HeightFusion++: Multi-modal Roadside Perception Data from Seven Locations

18.7 GB of multi-modal roadside perception data collected under diverse environmental conditions. The dataset integrates cameras, various LiDAR sensors, and 4D millimeter-wave radar from seven locations along a 600-meter road segment. Author Bowen Wang published this dataset on figshare in April 2026.

Use Cases

• Training roadside perception models based on multi-modal sensor data
• Developing multi-modal fusion algorithms based on integrated camera, LiDAR, and radar data
• Evaluating perception robustness based on data collected under challenging environmental conditions
• Benchmarking sensor performance based on data from seven continuous roadside locations

Strengths

• Dataset size is 18.7 GB, indicating a large volume of sensor data
• Data is collected from seven locations along a 600-meter continuous road segment
• Integrates multiple sensing modalities: cameras, various LiDAR sensors, and 4D millimeter-wave radar
• Data is collected under diverse and challenging environmental conditions

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Data collected by a deployed roadside sensing system.

Freshness

Last updated 2026-04-09 06:02:47

Geography

Data collected from seven locations along a 600-meter road segment.