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Connected Autonomous Vehicles (CAVs) are key components of the IntelligentTransportation System (ITS), and all-terrain Autonomous Ground Vehicles (AGVs)are indispensable tools for a wide range of applications such as disasterresponse, automated mining, agriculture, military operations, search and rescuemissions, and planetary exploration. Experimental validation is a requisite forCAV and AGV research, but requires a large, safe experimental environment whenusing full-size vehicles which is time-consuming and expensive. To addressthese challenges, we developed XTENTH-CAR (eXperimental one-TENTH scaledvehicle platform for Connected autonomy and All-terrain Research), anopen-source, cost-effective proportionally one-tenth scaled experimentalvehicle platform governed by the same physics as a full-size on-road vehicle.XTENTH-CAR is equipped with the best-in-class NVIDIA Jetson AGX Orin System onModule (SOM), stereo camera, 2D LiDAR and open-source Electronic SpeedController (ESC) with drivers written for both versions of the Robot OperatingSystem (ROS 1 & ROS 2) to facilitate experimental CAV and AGV perception,motion planning and control research, that incorporate state-of-the-artcomputationally expensive algorithms such as Deep Reinforcement Learning (DRL).XTENTH-CAR is designed for compact experimental environments, and aims toincrease the accessibility of experimental CAV and AGV research with lowupfront costs, and complete Autonomous Vehicle (AV) hardware and softwarearchitectures similar to the full-sized X-CAR experimental vehicle platform,enabling efficient cross-platform development between small-scale andfull-scale vehicles.

XTENTH-CAR: A Proportionally Scaled Experimental Vehicle Platform for Connected Autonomy and All-Terrain Research