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This paper presents an autonomous driving test held in Parma on urban roads and freeways open to regular traffic. During this test, the vehicle not only performed simple maneuvers, but it had to cope with complex driving scenarios as well, including roundabouts, junctions, pedestrian crossings, freeway junctions, and traffic lights. The test demonstrated the ability of the current technology to manage real situations and not only the well-structured and predictable ones. A comparison of milestones, challenges, and key results in autonomous driving is presented to highlight the novelty and the specific purpose of the test. The whole system is described: the vehicle; the software architecture; details about high-, medium-, and low-level control; and details about perception algorithms. A conclusion highlights the achieved results and draws possible directions for future development.Alberto Broggi received the Dr.Ing. (master's) degree in electronic engineering and the Ph.D. degree in information technology both from the Università degli Studi di Parma, Parma, Italy, in 1990 and 1994, respectively. He is currently a Full Professor with the Università degli Studi di Parma, where he is also the President and CEO of the VisLab spinoff company. He is an author of more than 150 publications on international scientific journals, book chapters, and refereed conference proceedings. Dr. Broggi served as Editor-in-Chief of IEEE TRANSACTIONS ON IN-TELLIGENT TRANSPORTATION SYSTEMS for the term 2004-

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Abstract-The presence of autonomous vehicles on public roads is becoming a reality. In the last 10 years, autonomous prototypes have been confined in controlled or isolated environments, but new traffic regulations for testing and direct automotive companies interests are moving autonomous vehicles tests on real roads. This paper presents a test on public urban roads and freeways that was held in Parma on July 12, 2013. This was the first test in open public urban roads with nobody behind the steering wheel: the vehicle had to cope with roundabouts, junctions, pedestrian crossings, freeway junctions, traffic lights, and regular traffic. The vehicle setup, the software architecture, and the route are here presented together with some results and possible future improvements.

Abstract-This paper presents a method for solving the extrinsic calibration between camera and multi-layer laser scanner for outdoor multi-sensorized vehicles. The proposed method is designed for intelligent vehicles within the autonomous navigation task where usually distances between sensor and targets become relevant for safety reasons, therefore high accuracy across different measures must be kept. The calibration procedure takes advantage of triangular shapes still present in scenarios, it recovers three virtual points as target pose in the laser and camera reference frames and then compute extrinsic information of each camera sensor with respect to a laser scanner by minimizing a geometric distance in the image space. To test algorithm correctness, and accuracy a set of simulations are used reporting absolute error results and solution convergence, then tests on robustness and reliability (i.e., outliers management) are based on a wide set of datasets acquired by VIAC prototypes.