Robust Traffic Light and Arrow Detection Using Digital Map with Spatial Prior Information for Automated Driving

Design and Implementation of HD Mapping, Vehicle Control, and V2I Communication for Robo-Taxi Services

This paper presents our autonomous driving (AD) software stack, developed to complete the main mission of the contest we entered. The main mission can be simply described as a robo-taxi service on public roads, to transport passengers to their destination autonomously. Among the key competencies required for the main mission, this paper focused on high-definition mapping, vehicle control, and vehicle-to-infrastructure (V2I) communication. V2I communication refers to the task of wireless data exchange between a roadside unit and vehicles. With the data being captured and shared, rich, timely, and non-line-of-sight-aware traffic information can be utilized for a wide range of AD applications. In the contest, V2I communication was applied for a robo-taxi service, and also for traffic light recognition. A V2I communication-enabled traffic light recognizer was developed, to achieve a nearly perfect recognition rate, and a robo-taxi service handler was developed, to perform the main mission of the contest.

Sensors and Sensing for Intelligent Vehicles

Over the past decades, both industry and academy have made enormous advancements in the field of intelligent vehicles, and a considerable number of prototypes are now driving our roads, railways, air and sea autonomously. However, there is still a long way to go before a widespread adoption. Among all the scientific and technical problems to be solved by intelligent vehicles, the ability to perceive, interpret, and fully understand the operational environment, as well as to infer future states and potential hazards, represent the most difficult and complex tasks, being probably the main bottlenecks that the scientific community and industry must solve in the coming years to ensure the safe and efficient operation of the vehicles (and, therefore, their future adoption). The great complexity and the almost infinite variety of possible scenarios in which an intelligent vehicle must operate, raise the problem of perception as an "endless" issue that will always be ongoing. As a humble contribution to the advancement of vehicles endowed with intelligence, we organized the Special Issue on Intelligent Vehicles. This work offers a complete analysis of all the mansucripts published, and presents the main conclusions drawn.