L A T E X 1 X-CAR: An Experimental Vehicle Platform for Connected Autonomy Research Powered by CARMA SM Goodarz Mehr, Prasenjit Ghorai, Ce Zhang, Anshul Nayak, Darshit Patel, Shathushan Sivashangaran, and Azim Eskandarian, Senior Member, IEEE Abstract—Autonomous vehicles promise a future with a safer, cleaner, more efficient, and more reliable transportation system. However, the current approach to autonomy has focused on building small, disparate intelligences that are closed off to the rest of the world. Vehicle connectivity has been proposed as a solution, relying on a vision of the future where a mix of connected autonomous and human-driven vehicles populate the road. Developed by the U.S. Department of Transportation Federal Highway Administration as a reusable, extensible plat- form for controlling connected autonomous vehicles, the CARMA Platform SM is one of the technologies enabling this connected future. Nevertheless, the adoption of the CARMA Platform SM has been slow, with a contributing factor being the limited, expensive, and relatively old vehicle configurations that are officially supported. To alleviate this problem, we propose X- CAR (eXperimental vehicle platform for Connected Autonomy Research). By implementing the CARMA Platform SM on more affordable, high quality hardware, X-CAR aims to increase the versatility of the CARMA Platform SM and facilitate its adoption for research and development of connected driving automation. Index Terms—Connected mobility, connected autonomous ve- hicles, intelligent transportation systems, experimental vehicle platform, CARMA SM , tutorial I. I NTRODUCTION A UTONOMOUS vehicles (AVs) promise a future with a safer, cleaner, more efficient, and more reliable trans- portation system [1], [2]. At high penetration rates they can reduce traffic accident fatalities and pedestrian collisions, lower fuel consumption, utilize efficient routes, and reduce traffic congestion [3]–[5]. However, the current approach to autonomy has focused on building small, disparate intelli- gences that are closed off to the rest of the world. In this approach, even if several autonomous vehicles are traveling in the same environment at the same time, they each have to carry expensive sensing, navigation, and processing hardware and still, lacking coordination with other road users, they may get into accidents. Vehicle connectivity has been proposed as a solution, re- lying on a vision of the future where a mix of connected Corresponding author: Goodarz Mehr The authors are with the Autonomous Systems and Intelligent Machines (ASIM) Laboratory, Virginia Tech, Blacksburg, VA 24061, USA. (email: goodarzm@vt.edu; prasenjitg@vt.edu; zce@vt.edu; anshulnayak@vt.edu; darsh2198@vt.edu; shathushansiva@vt.edu; eskandarian@vt.edu). Digital Object Identifier (DOI): 10.1109/MITS.2022.3168801 © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. autonomous and human-driven vehicles populate the road. Connectivity allows vehicles to perceive beyond the field of view (FoV) of their sensors, coordinate with other vehicles, and negotiate with other road users [1]. The CARMA SM (Cooperative Automation Research Mobil- ity Applications) program at the U.S. Department of Trans- portation Federal Highway Administration (FHWA)a is one of the leading forces behind cooperative driving autonomy (CDA) research, exploring the application of CDA to traffic, reliability, and freight scenarios [6]. CARMA SM products pro- vide the necessary software for conducting CDA research and testing, and include CARMA Cloud SM , CARMA Platform SM , CARMA Messenger, and CARMA Streets [7]. All four prod- ucts are open-source and work together with the FHWA V2X Hub, a separate multi-modal system enabling networked, wire- less communication between connected autonomous vehicles (CAVs), infrastructure modules, and personal communication devices [8]. The CARMA Platform SM is a reusable, extensible platform for controlling SAE level 3+ connected autonomous vehicles (CAVs). It is written in C++ and runs in a Robot Operating System (ROS) environment on Ubuntu. It’s latest version is CARMA3, which provides a rich, generic API for various sensors and actuators, as well as for third-party plugins that implement guidance algorithms to plan vehicle trajectories [9], [10]. The adoption of CARMA3 by the research community, however, has been slow. One contributing factor may be the fact that officially-supported vehicle configurations are limited, expensive, and use hardware that is several years old. To alleviate this problem, we developed X-CAR (eXperimental vehicle platform for Connected Autonomy Research). By implementing CARMA3 on a wider set of more affordable, high quality hardware, X-CAR aims to increase the versatility of CARMA3 and facilitate its adoption for research and development (R&D) of CDA. We used a 2017 Ford Fusion SE Hybrid for X-CAR development which can be seen in Fig. 1, and documented our work in the X-CAR Reference Manual [11]. It should be noted that the use of any particular vehicle, sensor, or hardware in this paper is not a commercial endorsement of the manufacturer. For most items alternatives are available and can be used without sacrificing the integrity of the system. Nevertheless, hardware-specific information is provided here for the sake of accuracy and to facilitate the reproducibility of the platform and results. The remainder of this document is organized as follows: Section II reviews past experimental AV and CAV platforms and provides some introductory information on topics such