Figures & data
Table 1. Impacts of AV on cities transportation/pros(right) and cons(left) (Maheshwari Citation2018).
Figure 1. Comparison of vehicle operating models of automated driving levels (Williams Citation2021).
Figure 2. Performance of the automated vehicle from the conventional vehicle perspective in rear-end collisions.
Table 2. AV implementation stage and its impacts (Litman Citation2023).
Table 3. AV implementation predictions set its levels per year.
Figure 3. Input to output process of the AV.
This image describes input to output processes of AV which includes sensors, [perception, planning and decision, motion and vehicle control] system supervision, and actuators respectively in which all of them interacts externally with maps, world status and user IO.
Figure 4. Autonomous vehicle driving all disciplinary research status.
This figure shows the quantitative research status of Autonomous driving vehicles from 2010 to 2022, in which slight decline from 2010 to 2011 and slight increase from 2011 to 2018. Later, up to 2022 highly increasing research status observed.
Figure 5. Automated vehicle for all disciplinary research status.
Automated vehicles research article status in all discipline increases (1379 to 6085) from 2010 to 2022 but, the conference abstracts show no effective change.
Figure 6. Autonomous vehicle driving engineering (only) discipline research status.
Reveals autonomous driving vehicle research status in only engineering discipline for research article, review paper, encyclopedia, book chapters an conference abstracts. Research article shows higher in line graph while the other four present delicate change except conference abstract.
Figure 7. Automated vehicle engineering discipline (only) research status.
Presents, the automated vehicle research status in only engineering discipline from 2010 onward quantitatively. This line graph contains data of research article, book chapters, review papers, encyclopedia and conference papers.
Table 4. Summary of automated vehicle companies and their background.
Table 5. Comparable table based on different automated vehicle machine learning algorithms.
Table 6. Current autonomous vehicle driverless testing permitted companies, algorithms, challenges and gaps, and their vulnerability.
Figure 8. AV functional performance hierarchies.
Indicates functional hierarchies of automated vehicles including (light, radio waves, force and sounds) as input, sense, localize the sensed matter, perceive, predict, plan for the predicted, control the planned message then dispatch to (steering, brake, throttle and commands) respectively.
Table 7. (SAE Citation2018) Reliability requirements, functions, and software information.
Figure 9. Overall approach for evaluation of AV safety.
This figure contains the structures of the operational concept for autonomous vehicle safety. The explained operational safety has been compiled of vehicle safety, functional safety, and cybersecurity on the first rows. Each of the evaluation steps shown has been shown both from top to bottom and from left to right reading.
Data availability statement
We can encourage that the data we have used in this paper are available on our hands and we can be ready to provide when necessary.