TOYOTA Sienna Incident

InjuryADS

Report ID: 30413-13249 ยท NOV-2025 at 11:38

Crash Details

Speed

โšก 5 mph

Weather

๐ŸŒค๏ธ Cloudy, Rain

Roadway Type

๐Ÿ›ฃ๏ธ Parking Lot

Road Conditions

๐Ÿ”ง Wet Surface

Crash Type

๐Ÿ’ฅ Other Fixed Object

Pre-crash Movement

Proceeding Straight

Vehicle Information

MakeTOYOTA
ModelSienna
Year2023
ManufacturerMay Mobility
System EngagedADS
Driver TypeIn-Vehicle (Commercial / Test)
Automation Versionv29.0.20
VIN (partial)5TDYRKECXPS

๐Ÿ“ Location

Atlanta, GA

Operating Entity: May Mobility Inc.

Evidence & Data

๐ŸŽฅVideo Availableโœ“
๐Ÿ‘ฎPolice Reportโœ“
๐Ÿ“ŠEDR Dataโœ—
๐ŸŽˆAirbag Deployedโœ—
๐Ÿš›Vehicle Towedโœ—

Narrative

During normal autonomous operation, the May autonomous shuttle (Ego) was traveling through a narrow section of roadway in a parking lot bordered by parked vehicles on the left and a retaining wall on the right on experimental software version v29.0.20. As the Ego proceeded, the system initially recognized the static retaining wall as a large, non-rectangular object. As the Ego approaches the wall, the resulting density of lidar returns on the object (wall) exceeds the detectors maximum limitation. The newer lidar points, toward the forward edge of the elongated object, exceeding the limit were filtered out, causing the track to disappear when the ego approached 5m from the track (i.e. the wall). The situation was exacerbated by the fact that the road edge was incorrectly marked in that section. The road edge was drawn through the retaining wall and thus the vehicle did not have any prior knowledge about the edge of the road. As a result, the Ego drove too close to the wall, scraping it at a speed of 2 meters per second while driving straight (i.e. in lane-nominal policy) with no nudge or veer corrections. There was no damage to the wall. The limitation leading to the lost track affects Software versions v26.0 (when the Open World Tracklet v2 feature was introduced) through v31.0. This is the only known instance of this failure mode, and in v32.0 an optimization was made to remove the LIDAR threshold entirely and mitigate the vulnerability. Furthermore, the incorrect road edge annotation was corrected shortly after this incident and the map updated for the deployed vehicles.

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