One critical bottleneck that impedes the development and deployment of autonomous transportation in open-pit mines is guaranteed robustness and trustworthiness in prohibitively extreme scenarios. In this research, a novel scenarios engineering (SE) methodology for the autonomous mining truck is proposed for open-pit mines. SE increases the trustworthiness and robustness of autonomous trucks from four key components: Scenario Feature Extractor, Intelligence & Index (I&I), Calibration & Certification (C&C), and Verification & Validation (V&V). Scenario feature extractor is a comprehensive pipeline approach that captures complex interactions and latent dependencies in complex mining scenarios. I&I effectively enhances the quality of the training dataset, thereby establishing a solid foundation for autonomous transportation in mining areas. C&C is grounded in the intrinsic regulation, capabilities, and contributions of the intelligent systems employed in autonomous transportation to align with traffic participants in the real world and ensure their performance through certification. V&V process ensures that the autonomous transportation system can be correctly implemented, while validation focuses on evaluating the ability of the well-trained model to operate efficiently in the complex and dynamic conditions of the open-pit mines. This methodology addresses the unique challenges of autonomous transportation in open-pit mining, promoting productivity, safety, and performance in mining operations.

Action detection and public traffic safety are crucial aspects of a safe community and a better society. Monitoring traffic flows in a smart city using different surveillance cameras can play a significant role in recognizing accidents and alerting first responders. The utilization of action recognition (AR) in computer vision tasks has contributed towards high-precision applications in video surveillance, medical imaging, and digital signal processing. This paper presents an intensive review focusing on action recognition in accident detection and autonomous transportation systems for a smart city. In this paper, we focused on AR systems that used diverse sources of traffic video capturing, such as static surveillance cameras on traffic intersections, highway monitoring cameras, drone cameras, and dash-cams. Through this review, we identified the primary techniques, taxonomies, and algorithms used in AR for autonomous transportation and accident detection. We also examined data sets utilized in the AR tasks, identifying the main sources of datasets and features of the datasets. This paper provides potential research direction to develop and integrate accident detection systems for autonomous cars and public traffic safety systems by alerting emergency personnel and law enforcement in the event of road accidents to minimize human error in accident reporting and provide a spontaneous response to victims

Machine intelligence and human augmentation: Still in the early stages, data analytics is improving our powers of prediction, such as assessing the propensity to develop a particular disease. Over the next decade, we must refine these capabilities for decision-making under variable conditions and risks. Technological advances and ethical deliberations about how we deal with knowledge and uncertainty will shape our thinking. Robotics-assisted living and autonomous transportation: We will see more robots in the home helping the elderly and disabled to live independently. They will analyze a person's movements, for example, to help them head off stumbles.

Autonomous vehicles will fail to reach their full potential until ubiquitous and extremely reliable high-speed communications networks with very low latency are available. These networks are key to facilitating the realtime, instantaneous communications among vehicles and supporting infrastructure that must exist before vehicles can continuously and autonomously traverse city streets void of vigilant human oversight. The deployment of 5G (fifth generation) cellular technologies will represent a giant leap forward toward the use of autonomous vehicles for swift, efficient, and safe travel. However, the successful deployment of 5G (and subsequent) technologies depends upon the support of, and coordination among, federal, state, and local governments. Without this support and coordination, only the most lucrative markets will likely benefit from new technologies, and autonomous vehicles will remain technologically insular due to the scale of telecommunications investment required for the mass autonomous vehicle market.

With the rise of self-driving technologies, there is great speculation as to how this new world of autonomous transportation will impact the economy and society. Critics claim that industries will suffer, millions of people will lose their jobs, and society will overall be worse off. Optimists predict that along with new technologies will come new industries and new jobs, and with the benefits of self-driving cars, there will be a ripple of benefits into other aspects of life. Before exploring these different possibilities of what the future may be, let's take a journey to the past. Here we find civilizations at war, and one of the earliest forms of transportation: the chariot.

It sounds like we can all take a breath and forget about robot attacks occurring -- at least anytime soon. Robots turning against their makers is a common theme in science fiction. However, there's "no cause for concern that AI poses an imminent threat to humanity," according to Fast Company, citing the first report from the One Hundred Year Study on Artificial Intelligence (AI100). The Stanford University-hosted project represents a standing committee of AI scientists. The AI100 project is ongoing but will not issue reports annually -- the next one will be published "in a few years."

It sounds like we can all take a breath and forget about robot attacks occurring -- at least anytime soon. Robots turning against their makers is a common theme in science fiction. However, there's "no cause for concern that AI poses an imminent threat to humanity," according to Fast Company, citing the first report from the One Hundred Year Study on Artificial Intelligence (AI100). The Stanford University-hosted project represents a standing committee of AI scientists. The AI100 project is ongoing but will not issue reports annually -- the next one will be published "in a few years."