Cavities under urban roads have increasingly become a great threat to the traffic safety in many cities. As a quick, effective, and high-resolution geophysical method, ground penetrating radar (GPR) has been widely used to detect and image near-surface objects. However, the interpretation of field GPR data is still challenging. For example, it is hard to distinguish reflections caused by road cavities or other urban utilities by a conventional 2D GPR survey. The superiority of 3D GPR in data interpretation is demonstrated by a laboratory experiment. Two pipes and a glass-made cavity buried in a sandpit show similar hyperbolic reflections in the 2D GPR profiles, and are hard to be discriminated. In contrast, their geometric shapes and dimensions are readily identified in the 3D image reconstructed from the synthetic 3D GPR dataset. Thus, a car-mounted 3D GPR system with two antenna arrays oriented in different polarization directions is developed, and has detected over 100 cavities in three Chinese cities over the past one year. The field data of two of the cavities are presented. As a result, the cavity depth, horizontal size and height can be accurately estimated from the 3D GPR dataset. Both laboratory and field experimental results indicate that 3D GPR possesses a great potential in detection and recognition of road cavities and utilities in the complicated urban environment.