Object Verification for ADAS & HAD with Option Driver Assistance
Driver assistance systems and systems for highly automated driving (HAD) acquire information about the vehicle’s environment via a wide variety of sensors such as video, radar, LIDAR, etc. ADAS sensors identify objects in road traffic. The Driver Assistance option allows you to capture the sensor data and conveniently verify it with reality.
The Option Driver Assistance is available in CANape, CANape log and vSignalyzer.
Visualize the sensor data | Capture sensor data | |
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CANape Option DA | | |
CANape log Option DA | | |
vSignalyzer Option DA | |
Advantages
Recording ADAS sensors at very high data rates
For the development of driver assistance systems and autonomous driving vehicles, as much sensor data as possible is recorded to use it later in a re-simulation for testing new software versions. The data rates from radar and video sensors are particularly high. The Driver Assistance option provides you with special recorders (DHPR: Distributed High Performance Recorder) for the various ADAS sensors. We will be happy to integrate new sensors for you at any time.
Visualization and validation of ADAS sensors
The detected objects are displayed as graphical symbols (e.g. as rectangles, polygons and point clouds) in various display windows. Both during the measurement and on the basis of measurement data. A video of a reference camera recorded synchronously with the measurement serves as the basis for verification of the sensor data. The sensors provide the coordinates of the objects, which are then displayed at the corresponding positions of the reference image. Further windows for displaying the objects, such as freely configurable scene windows and map windows, are available. This direct comparison between sensor data and reality allows you to verify the quality of your sensor data quickly and reliably.




Application Areas
The flexible configuration covers a wide range of applications in ADAS development:
- Complete vehicle logging for verification and simulations
- Verification of object recognition algorithms for e.g. ACC (Adaptive Cruise Control), Stop&Go systems as well as parking assistants with the help of object overlaying
- Development of lane-keeping systems or adaptive cornering lights by representing the lanes as curves
- Support for testing traffic sign recognition systems by integrating bitmaps
Recording ADAS Sensor Data
ADAS sensors deliver their data along different paths. Radar and video sensors are integrated via the VX1000 product family. Sensors that transmit data via CAN FD, for example, or whose data is measured via XCP, are integrated directly into CANape. Other sensor types, such as LIDARs, which transmit data via Ethernet using a manufacturer-specific protocol, require a special connection to CANape.
With the Driver Assistance option, special recorders (DHPR: Distributed High Performance Recorder) are available for the various ADAS sensors. We will be happy to integrate new sensors for you at any time.
The DHPRs are controlled from CANape via TCP/IP. The entire measurement task can be distributed across several measurement computers without any problems and is thus fully scalable.
Creating the Object Verification

Validation and visualization of ADAS sensors
The detected objects are displayed as graphical symbols (e.g. as rectangles and polygons) in various display windows. Both during the measurement and based on measurement data.
Videos from reference cameras recorded synchronously with the measurement serve as a basis for verifying the sensor data. The sensors provide the coordinates of the objects, which are then displayed at the corresponding positions of the reference image. For a better overview, the sensor objects can also be displayed in a three-dimensional, freely configurable scene window.
This direct comparison between sensor data and reality allows you to verify the quality of your sensor data quickly and reliably.
Product Descriptions
- 2021-02-24 vCDM 19.1 – New Features for Managing Calibration Data
- 2020-10-08 Squore: Best Practices to Comply with ISO26262 and the HIS...
- 2020-08-25 Automotive Ethernet Introduction – Technology and Protocols for...
- 2020-07-15 Online and Offline Validation of ADAS ECUs
- 2020-07-02 CANape log - Mastering Demanding ADAS Logging Tasks Efficiently...
- 2020-07-02 CANape log - Mastering Demanding ADAS Logging Tasks Efficiently...
- 2020-06-17 Introduction to Run-time Measurement and Calibration of ECUs with...
- 2020-05-14 VectorCAST: Testing of Satellite-Communications based Software in...
- 2020-05-14 VectorCAST: Test di regressione HIL più intelligenti e veloci con...
- 2020-03-26 Efficient Development of Data Fusion Systems for Automated...
Do you have technical questions and are looking for suitable answers? Our KnowledgeBase provides the most important!
Downloads
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2021-02-19 Service PackCANape 18.0 SP5
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2021-01-26 Add-On/FreewarevCDM 19.1 API Toolkit
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2021-01-11 Add-On/FreewareVector MATLAB/Simulink MC Add-On 15.0 (64 bit)
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2020-12-18 DemoCANape 19.0 Demo
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2020-11-06 Service PackCANape 17.0 SP6
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2020-11-02 Press ReleaseRecord ADAS Data Synchronously with the New Logging Solution from Vector
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2020-10-23 Add-On/FreewareVector MATLAB/Simulink MC Add-On 14.0.30 (64 bit)
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2020-10-23 Add-On/FreewareVector MATLAB/Simulink MC Add-On 14.0.30 (32 bit)
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2020-09-02 Service PackvCDMstudio 18.1 (vCDM 6.8 SP1)
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2020-11-05 Product DescriptionCANape log
News & Events
- 2021-03-01 - 2021-03-05 Embedded World Digital 2021
- 2021-03-11 Webinar: New features of CANape 19
- 2021-04-01 Webinar: Managing Projects and Configurations
- 2021-05-06 Webinar: Creating Virtual Signals with the Function Editor
- 2021-06-03 Webinar: Simulink and CANape working together
Training

CANape Fundamentals Workshop
Vector offers many different opportunities for you to build your knowledge of CANape and broadening it. We recommend our CANape Fundamentals Workshop as an entry-level course in CANape. It is best to take this basic course before attending advanced training courses that are also offered. However, you may register for any of the courses independently.