重点人车管控系统

大华重点人车管控系统结合国际先进的机器识别与深度学习技术，实现对车辆数据和驾驶人员信息的深度挖掘。通过海量卡口数据积累与实时数据碰撞比对，对假/套牌、逾期未年检、多次违法未处理等重点违法进行精确预警；对大货车、渣土车、危化品运输车等重点车辆进行全时全区通行管控；对“失驾”人员违法驾驶行为进行主动告警，实现交通违法行为的定向管控，辅助交通管理专项行动，改变传统以人防为主的模式，有效打击各类重点交通违法行为，构建文明安全的行车秩序。 1、数据价值深度挖掘充分利用已建前端采集数据，通过车辆二次识别，深度挖掘过车数据与价值，对交通违法行为进行重点打击，实现道路交通安全有效提升。 2、填补传统交管空白打破传统技术下重点驾驶人员管控空白，助力智能化应用提升效果，如不系安全带、开车打电话违法检出等。 3、突破传统交管瓶颈采用人车关系结合的方式，实现“失驾”人员违法驾驶行为主动告警，解决了传统交管管车易、管人难的问题，实现从单纯交通管理向情报管理的升维。 4、科学指导警力部署运用大数据分析高效碰撞卡口过车数据，主动发现高危车辆及活动规律，为交管部门实现数据二次应用及精准布警提供了科学数据支撑。

DaHua Key Vehicle and Pedestrian Control System incorporates internationally advanced machine recognition and deep learning technologies to enable in-depth mining of vehicle data and driver information. Through the accumulation of massive checkpoint data and real-time data collision and comparison, it accurately pre-warns key traffic violations such as fake/altered license plates, overdue annual inspection, and multiple unprocessed violations; implements full-time and full-area traffic control for key vehicles including heavy-duty trucks, muck trucks, and hazardous chemical transport vehicles; and proactively alerts against illegal driving by driver-disqualified personnel. The system achieves targeted control over traffic violations, supports special traffic management operations, replaces the traditional people-oriented defense model, effectively combats various key traffic violations, and establishes a civilized and safe traffic order.

1. In-depth Data Value Mining
It makes full use of the collected data from existing front-end facilities, conducts secondary vehicle recognition to deeply mine passing vehicle data and its value, focuses on cracking down on traffic violations, and effectively improves road traffic safety.

2. Filling Gaps in Traditional Traffic Management
It eliminates the control gaps for key drivers under traditional technologies, and enhances the effectiveness of intelligent applications such as detection of violations like not wearing seatbelts and using mobile phones while driving.

3. Breaking Through Bottlenecks in Traditional Traffic Management
Adopting a combined vehicle-driver relationship approach, it proactively alerts against illegal driving by driver-disqualified personnel, solves the traditional traffic management problem of being easy to manage vehicles but difficult to manage drivers, and achieves the upgrade from simple traffic management to intelligence-based management.

4. Scientifically Guiding Police Deployment
Using big data analysis to efficiently collide checkpoint passing vehicle data, it proactively identifies high-risk vehicles and their activity patterns, and provides scientific data support for traffic management departments to realize secondary data application and accurate police deployment.

搜集汇总

背景与挑战

背景概述

重点人车管控系统是一个应用于交通物流领域的数据工具、模型和服务，由浙江大华技术股份有限公司提供。该系统利用先进的机器识别与深度学习技术，对车辆和驾驶人员信息进行深度挖掘，实现交通违法行为的精确预警和管控，有效提升道路交通安全。