New crash data highlights the slow progress of Tesla's robotaxis

Newly unredacted data from the National Highway Traffic Safety Administration (NHTSA) reveals that at least two Tesla robotaxi crashes since July 2025 occurred while the vehicles were being remotely operated by teleoperators. Both incidents took place in Austin, Texas, where Tesla launched its robotaxi service in June 2025. In these cases, safety monitors were present in the vehicles but no passengers were onboard. One crash involved a remote operator increasing the robotaxi’s speed and driving it up a curb into a metal fence, while another saw a remote operator hitting a temporary construction barricade at low speed. Tesla disclosed to lawmakers in March 2025 that it allows remote operators to take direct control of its robotaxis, a practice that differs from other autonomous driving services where remote workers typically only monitor and consult with the driving software rather than actively driving. Additional incidents include minor collisions such as clipped side mirrors and a robotaxi hitting a dog that ran into the street, though the animal survived. These events highlight ongoing safety challenges as Tesla continues to develop its autonomous ride-hailing technology. Beyond safety concerns, Tesla’s robotaxi service is also facing operational difficulties, including long wait times and inconsistent drop-off locations. A recent report detailed a nearly two-hour wait for a five-mile trip in Dallas, as well as instances where riders were dropped off significantly far from their intended destinations despite being within Tesla’s coverage area. These issues underscore the hurdles Tesla must overcome to scale its robotaxi service effectively. While Tesla is not alone in encountering crashes and software problems—competitors like Waymo face similar challenges—the data suggests Tesla’s robotaxi program is progressing more slowly. The combination of safety incidents and service inefficiencies indicates that Tesla may need substantial improvements before matching the operational scale and reliability of its rivals in the autonomous vehicle industry.