Self-driving cars are revolutionizing the next generation of transportation. Autonomous vehicles are designed to improve road safety, increase traffic efficiency, reduce carbon emissions and increase mobility. Through technological advances in robotics and artificial intelligence, the automotive manufacturing industries will move closer to the trend of using automation technology in vehicles for highly or fully automated vehicles (AVs). As people adapt to self-driving vehicles, some capacities will improve such as accessibility, safety, traffic flow, emissions, fuel use, and comfort (Panagiotopoulos & Dimitrakopoulos, 2018).
According to Khan, M.A., and other authors’ articles, systems for autonomous driving combine many technologies. These technologies are necessary for automation to reach the most level of safety that does not need drivers’ attention. The current self-driving trucks are identified in level 4 by The Society of Automotive Engineers (SAE). The categories mean high automotive, that is driver always present, but every safety function is automotive, and the vehicle can manage the response to all road conditions. Every level has several 0 to 5, the higher numbers indicate a higher level of autonomy. Self-driving vehicles of level 1 required drivers’ full attention; vehicles of level 2 required drivers’ partial attention; vehicles of level 3 only need drivers’ attention when needed; level-4 means no driver is required at most conditions; and the highest level doesn’t need driver all the time. The current technology pledges the safety property of self-driving cars that consuming a reasonable amount of energy can deliver sufficient computing power. Therefore, safety is protected by the autonomous driving edge against attacks. In addition, Vehicle-to-Ethernet (V2X) provides autonomous driving redundancy for autonomous driving workloads, mitigates performance stringent and energy constraints at the edge.
While trucking has become an important mode of transportation in the logistics market, driverless trucks are not truly driverless trucks, but they are equipped with advanced driver assistance systems (ADAS)(IEEE Xplore, 2019). The ADAS is mandatory knowledge for drivers that includes the software used for autonomous driving functions, such as power steering, radar, cruise control, and automatic gear shifting. In the last mile of transportation, drivers assist to help trucks find the right place to park (IEEE Xplore, 2019).
Self-driving trucks can reduce collisions and accidents by increasing revenue to reduce costs, solving manpower shortages, increasing fuel rates by 10%, and reducing delivery times(Meg Sabatino August 6, 2021). Disadvantages include legal and insurance liability attribution in the accident, security concerns such as system intrusion into the truck’s software, and strict legal and regulatory restrictions on autonomous driving (Meg Sabatino August 6, 2021). With the improvement of self-driving technology, the realization of level 5 driverless driving trucks is soon.
Reference:
Edge computing for autonomous driving: Opportunities and challenges. IEEE Xplore. (n.d.). Retrieved April 10, 2022, from https://ieeexplore.ieee.org/abstract/document/8744265
Khan, M. A., Sayed, H. E., Malik, S., Zia, T., Khan, J., Alkaabi, N., & Ignatious, H. (2022). Level-5 autonomous driving—are we there yet? A review of research literature. ACM Computing Surveys, 55(2), 1–38. https://doi.org/10.1145/3485767
Meg Sabatino August 6, 2021 • 6 min read. (2021, November 28). What is Autonomous Trucking? FreightWaves Ratings. Retrieved April 10, 2022, from https://ratings.freightwaves.com/what-is-autonomous-trucking/
Panagiotopoulos, I., & Dimitrakopoulos, G. (2018). An empirical investigation on consumers’ intentions towards autonomous driving. Transportation Research Part C: Emerging Technologies, 95, 773–784. https://doi.org/10.1016/j.trc.2018.08.013
