China’s inaugural self-driving police patrol vehicles start road tests in Beijing

Published: Jan 19, 2024 18:11
Source: gasgoo
On January 16, the inaugural fleet of 15 unmanned police patrol vehicles received approval to conduct road tests in the Beijing High-level Automated Driving Demonstration Area (BJHAD).

Beijing (Gasgoo)- On January 16, the inaugural fleet of 15 unmanned police patrol vehicles received approval to conduct road tests in the Beijing High-level Automated Driving Demonstration Area (BJHAD).

With the approval, the self-driving patrol vehicles are allowed to be tested across multiple parks, subway stations, and commercial squares within the 60-square-kilometer of the BJHAD. This marks a significant step in creating a blueprint for smart policing through the application of autonomous driving technology

In recent years, autonomous driving technology has emerged as a crucial tool to enhance the digitization of urban governance. In the realm of urban smart policing, integrating unmanned patrol cars into regional security will offer the public and economic development a secure and efficient new experience. 

Since 2021, the BJHAD has been open for unmanned patrol scenarios, aiding the area’s Traffic Police Division in routine roadside vehicle violation patrols with successful validation of relevant technologies and service capabilities.

The current initiation of road testing aims to further strengthen the deployment and practical exercises of unmanned patrol cars. Leveraging the integrated urban-level vehicle-road-cloud engineering trial platform of the BJHAD, these vehicles can autonomously patrol predetermined routes round-the-clock, offering features such as remote announcements, real-time observation, live video transmission, and precise command and control. Covering 60 square kilometers of densely populated areas and critical locations, they will undertake 24/7 duties, including patrol and control, large-scale event security, vocal deterrence, public awareness campaigns, and emergency response tasks.

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