Advanced science.  Applied technology.


A SwRI Automated Shuttle, 10-R8856

Principal Investigator
Inclusive Dates 
05/14/18 - Current


Over the past decade SwRI has developed a strong reputation for providing innovative solutions to challenging technical problems in the field of automated vehicles. As a consequence of this success, SwRI regularly receives requests to carry out very ambitious automated vehicle projects. Although SwRI is fully capable of achieving project objectives from a technical perspective, the corresponding costs and/or cost uncertainties have limited the number of opportunities that come to fruition. Among the largest factors that affect the cost and uncertainty are a lack of thorough testing and refinement of the existing core vehicle automation software and limited overall functionality of the software. Maturing and expanding this software would reduce the risk associated with estimating these projects.

This project was originally conceived in three phases. Phase 1 consisted of two main tasks: the preparation of the basic shuttle software and the implementation of a dedicated “people mover” vehicle. Phases 2 and 3 focus on the deployment, operation, and experimentation of the automated shuttle system, as well as the data collection and software refinement and enhancement process.


This research effort bridges together SwRI’s various automated vehicle technology offerings on a single vehicle platform. Phase 1 created an initial shuttle on a SwRI-owned passenger sedan. SwRI’s commercial automated driving system was installed, and a safety driver was trained to operate the vehicle on SwRI’s campus. The safety driver performed mileage accumulation to collect data and identify and measure limitations of the current system, especially rare events not seen during typical brief capability tests. Phase 1 identified two capabilities missing from the automated driving system that are critical for a campus automated shuttle: high-reliability intersection negotiation and intelligent detection of and interaction with pedestrians. The shuttle building task of Phase 1 and the software improvements implemented during Phase 2 were shaped by these identified needs. Phase 2 recently concluded, and Phase 3, which involves extensive shuttle operation and data collection around campus, will soon begin.


We successfully operated the shuttle platform autonomously with our Ranger localization solution. We tested and added to our map pedestrian detection capabilities and crosswalk integration. Additional testing was conducted in a controlled environment at our test track as well as on campus roads with real traffic and pedestrians. The shuttle was demonstrated to executive management and multiple groups of visitors, and routine operations are planned for Phase 3.