Safety Drives
Technology
Autonomy
Innovation
Freedom
Us
Technology
Autonomy
Innovation
Freedom
Us
Technology
Autonomy
Innovation
Freedom
Us


360º Simultaneous Detection
Without Blind Spots
It detects movements not only around autonomous vehicles but also in blind spots, responding immediately to unexpected dangers.
Even on dark and stormy days,
to places unseen by people
Even in low visibility environments, such as dark conditions, rain, and fog,
we use lidar, cameras, and radar together to clearly understand the surrounding situation.
Always stable
condition maintenance
RideFlux Driver drives safely with consistent standards without being affected by fatigue or emotions.
Large-scale driving learning through
fleet operation
It detects movements not only around autonomous vehicles but also in blind spots, responding immediately to unexpected dangers.
360º Simultaneous Detection
Without Blind Spots
It detects movements not only around autonomous vehicles but also in blind spots, responding immediately to unexpected dangers.
Even on dark and stormy days,
to places unseen by people
Even in low visibility environments, such as dark conditions, rain, and fog,
we use lidar, cameras, and radar together to clearly understand the surrounding situation.
Always stable
condition maintenance
RideFlux Driver drives safely with consistent standards without being affected by fatigue or emotions.
Large-scale driving learning through
fleet operation
It detects movements not only around autonomous vehicles but also in blind spots, responding immediately to unexpected dangers.
Systematic Preparation for
Safe Roads








Becoming Safer Every Day
Autonomous Driving
Automatically labels and inspects key data collected from operating vehicles to reflect in learning.
Based on various road information such as objects, lanes, and signals, the model continues to improve
and the safety of autonomous driving also increases.
Core data collected from the operating vehicles
is reflected in the training through automatic labeling and verification.
Based on various road information such as objects, lanes, and signals,
the model continuously improves,
increasing the safety of autonomous driving as well.

Step 1
차량 정비 및 자율주행 시스템 점검
차량 정비 및 자율주행
시스템 점검

Step 2
도로 환경 변화 및 예외 상황 데이터 수집
도로 환경 변화 및
예외 상황 데이터 수집

Step 3
RideFlux Driver™ 모델 개선 및 성능 향상
RideFlux Driver™ 모델
개선 및 성능 향상
Safer
Real-time Remote Guidance
Monitoring the location, speed, and driving status of all operating vehicles in real time,
Communicating with road infrastructure through V2X technology to anticipate traffic light information and unexpected situations.
The collected information is transmitted to the vehicle's AI system to support safer decision-making,
connecting vehicles, infrastructure, and control centers to establish a safety net.
Real-time monitoring of the location, speed, and driving status of all vehicles in operation.
Communicating with road infrastructure through V2X technology.
This identifies traffic light information and unexpected situations in advance.
The collected information is transmitted to the vehicle's AI system to support safer decisions, and a safety network is established connecting vehicles, infrastructure, and control centers.
.



Inquiry
Headquarters
25 4th floor, Nohyung 11-gil, Jeju-si, Jeju Special Autonomous Province
Seoul
11 W-dong, 7th floor, 41-gil, Dangsan-ro, Yeongdeungpo-gu, Seoul
contact@rideflux.com
© 2026. RideFlux Inc. All Rights Reserved.
Inquiry
Headquarters
25 4th floor, Nohyung 11-gil, Jeju-si, Jeju Special Autonomous Province
Seoul
11 W-dong, 7th floor, 41-gil, Dangsan-ro, Yeongdeungpo-gu, Seoul
contact@rideflux.com
© 2026. RideFlux Inc. All Rights Reserved.
Inquiry
Headquarters
25 4th floor, Nohyung 11-gil, Jeju-si, Jeju Special Autonomous Province
Seoul
11 W-dong, 7th floor, 41-gil, Dangsan-ro, Yeongdeungpo-gu, Seoul
contact@rideflux.com
© 2026. RideFlux Inc. All Rights Reserved.



