有料盒子APP

AV technologies are disrupting businesses and agencies across the world. New organizational structures are evolving, strategies are rewritten, and firms need help to match the rapid pace of change with new processes and design cycles.

Vehicle automation relies heavily on technologies such as wireless communications, positioning, mapping, localization, timing, tracking, and sensing鈥攚hich have recently experienced some degree of disruption themselves. AVs are evolving so quickly that many organizations are afraid programs and policies will be caught off guard. For example, while cameras were seldom used in AV perception 10 years ago, they鈥檙e now the main sensor in several vehicles.

But it鈥檚 important to remember accurately predicting the future is not the main goal of these new technologies. It鈥檚 minimizing surprises.

AV technology poses several systems engineering challenges that companies and agencies will need to address.

• Complexity: The complex systems-of-systems that make up AVs are developed and integrated by many different companies with interdependencies and interfaces that are challenging to manage and evaluate.
• Expansive design space: The definition and testing of requirements is challenged by the nearly infinite number of scenarios the system may encounter.
• Non-deterministic: Machine learning algorithms are non-deterministic in nature, which means a car could act differently if put in the exact same situation at separate times.

有料盒子APP is supporting systems engineering efforts to address these challenges 鈥� for example, in the areas of safety assurance and technical standards.

The National Highway Traffic Safety Administration (NHTSA) is trying to determine how to evaluate AV performance and ensure driverless cars are safe for public use. The old methods 鈥攃rashing cars into walls鈥攚on鈥檛 cut it. New testing systems must be able to assess the car鈥檚 behavior in a large number of scenarios. These tests must also be economical, repeatable, and transparent.

有料盒子APP is working with Virginia Tech Transportation Institute, Southwest Research Institute, and the automobile industry to develop a framework for聽AV聽performance testing and certification for聽NHTSA.

To build the framework, our team first surveyed all proposed implementations of聽AV聽features in the marketplace, such as highway autopilot, low speed airport shuttles, and (eventually) fully-automated taxis. We then identified the Operational Design Domain (ODD) of each feature, where it can operate (e.g. roadway type, speed, time of day, geographic boundaries, etc.), and how it must respond to its surroundings (e.g., pedestrian interactions, taking turns at stop signs, etc.).

The team is reviewing fail-operational/fail-safe mechanisms. The outputs from this project represent a historic step towards developing a new national, and perhaps international, testing and certification procedure.

Transportation, as we know it today, will soon be a thing of the past. Fleets of automated vehicles will provide cheap, on-demand mobility as a service for people and freight across cities. The in-car experience will refocus on productivity and entertainment.

有料盒子APP is a player in this wave of new tech, and continues to invest and provide leadership in the burgeoning vehicle automation market.

We鈥檙e building our transportation offerings and investing in key areas of research. By joining forces with clients and partners, we鈥檙e able to thrive during what may be the transportation industry鈥檚 biggest era of change since the first聽automobile.