the annual average dwell time, otherwise it is marked as normal.

3. Data Application: Port managers can use the dataset to monitor and optimize traffic flow in real time, improve transportation efficiency, and make rational plans to cope with peak operation demands.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于舟山金塘港区的集装箱卡车流量分析，包含1001条记录，涵盖集卡编号、进出时间、在场时间、实时在场数量以及年月日流量等16个字段，每年更新一次。其特点在于通过算法规则计算车辆在场时间和流量数据，旨在帮助港口管理者优化交通流、减少拥堵、提高运输效率，并支持安全排查和资源规划，适用于交通运输行业的监控与决策应用。