Public acceptance and perception of autonomous vehicles: a comprehensive review

Probably not a substantial claim: may not pass S3 (load-bearing).

Richardson et al. conducted an online and in-paper survey for 69 truck drivers and 17 fleet managers.

“Richardson et al. conducted an online and in paper survey for 69 truck drivers and 17 fleet managers [34].”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourceDisputed

  Sections 3.1 (Data Collection) and 3.2 (Demographics of the sample) describe this paper’s survey as an online survey of adults in Ireland, with 475 usable responses. That contradicts the attributed description of an online and paper survey of 69 truck drivers and 17 fleet managers. (LLM, conf=0.90)

  Checked by a reasoning model — may be wrong.

  Experimental — accuracy not yet measured

May combine two claims.

In Casley et al.'s US survey, 82% ranked safety as most important for adopting AVs, 12% ranked laws, and 6% ranked costs.

“82% of the respondents ranked safety as the most important aspect in order to adopt AVs, 12% believe that laws are the most important aspect, and 6% choose costs.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4 discusses public acceptance, safety concerns and legislation, but gives no survey rankings or percentages. Searches for Casley and the 82%/12%/6% figures found no passage addressing the claimed US survey; page numbers were not available in our copy. (LLM, conf=0.77)

  Experimental — accuracy not yet measured

May combine two claims.

Šinko et al. found people were more negative about AVs in 2017, with average acceptance 3.3 out of 5, than in 2014, with average acceptance 3.6-4.3 out of 5 across countries.

“Results show that people become more negative about AVs in 2017 with an average acceptance of 3.3 out of 5 than in 2014 with an average acceptance of 3.6–4.3 out of 5 in different countries [38].”

• cites [38] Greaves, S.P., Brett, S., Tony, A., Doina, O., Andrew T.C.: ITLS-WP-18-18 autonomous vehicles down under: an empirical investigation of consumer sentiment (2018)Could not verify

  Section 2.1 discusses differences in AV sentiment across countries, and Table 2 in Section 4.4 reports opinions among Australian respondent groups. Neither gives a 2017 average acceptance of 3.3, a 2014 range of 3.6–4.3, or a comparison showing sentiment became more negative. Searches for those figures and years did not locate the claimed comparison. (LLM, conf=0.73)

  Experimental — accuracy not yet measured

May combine two claims.

In Casley et al.'s survey, 74% believed AVs would be prone to malfunction, 57% were concerned about poor awareness of surroundings, 52% about programming issues, and 50% about poor control such as braking and steering.

“On the other hand, 74% of the respondents believe that AVs would be prone to malfunction, 57% of the respondents were concerned about the system’s poor awareness of its surrounding environment, 52% were concerned about programming issues, and 50% were concerned about the poor control of the system such as braking and steering.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4, “Further considerations about AVs” (page unavailable), discusses public distrust of autonomous vehicles but gives no survey percentages. Searches for Casley, malfunction, and the four reported percentages found no passage reporting these results in our copy. (LLM, conf=0.75)

  Experimental — accuracy not yet measured

May combine two claims.

In Casley et al.'s survey, 74% did not trust AVs or believe they can perform better than a normal driver, while 26% did.

“74% of the respondents do not trust AVs nor believe AVs can perform better than a normal driver, while 26% of the respondents do.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4, “Further considerations about AVs” (page unavailable), discusses general distrust of autonomous vehicles but does not report Casley et al.'s survey. Searches for the 74%/26% split and the comparison with a normal driver found no passage addressing those results. (LLM, conf=0.75)

  Experimental — accuracy not yet measured

May combine two claims.

Safety is a top priority for people, and people will not adopt AVs until they are sure the technology is safe.

“These results show that safety is a top priority for people and illustrate that people will not adopt AVs until they make sure that this new technology is safe.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourcePartly supported

  Section 4 (page not provided) identifies acceptance as an important issue and says some people distrust leaving their lives in a machine’s hands, while most fear cyber-attacks. It does not establish that safety is people’s top priority or that they will not adopt AVs until they are sure the technology is safe. (LLM, conf=0.86)

  Experimental — accuracy not yet measured

May combine two claims.

Moral Machine results show people prefer sparing humans over animals, sparing more lives, and sparing young lives.

“Generally, results of the moral machine show that people prefer sparing humans over animals, sparing more lives, and sparing young lives [153].”

• cites [153] Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J., Rahwan, I.: The moral machine experiment. Nature 563(7729), 59–64 (2018) sourceSupported

May combine two claims.

Moral Machine results show broad differences in relative preferences among countries, but nearby countries have closer moral preferences, with three dominant clusters in the West, East, and South.

“However, results show broad differences in relative preferences among different countries [153]. However, results show countries within close proximity to one another showed closer moral preferences, with three dominant clusters in the West, East, and South [154].”

• cites [153] Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J., Rahwan, I.: The moral machine experiment. Nature 563(7729), 59–64 (2018) sourceSupported
• cites [154] Awad, E., Bonnefon, J., Shariff, A., Rahwan, I.: The thorny challenge of making moral machines: ethical dilemmas with self-driving cars. NIM Market Intell Rev 11(2), 42–47 (2019). https://doi.org/10.2478/nimmir-2019-0015 sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Active FTC monitors performance through fault detection and diagnosis and can reconfigure the controller online in real time; passive FTC uses a fixed controller for predefined faults.

“Active FTC depends on fault detection and diagnosis process to monitor the system performance, while passive FTC deals with predefined faults by using a specially designed fixed controller. The main advantage of the active FTC is the ability to detect and identify faults in the system and reconfigure the controller online and in real-time [136–138].”

• cites [136] Zhang, Y., Jiang, J.: Bibliographical review on reconfigurable fault-tolerant control systems. Annu. Rev. Control 32(2), 229–252 (2008) sourceNot checked — no full text of the source
• cites [137] Ducard, G.: Fault-Tolerant Flight Control and Guidance Systems: Practical Methods for Small Unmanned Aerial Vehicles, pp. 1–20. Springer, London (2009) sourceNot checked — no full text of the source
• cites [138] Benosman, M.: A survey of some recent results on nonlinear fault tolerant control. Math. Probl. Eng. 2010, 1–25 (2009) sourceSupported

May combine two claims.

Ethics significantly influence public acceptance of new technology, and the AV ethical dilemma resembles the trolley paradox but will occur more often for AVs.

“Similar to AVs’ accidents, ethics have a significant influence on the public acceptance of any new technology. AVs’ ethical dilemma is similar to the famous trolley paradox; however, the paradox will be more frequent for the case of AVs.”

• cites [142] Lim, H.S.M., Taeihagh, A.: Algorithmic decision-making in avs: understanding ethical and technical concerns for smart cities. MDPI Sustain. 11, 5791 (2019) sourcePartly supported

  Section 4 says safety risks and potential discrimination can dampen consumer acceptance of AVs, but does not extend that finding to any new technology. Section 5.2 uses a trolley problem to illustrate an AV ethical dilemma and says ethics arise in routine driving; it does not say trolley-like dilemmas will occur more frequently for AVs. (LLM, conf=0.86)

  Experimental — accuracy not yet measured
• cites [143] Lin, P.: The ethics of autonomous cars. The Atlantic (2013)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [144] https://www.theatlantic.com/technology/archive/2013/10/the-ethics-of-autonomous-cars/280360/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [145] Worstall, T.: When should your driverless car from google be allowed to kill you? Forbes. 2014. https://www.forbes.com/sites/timworstall/2014/06/18/when-should-your-driverless-car-from-google-be-allowed-to-kill-you/#36e3f970fa5bNot matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

The IEEE code of ethics emphasizes fair treatment of all persons regardless of race, religion, gender, disability, age, national origin, sexual orientation, gender identity, or gender expression.

“the Institute of Electrical and Electronics Engineers (IEEE) emphasizes on treating fairly all persons regardless of their race, religion, gender, disability, age, national origin, sexual orientation, gender identity, or gender expression” [146].”

• cites [146] Bonnefon, J., Shariff, A., Rahwan, L.: The social dilemma of autonomous vehicles. Science (2016). https://doi.org/10.1126/science.aaf2654 sourceCould not verify

  The discussion of ethical autonomous vehicles (p. 7) concerns moral standards for driving algorithms, not the IEEE code of ethics. Searches for the IEEE code, fair treatment, and the listed protected characteristics found no passage in our copy addressing the attributed statement; the IEEE mention in the References (p. 8) is a journal title. (LLM, conf=0.78)

  Experimental — accuracy not yet measured

May combine two claims.

Moral Machine results suggest people want AVs to treat people unequally, preferentially saving women, the young, and the rich over men, the old, and the poor.

“In general, results of the Moral Machine suggest that people want AVs to treat people unequally, preferentially killing some people over others. For example, results show that people prefer saving the lives of women, the young and the rich than the lives of men, the old, and the poor [155].”

• cites [155] Awad, E., Dsouza, S., Kim, R., et al.: Reply to: Life and death decisions of autonomous vehicles. Nature 579, E3–E5 (2020). https://doi.org/10.1038/s41586-020-1988-3 sourcePartly supported

  The paper reports a strong preference for saving younger lives, but describes the preference for saving women as weak, with equality the most common explicit response (Abstract; page unavailable). It says scenario choices favored high-status over low-status characters, while users explicitly preferred equal treatment and would likely be unhappy if that bias were acted upon. Thus the claim overstates what the results show people want AVs to do. (LLM, conf=0.88)

  Experimental — accuracy not yet measured

May combine two claims.

The deontological approach provides guidance in many scenarios but is not a complete ethical system because complex human ethics are difficult to articulate, and it cannot address human factors in edge scenarios such as whether a pedestrian is a child or pregnant woman.

“The deontological approach can provide guidance in many scenarios, however, it cannot be considered as a complete ethical system because of the difficulty involved in the articulation of complex human ethics [148]. Additionally, this approach cannot address the problem related to the human factors in edge scenarios shown in a social dilemma, such as: would it matter if the pedestrian was child or”

• cites [148] Gerdes, J.C., Thornton, S.M.: Implementable ethics for autonomous vehicles. Autonomes Fahren: Technische, rechtliche und gesellschaftliche Aspekte. M. Maurer, J. C. (2015) sourcePartly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured
• cites [164] Beavers, A.: 21 Moral machines and the threat of ethical nihilism. In: Robot Ethics: Ethical Social Implications Robotics, p. 333 (2011)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

Moral Machine results clash with the IEEE code and German rules that prohibit distinctions based on personal features such as age, yet people strongly preferred sparing the young.

“These results by contrast clash with many rules such as the IEEE code of ethics and some of the German ethical rules that clearly prohibit any distinction based on personal features such as age. However, results of the moral machine show that people strongly preferred sparing the young (such as children).”

• cites [153] Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J., Rahwan, I.: The moral machine experiment. Nature 563(7729), 59–64 (2018) sourcePartly supported

  The Global Preferences section (page unavailable) says German Ethical Rule #9 prohibits distinctions based on personal features such as age and explicitly contrasts that rule with the Moral Machine’s strong preference for sparing children. Our copy does not establish that the IEEE code contains a comparable prohibition, so that part of the attributed claim is unsupported. (LLM, conf=0.89)

  Experimental — accuracy not yet measured

May combine two claims.

MIT's Moral Machine platform collected opinions from millions of people in 233 countries, with 40 million decisions in ten languages.

“The platform gathered the opinion of millions of people from 233 countries with 40 million decisions in ten languages.”

• cites [152] http://moralmachine.mit.edu/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [153] Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J., Rahwan, I.: The moral machine experiment. Nature 563(7729), 59–64 (2018) sourceSupported

May combine two claims.

In Casley et al. survey, 80% believe a driving license should be required, 10% neutral, 10% no license.

“Results show that 80% of people believe that a driving license should be required, 10% are in the neutral state, and 10% believe that no license is required.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4, “Further considerations about AVs” (page unavailable), discusses what type of driving license might be necessary but gives no survey results. Searches for Casley and the 80%/10%/10% breakdown found no passage in our copy reporting those figures. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

Surveys show high levels of concern regarding vehicle security: 90.9% [34], 54% [199], 68% [37].

“Surveys showed high levels of concerns regarding security as follows:90.9% of respondents are concerned about vehicle security [34]54% of respondents are concerned about vehicle security [199]68% of respondents are concerned about vehicle security [37]”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourcePartly supported

  Section 4.1 reports concerns about autonomous-vehicle safety and security, particularly when a vehicle has no steering wheel. It does not report that 90.9%, 54%, or 68% of respondents were concerned about vehicle security, so the attributed percentages are unsupported. (LLM, conf=0.84)

  Experimental — accuracy not yet measured
• cites [199] Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., Malhene, N.: Public views towards implementation of automated vehicles in urban areas. Transp. Res. Procedia 14, 2168–2177 (2016) sourceSupported
• cites [37] Kyriakidis, R., et al.: Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transp. Res. Part F Traff. Psychol. Behav. 32, 127 (2015) sourcePartly supported

  Section 3.3 reports that respondents were most concerned about software hacking and misuse, supporting the general point about vehicle-security concerns. It does not report that 68% of respondents were concerned about vehicle security; the 68% in section 1.1 refers to acceptability in a different survey. (LLM, conf=0.86)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Programming AVs with different ethical theories and letting owners determine ethical values would make liability similar to today, with drivers liable in collision.

“One answer might be programming AVs with different ethical theories and let owners determine the vehicle's ethical values. In this approach, liability will be similar to liability nowadays and drivers will be liable in case of collision [178].”

• cites [178] Bartolini, C., Tettamanti, T., Varga, I.: Critical features of autonomous road transport from the perspective of technological regulation and law. Transp. Res. Procedia 27, 791–798 (2017). https://doi.org/10.1016/j.trpro.2017.12.002 sourcePartly supported

  Section 3 says ethical proxies would let car owners choose an ethical theory and make the liability concept close to the current system for human drivers. Section 4.1 says drivers bear liability for damage to third parties under the current system, but it does not say that choosing an ethical theory would make drivers liable for AV collisions; it also discusses possible shifts to owner or manufacturer liability. (LLM, conf=0.83)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

Defining AV software as the driver raises new concerns about liability, especially in complex situations.

“One of the proposed solutions is to define the AV software as the driver. However, this raises new concerns about liability, especially in complex situations [179, 180].”

• cites [179] Taeihagh, A., Lim, H.: Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks. Transp. Rev. 39(1), 103–128 (2019) sourcePartly supported

  The Liability section (p. 8) says that apportioning liability between an AV’s autonomous system and a human driver is unclear, particularly when a human could have intervened. It also describes difficulty assigning responsibility among the parties that design AV systems. These passages support the concern about liability in complex situations, but they do not describe defining AV software as the driver as a proposed solution. (LLM, conf=0.82)

  Experimental — accuracy not yet measured
• cites [180] Slone, S.: State Laws on Autonomous Vehicles. The council of state governments (2016). http://knowledgecenter.csg.org/kc/content/state-laws-autonomous-vehiclesNot matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

In Casley et al. survey, 82% ranked safety as most important to adopt AVs, 12% laws, 6% costs.

“82% of the respondents ranked safety as the most important aspect in order to adopt AVs, 12% believe that laws are the most important aspect, and 6% choose costs.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4 (page unavailable) discusses public acceptance of autonomous vehicles, including safety concerns and legal barriers, but gives no survey rankings. Searches for Casley and the 82%, 12%, and 6% figures found no passage reporting the claimed results. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

In Casley et al. survey, 10% believe laws will not impact desire to purchase, 50% neutral, 40% believe laws will affect desire.

“10% of the respondents believe that laws will not impact their desire to purchase an AV, 50% were in the neutral state, and 40% believe that laws will affect their desire in adopting AVs.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4, “Further considerations about AVs” (page not provided), discusses public acceptance and the need for new legislation, but gives no survey results about laws affecting willingness to purchase an AV. Searches for Casley, the 10%/50%/40% figures, and purchase-related responses found no matching passage in our copy. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

Most countries treat the vehicle as a thing and the human driver as liable in case of error or accident.

“The main issue is that most counties deal with the vehicle as a thing and the driver is the human who is liable in case of error or accident [178].”

• cites [178] Bartolini, C., Tettamanti, T., Varga, I.: Critical features of autonomous road transport from the perspective of technological regulation and law. Transp. Res. Procedia 27, 791–798 (2017). https://doi.org/10.1016/j.trpro.2017.12.002 sourceSupported

May combine two claims.

In Casley et al. survey, 72% were not comfortable being liable for an accident if not driving, 10% comfortable, 18% neutral.

“72% of the respondents were not comfortable with being liable, and 10% were comfortable with this idea, while 18% were in the neutral state.”

• cites [31] Martínez-Díaz, M., Soriguera, F.: Autonomous vehicles: theoretical and practical challenges. Transp. Res. Procedia 33, 275–282 (2018). https://doi.org/10.1016/j.trpro.2018.10.103 sourceCould not verify

  Section 4, “Further considerations about AVs” (page unavailable), discusses accident liability but gives no survey results about respondents’ comfort with being liable. Searches for Casley and the 72%, 10%, and 18% figures found no passage in our copy supporting the attributed percentages. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

In Richardson et al. survey, privacy and liability are major concerns, and 46.2% of truck drivers are concerned about loss of driving pleasure.

“Privacy and liability of AVs are the major sources of fleet managers and truck driver concerns, and a significant portion of truck drivers (46.2%) are concerned about the loss of driving pleasure.”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourcePartly supported

  Sections 4.4 (Recording Travel Data by AVs) and 4.5 (AV's Legal Liability) report privacy concerns and reluctance to accept liability among the paper’s survey respondents. They do not establish these as the major concerns of fleet managers or truck drivers, and the copy does not report that 46.2% of truck drivers feared losing driving pleasure. (LLM, conf=0.86)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

In Richardson et al. survey, 74% of truck drivers feel safe about their jobs.

“74% of truck drivers feel safe about their jobs.”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourceCould not verify

  Section 3.2 describes an Irish national survey, while Section 4.1 reports respondents’ views about the safety of autonomous vehicles. Neither the supplied passages nor searches for “74% of truck drivers” and “Richardson” yielded a passage about truck drivers feeling secure in their jobs. (LLM, conf=0.78)

  Experimental — accuracy not yet measured

May combine two claims.

In Richardson et al. survey, 44% of truck drivers are not aware of AV technology, while 90% of fleet managers have knowledge.

“Significant portion of the truck drivers (44%) are not aware of the AV technology, while 90% of fleet managers already have the knowledge about the new technology.”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourceCould not verify

  The Data Collection section describes a public survey of road users, and section 4.4 reports awareness of AV travel-data recording, not awareness of AV technology among truck drivers or fleet managers. Searches for Richardson, truck drivers, fleet managers, 44%, and 90% found no passage supporting the attributed figures. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

Piao et al. evaluated public opinion about AVs in La Rochelle, France, using online survey and telephone interview, because six automated buses were piloted in 2015.

“Piao et al. evaluated the public opinion about AVs with the aim of understanding the impact of the previous experience with AVs technology on public acceptance of the technology using an online survey and telephone interview in La Rochelle, France because six automated buses piloted in the city in 2015 [199].”

• cites [199] Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., Malhene, N.: Public views towards implementation of automated vehicles in urban areas. Transp. Res. Procedia 14, 2168–2177 (2016) sourceSupported

May combine two claims.

Bazilinskyy et al. (2015) conducted three surveys in 112 countries with 8862 respondents to estimate public acceptance at national level.

“Bazilinskyy et al. (2015) conducted three surveys in 112 countries with 8862 respondents to estimate the public acceptance in the national level.”

• cites [205] Bazilinskyy, P., et al.: An international crowdsourcing study into people’s statements on fully automated driving. Procedia Manuf. 3, 2534–2542 (2015) sourcePartly supported

  The Abstract reports data from three online surveys totaling 8,862 respondents in 112 countries. But the Results’ national-level comparison used 792 meaningful comments grouped by countries’ GDP per capita, not acceptance responses from all 8,862 respondents or estimates for individual nations. The paper also describes its analysis as using comments extracted from the surveys, rather than saying this study conducted all three surveys. (LLM, conf=0.87)

  Experimental — accuracy not yet measured

May combine two claims.

Schoettle and Sivak found that almost 60% of respondents in the US, UK, and Australia would not pay more for AVs, while only 10% would pay much more.

“Schoettle and Sivak found that almost 60% of respondents in the US, UK, and Australia are not willing to pay more for the new technology, while only 10% are willing to pay much more [34].”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourceCould not verify

  The Literature Review (page unavailable) identifies Schoettle and Sivak as researchers who surveyed willingness to pay for AVs, but does not report the claimed 60% and 10% findings or identify a US, UK, and Australian sample. Searches for those percentages and countries found no supporting passage in our copy. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

In Piao et al. survey, majority were optimistic, 50% believe AVs reduce energy and emissions.

“Majority of respondents were optimistic about the AV technology with 50% believe that AVs reduce energy and emissions.”

• cites [199] Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., Malhene, N.: Public views towards implementation of automated vehicles in urban areas. Transp. Res. Procedia 14, 2168–2177 (2016) sourcePartly supported

  Section 4.1 reports that a majority were optimistic that the listed AV benefits would occur. It reports 51% answering “very likely” for reduced energy consumption and 45% for reduced pollutant emissions, rather than 50% believing AVs would reduce both. (LLM, conf=0.85)

  Experimental — accuracy not yet measured

May combine two claims.

Younger people are more interested in AVs than older people, which contradicts the theory that older adults would benefit more from AVs.

“results show that younger people are more interested in AVs, which contradict with the theory that elder will benefit more from AVs.”

• cites [19] Securing America’s Future Energy (SAFE). America’s workforce and the self-driving future: realizing productivity gains and spurring economic growth (2018)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [208] Miller, S.A., Heard, B.R.: The environmental impact of autonomous vehicles depends on adoption patterns. Environ. Sci. Technol. 50(12), 6119–6121 (2016) sourcePartly supported

  In “Travel Behavior Patterns” (page not provided), the paper says AV mobility services would benefit elderly and disabled people. It does not report that younger people are more interested in AVs than older people, or say that greater interest among younger people contradicts the benefit to older people. The Discussion describes Millennials as more inclined toward on-demand mobility, not AVs specifically. (LLM, conf=0.86)

  Experimental — accuracy not yet measured
• cites [209] Compass Transportation and Technology prepared for: Securing America’s Future Energy (SAFE). The Economic and Social Value of Autonomous Vehicles: Implications from Past Network-Scale Investments (2018)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [210] Brown, A., Gonder, J., Repac, B.: An analysis of possible energy impacts of automated vehicle. (2014). https://doi.org/10.1007/978-3-319-05990-7_13 sourceNot checked — no full text of the source
• cites [211] Clark, B.Y., Larco, N., Mann, R.F.: The impacts of autonomous vehicles and e-commerce on local government budgeting and finance (2017). sourceNot checked — no full text of the source

May combine two claims.

Piao et al. found that 56% of respondents over 65 would consider AV trips, compared with 62% of those aged 18-34 and 61% of those aged 35-64.

“Piao et al., found that 56% of respondents aged > 65 would consider making trips using AVs, compared to 62% and 61% for people aged between 18 and 34, and 35–64 [199].”

• cites [199] Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., Malhene, N.: Public views towards implementation of automated vehicles in urban areas. Transp. Res. Procedia 14, 2168–2177 (2016) sourceSupported

May combine two claims.

40%, 20%, and 23% of respondents from high, medium, and low-income countries were concerned about AV technology.

“40%, 20%, and 23% of respondents from high, medium, and low-income countries were concerned about the AV technology.”

• cites [205] Bazilinskyy, P., et al.: An international crowdsourcing study into people’s statements on fully automated driving. Procedia Manuf. 3, 2534–2542 (2015) sourcePartly supported

  The Results report that respondents from high-income countries were more likely to express negative views about automated driving than those from low-income countries. But the indexed text does not give the claimed 40%, 20%, and 23% breakdown; its 23% figure refers to negative comments across all three income groups, not the low-income group. Figure 2’s caption describes percentages by income group, but does not state their values. (LLM, conf=0.84)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

In Richardson et al. survey, 47% of truck drivers choose their job because of driving pleasure.

“47% of truck drivers choose their job because of driving pleasure.”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourceCould not verify

  The Demographics of the sample section describes a survey of adults in Ireland, and §4.6 reports reasons for purchasing autonomous vehicles. Searches for Richardson, truck drivers, driving pleasure, and 47% found no passage addressing why truck drivers chose their jobs. (LLM, conf=0.75)

  Experimental — accuracy not yet measured

May combine two claims.

People with higher education are more aware of AV benefits and concerns and are generally skeptical.

“Higher education people are more aware of AVs’ benefits and concerns and generally skeptical [34].”

• cites [34] Rezaei, A., Caulfield, B.: Examining public acceptance of autonomous mobility. Trav. Behav. Soc. 21, 235–246 (2020). https://doi.org/10.1016/j.tbs.2020.07.002 sourcePartly supported

  Section 4.1 reports that few respondents believed AVs would operate more safely and securely than human drivers, supporting general skepticism. It does not establish that people with higher education are more aware of AV benefits and concerns or are more skeptical than others; searches for education and educated respondents found no such finding. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

In Piao et al.'s survey, 33% of respondents did not know which mode they preferred because they were unfamiliar with AV sharing services.

“It must be mentioned that 33% of the respondents stated that they do not know which mode they prefer because they are no familiar with the sharing service provided by AVs [199].”

• cites [199] Piao, J., McDonald, M., Hounsell, N., Graindorge, M., Graindorge, T., Malhene, N.: Public views towards implementation of automated vehicles in urban areas. Transp. Res. Procedia 14, 2168–2177 (2016) sourcePartly supported

  The Car-pooling section (page unavailable) reports that about one fifth answered “Don’t know” when asked about the appeal of car-pooling benefits; it suggests lack of car-pooling experience as one possible reason. It does not report that 33% were unsure which travel mode they preferred or establish unfamiliarity with AV sharing services as the reason. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

In 2016 the German government appointed a commission on the AV ethical dilemma, and in June 2017 it proposed twenty ethical rules all AVs must follow.

“In 2016, the German government appointed a commission to understand and study this ethical dilemma [150]. In June 2017, the commission proposed its final report that provides twenty ethical rules that all AVs must follow [151].”

• cites [150] Gogoll, J., Müller, J.F.: Autonomous cars: in favor of a mandatory ethics setting. Sci. Eng. Ethics 23, 681–700 (2017). https://doi.org/10.1007/s11948-016-9806-x sourceNot checked — no full text of the source
• cites [151] Luetge, C.: The German ethics code for automated and connected driving. Philos. Technol. 30, 547–558 (2017). https://doi.org/10.1007/s13347-017-0284-0 sourceNot checked — no full text of the source

May combine two claims.

Figure 8 shows that a significant portion of people are not willing to pay more for AVs, while a small proportion is willing to pay much more.

“A significant portion of people are not willing to pay more for AVs, and a small proportion is willing to pay much more.”

May combine two claims.

Although accessibility for the elderly and disabled was among the key benefits of AVs, little to no research has focused on disabled people's acceptance of AVs.

“In other words, it is noteworthy that, although accessibility to the elderly and disabled was among the key benefits of AVs, little to no research focused on the disabled to understand their acceptance of AVs.”

May combine two claims.

Surveys show that older people are the most pessimistic towards AVs, contradicting theories that elders will benefit more from AVs.

“However, surveys showed that older people are the most pessimistic towards AVs, which contradicts the theories that the elder will benefit more from the AVs.”

May combine two claims.

People are highly concerned about AVs, and fear of AVs increases with the number of reported accidents.

“In general, people are highly concerned about AVs, and the level of fear of AVs increase with the increase in the number of accidents reported.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Rare studies have focused on the perception or opinion of truck drivers about AV technology.

“rare studies focused on the perception or the opinion of truck drivers on AVs’ technology.”

May combine two claims.

In that survey, 66% would not feel safe if the vehicle had no steering wheel, while 14% had no problem with it.

“Additionally, 66% of respondents responded that they will not feel safe if the vehicle does not have a steering wheel, while only 14% have no problem if the vehicle does not have a steering wheel”

• cites [33] Zmud, J., Sener, I., Wagner, J.: Consumer Acceptance and Travel Behavior Impacts of Automated Vehicles. Texas A&M Transportation Institute, Texas (2016)Not checked — no full text of the source

May combine two claims.

Extensive media coverage of AV accidents means the news reaches every person in the world and increases fear of the technology.

“This extensive coverage means that this news will be delivered to every person in the world and increase the level of fear of this technology.”

May combine two claims.

Jefferson and McDonald's sentiment analysis showed both positive and negative sentiment decreased after the crash, with the positive drop much larger than the negative decrease.

“The figure illustrates that across time, both positive and negative sentiment decreased following the crash. However, the drop in the positive sentiment was much larger than the decrease in negative sentiment [39].”

• cites [39] Obrecht, M., Knez, M., Sinko, S.: Analysis of public opinion on autonomous vehicles. In: 12th International Conference on Challenges of Europe: Innovative Responses for Resilient Growth and Competitiveness at: Bol (2017)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

During the 2018 Uber crash, the AV sensed the pedestrian six seconds prior to impact but delayed braking until 1.3 seconds before the deadly collision.

“The National Transportation Safety Board (NTSB) reported that the vehicle detected the pedestrian six seconds before the accident but did not brake until 1.3 s before hitting the fatal accident [26].”

• cites [26] Walker, A.: Are self-driving cars safe for our cities? (2020). https://www.curbed.com/2016/9/21/12991696/driverless-cars-safety-pros-consNot matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

AV safety is a complex process requiring coordination across machine learning, sensor development, testing, and standard testing process.

“Koopman and Wagner showed that safety of AVs is a complex process that requires coordination between different disciplines starting from machine learning, to sensor development, to testing AVs, and developing a standard testing process [23].”

• cites [23] Koopman, P., Wagner, M.: Autonomous vehicle safety: an interdisciplinary challenge. IEEE Intell. Transp. Syst. Mag. 9, 90–96 (2017). https://doi.org/10.1109/MITS.2016.2583491 sourceNot checked — no full text of the source

May combine two claims.

Sivak and Schoettle found that factors contributing to accidents will change with AV introduction; some vehicle failures become obsolete while others appear.

“In 2015, Sivak and Schoettle found that there are many factors which contribute to accidents and the contribution of these factors will change with the introduction of AVs.”

• cites [21] Sivak, M., Schoettle, B.: Road safety with self-driving vehicles: general limitations and road sharing with conventional vehicles (University of Michigan, Ann Arbor, Transportation Research Institute, 2015-01) (2015).Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

There is no standard for testing AVs; a driving test is not feasible because it only checks basic tasks and not complex conditions.

“First, there is no standard for testing AVs. For example, the use of the driving test will not be feasible for AVs, because this test will make sure that AVs have the ability to perform the basic driving tasks, while the behavior of AVs in different or complex conditions will not be tested [24].”

• cites [24] Kalra, N.: Challenges and approaches to realizing autonomous vehicle safety. In: Presented to the Committee on Energy and Commerce Subcommittee on Digital Commerce and Consumer Protection United States House of Representatives. RAND Corporation, Santa Monica (2017) sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

Machine learning and artificial intelligence require massive data to train AVs to make right decisions.

“However, the use of machine learning and artificial intelligence is a very complex process that requires massive data to train the vehicle to make the right decision [104].”

• cites [104] Viatech. Why sensor fusion is the key to self-driving cars. Viatech (2019). https://www.viatech.com/en/2019/10/why-sensor-fusion-is-the-key-to-self-driving-cars/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

Increased complexity of AV systems and sensors will raise vehicular failure rates and may increase accident rates.

“Additionally, the complexity of the system and sensors will increase the vehicular failure rates which might increase the rate of accidents.”

• cites [21] Sivak, M., Schoettle, B.: Road safety with self-driving vehicles: general limitations and road sharing with conventional vehicles (University of Michigan, Ann Arbor, Transportation Research Institute, 2015-01) (2015).Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

In an Austin survey, 41% would not consider AVs due to lack of trust, 24% due to safety concerns, and 22% due to high costs.

“41% of the respondents stated that they will not consider AVs because of the lack of trust in the technology, 24% stated they will not consider AVs because of their concerns about the safety of this new system, and 22% will not consider AVs because of the high costs.”

• cites [32] Casley, L., Jardim, A., Quartulli, A.: A Study of Public Acceptance of Autonomous Cars Interactive Qualifying Project. Worcester Polytechnic Institute, Worcester (2014)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

The accident reduced trust in AV technology, especially among people with positive attitudes who stopped tweeting about positives.

“Additionally, this accident reduced the level of trust in the technology especially for people with positive attitude that they stopped tweeting about the positives of AVs.”

• cites [39] Obrecht, M., Knez, M., Sinko, S.: Analysis of public opinion on autonomous vehicles. In: 12th International Conference on Challenges of Europe: Innovative Responses for Resilient Growth and Competitiveness at: Bol (2017)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

The accident caused a large proportion of positive tweets to disappear while negative tweets remained almost the same, suggesting many previously positive people became worried.

“These results indicate that a large proportion of the positive tweets disappeared (almost half), while the negative tweets almost remain the same as before the accident, which means that a large number of people who were positive towards AVs before the accident might became worried about the technology.”

• cites [39] Obrecht, M., Knez, M., Sinko, S.: Analysis of public opinion on autonomous vehicles. In: 12th International Conference on Challenges of Europe: Innovative Responses for Resilient Growth and Competitiveness at: Bol (2017)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

There is no agreement on the definition of AV safety.

“Second, there is no agreement on the definition of the safety of AVs.”

• cites [25] Nishimoto, A.: All new tesla models will feature level 5-capable autopilot hardware (2016). https://www.motortrend.com/news/new-tesla-models-will-feature-level-5-capable-autopilot-hardware/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Sensor fusion combines inputs from multiple sensors to support vehicle decision-making and provides redundancy, rather than relying on a single unreliable sensor.

“Thus, sensor fusion support AVs to fuse various information from the sensor suite, instead of relying on a single and unreliable sensor. Also, sensor fusion provides redundancy as the same areas are covered by different types of sensors to support the vehicle decision [103–107].”

• cites [103] Burke, K.: How does a self-driving car see? Camera, radar and lidar sensors give autonomous vehicles superhuman vision. Nvidia (2019). https://blogs.nvidia.com/blog/2019/04/15/how-does-a-self-driving-car-see/Not checked yet

  Not checked in the free run.

• cites [104] Viatech. Why sensor fusion is the key to self-driving cars. Viatech (2019). https://www.viatech.com/en/2019/10/why-sensor-fusion-is-the-key-to-self-driving-cars/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [105] Kozma, P.: Why sensor fusion is critical for self-driving cars (2019). https://aimotive.com/blog/content/7321Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites [106] Mitchell, H.B.: Multi-sensor data fusion: an introduction. Springer, Berlin (2007) sourceNot checked — no full text of the source
• cites [107] Hall, D.L., et al.: Handbook of multisensory data fusion. CRC Press, Boca Raton (2001) sourceNot checked — no full text of the source

May combine two claims.

AV navigation is difficult because of obstacles such as weather, and insufficient information creates uncertainty that makes it hard to follow a pre-defined path.

“AVs’ navigation is a difficult task because of a variety of obstacles such as the weather conditions [108]. These obstacles create uncertainty when the vehicle is unable to gain sufficient information from the surrounding environment, which makes it difficult for the vehicle to precisely follow a pre-defined path [109].”

• cites [108] Parhi, D.R., Singh, M.K.: Navigational strategies of mobile robots: a review. Int. J. Autom. Control 3(2/3), 114–134 (2009) sourceNot checked — no full text of the source
• cites [109] Mohamed, A., Ren, J., El-Gindy, M., Lang, H., Ouda, A.N.: Literature survey for autonomous vehicles: sensor fusion, computer vision, system identification and fault tolerance. Int. J. Autom. Control 12(4), 555–581 (2018) sourceNot checked — no full text of the source

May combine two claims. The quote only partly states this claim.

Jefferson and McDonald found that after a 2019 AV accident, the word 'crash' did not appear before the accident but became common after it, and frequent terms changed.

“The analysis shows that the word “crash” does not appear before the accident, but it becomes a common word after the accident.”

• cites [39] Obrecht, M., Knez, M., Sinko, S.: Analysis of public opinion on autonomous vehicles. In: 12th International Conference on Challenges of Europe: Innovative Responses for Resilient Growth and Competitiveness at: Bol (2017)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

AV safety is a complex process still in early stages.

“Additionally, safety studies show that AVs’ safety is extremely complex and still in the early stages.”

May combine two claims.

In Rezaei and Caulfield's international survey, 44% did not believe AVs are safer than a normal human driver, while 25% believed they are safer.

“Results show that 44% of the respondents do not believe that AVs are safer than a normal human driver, while 25% believe AVs are safer.”

• cites [33] Zmud, J., Sener, I., Wagner, J.: Consumer Acceptance and Travel Behavior Impacts of Automated Vehicles. Texas A&M Transportation Institute, Texas (2016)Not checked — no full text of the source

May combine two claims.

In that survey, 13% would adopt AVs once available, and 87% would wait to see the opinion of early adopters.

“Results show that only 13% will adapt AVs once they are in the market, and 87% of the respondents will wait to see the opinion of the early adaptors [33].”

• cites [33] Zmud, J., Sener, I., Wagner, J.: Consumer Acceptance and Travel Behavior Impacts of Automated Vehicles. Texas A&M Transportation Institute, Texas (2016)Not checked — no full text of the source

Classified as probably not a substantial claim.

Consumers tend to distrust emerging technologies in their early phases, particularly when personal safety and life are at stake.

“Probably, the rationality behind this is that people do not trust new technologies at early stages especially if these technologies will affect their own safety and lives.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Some people think AVs should be allowed once they are safer than human driving, while others do not trust machines and will not accept putting their lives in machines' hands.

“While some people think that AVs must be allowed once they provide a higher safety level than human driving, others will not trust machines and will not accept the idea of putting their lives in the hands of machines [25].”

• cites [25] Nishimoto, A.: All new tesla models will feature level 5-capable autopilot hardware (2016). https://www.motortrend.com/news/new-tesla-models-will-feature-level-5-capable-autopilot-hardware/Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Sensor fault detection commonly uses analytical or model-based methods requiring mathematical modeling; such models are popular but hard for complex tasks, where artificial neural networks are used.

“The most common methods used for sensor fault detection are the analytical methods or the model-based models that require mathematical modeling of the system, inputs, and outputs in order to produce the detected features.”

• cites [132] Meskin, N., Khorasani, K.: Fault detection and isolation: multi-vehicle unmanned systems. Springer, New York (2011) sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

For nonlinear dynamic models, methods such as the modified Kalman filter are used.

“However, for the nonlinear dynamic models, other methods are used such as the modified Kalman filter [115].”

• cites [115] Welch, G., Bishop, G.: Course 8: an Introduction to the Kalman filter’, ACM SIGGRAPH (2001)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

Both rational and AI approaches have their own shortcomings.

“As shown above, both the rational and AI approaches have their own shortcomings.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Machine-learning sensor fusion requires an analytical or empirical model of a specific sensor to compute the likelihood function and prior distribution values.

“The main drawback of this method is that it needs analytical or empirical model of a particular sensor to compute the likelihood function and ascertain prior distribution values.”

• cites [111] Brown, C., Durrant-Whyte, H., Leonard, J., Rao, B., Steer, B.: Distributed data fusion using Kalman filtering: a robotics application. In: Data Fusion in Robotics and Machine Intelligence, San Diego, CA, pp. 267–309 (1992)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

Summarizing prior studies gives a mixed picture: some respondents endorse utilitarian approaches, but selfish attitudes exist, and even utilitarian supporters are unsure about riding in a car that would sacrifice them to save more lives.

“Summarizing the results of the previous studies gives a similarly mixed picture as in the ethicists’ discussions. There are findings in which respondents call a utilitarian approach for good, but also a selfish attitude can be found. Additionally, even those who in principle consider the utilitarian approach, are apparently not sure whether they want to sit in a car that sacrifices their lives to”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The particle filter uses iterative Monte Carlo, builds a density function from random particles, and has prediction and updating phases.

“This approach is based on the iterative implementation of Monte Carlo technique [120] in order to solve the filtering problem. This approach builds upon the density function using several random samples called particles.”

• cites [120] Crisan, D., Doucet, A.: A survey of convergence results on particle filtering methods for practitioners’. IEEE Trans. Signal Process. 50(3), 736–746 (2002) sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

A hybrid approach might represent a better solution.

“Thus, a hybrid approach might represent a better solution.”

Probably not a substantial claim: may not pass S3 (load-bearing).

AV navigation is complex and requires coordination across machine learning, sensor development, testing, and standard testing processes.

“Finally, the process of AVs’ navigation is a complex process that requires coordination between different disciplines starting from machine learning, to sensor development, to testing AVs, and developing a standard testing process.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

FTC systems must handle fast response time and failure coverage.

“Any FTC system should have the ability to deal with many challenges such as the fast response time to avoid the degradation of the system performance to an undesired level, and failure coverage to allow the system to deal with as many failures as possible.”

May combine two claims.

Social acceptance of AVs significantly influences their market penetration, and ethics and expectations challenge all automotive stakeholders so results cannot satisfy everyone.

“This is not only about ethics but also about the social acceptance of AVs that has a significant influence on the market penetration of AVs. Ethics and expectations are always challenging each other to all automotive stakeholders, so results can never satisfy everyone [143].”

• cites [143] Lin, P.: The ethics of autonomous cars. The Atlantic (2013)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

Academic studies on AV ethical programming can be categorized into rational, artificial, and hybrid rational-artificial intelligence approaches.

“From the academic perspective, previous studies can be categorized into one of three categories: rational approaches, artificial approaches, and hybrid rational and artificial intelligence approaches.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

Public acceptance of AVs is significantly influenced by perceived safety; unsafe AVs are less desirable regardless of benefits, and perceived lack of safety sways potential buyers.

“As shown above, the public acceptance of AVs is significantly influenced by the perceived level of safety of AVs. If the vehicles are not safe, they are significantly less desirable, regardless of their benefits. The perceived safety, or rather the perceived lack of safety of AVs, is what will truly sway the opinions of potential buyers.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Increasing the number of data points can prevent the variance underestimation because sample variance approaches original data variance at the limit.

“However, this problem can be avoided by increasing the number of data points (N) used as the variance of the sample equals the variance of the original data at the limit .”

Probably not a substantial claim: may not pass S3 (load-bearing).

For autonomous vehicles, utility can be defined as damage cost.

“For AVs, the utility can be defined as damage cost.”

May combine two claims.

These results indicate a social dilemma: people agree on what should be done for the greater good but self-interest discourages doing it themselves.

“The previous results indicate a social dilemma as people generally agree on what should be done for the greater good of everyone, but it is in everybody’s self-interest not to do it themselves.”

May combine two claims.

AVs will be able to make decisions about who should live and die without real-time human supervision, affecting everyday transportation and all road users.

“We find ourselves in a situation that is new to the world as vehicles will be able to make decisions on who should live and who should die with no real-time human supervision. This problem is not limited to a niche market but will affect everyday transportation and all road users, no matter whether they drive, walk, or ride a bike.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Fault recovery uses direct redundancy (replacing a faulty module) or analytical redundancy (using working modules to complete failed tasks).

“After identifying the error, two methods are used for the fault recovery: direct redundancy or analytical redundancy. In the direct redundancy, an additional module is employed to replace the faulty one. However, the analytical redundancy implies to utilize the working modules to complete the tasks which failed [135].”

• cites [135] Aldridge, H.A.: Robot position sensor fault tolerance. Ph.D. 9713717, Carnegie Mellon University, United States—Pennsylvania (1996)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Fault prevention and removal aim to avoid or remove faults, while fault forecasting and tolerance aim to prevent system failure despite faults.

“While fault preventions and fault removal focus on the avoidance or removal of faults, fault forecasting and fault tolerance deal with focus on avoiding the system failure with the existence of faults to avoid unplanned behaviors [131].”

• cites [131] Isermann, R.: Fault-Diagnosis Applications: Model-Based Condition Monitoring: Actuators, Drives, Machinery, Plants, Sensors, and Fault-Tolerant Systems. Springer, Berlin (2011) sourceNot checked — no full text of the source

May combine two claims.

Centralized architectures use one global filter and can detect hard sensor failures via residuals but not soft failures; federated architectures use parallel local filters and a master filter to isolate faulty sensor data before fusion.

“Centralized architectures employ one global filter to process the measurements of all the local sensors. This architecture can detect hard sensor failures through the detection of residuals. However, the single centralized filter architecture is not powerful enough to detect soft sensor failures.”

• cites [133] Carlson, N.A.: Federated filter for fault-tolerant integrated navigation systems. In: Position Location and Navigation Symposium, 1988. Record. Navigation into the 21st Century. IEEE PLANS '88. IEEE, pp. 110–119 (1988) sourceNot checked — no full text of the source
• cites [134] Lawrence, Jr., P.J., Berarducci, M.P.: Comparison of federated and centralized Kalman filters with fault detection considerations. In: Position Location and Navigation Symposium, 1994. IEEE, pp. 703–710 (1994) sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Asimov's Three Laws of Robotics can be translated into AV rules: no collision with pedestrians or cyclists, no collision with another vehicle unless conflicting with the first law, and no collision with other objects unless conflicting with the first and second laws.

“These laws can be translated for the case of AVs as follows [163]:An AV should not collide with a pedestrian or a cyclist.An AV should not collide with another vehicle unless this collision would not conflict with the first law.An AV should not collide with any other object in the environment unless avoiding such a collision does not conflict with the first and second laws.”

• cites [163] Wang, H., Khajepour, A., Cao, D., Liu, T.: Ethical decision making in autonomous vehicles: challenges and research progress. In: IEEE Intelligent Transportation Systems Magazine (2020). https://doi.org/10.1109/MITS.2019.2953556. sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Programming ethical rules in AVs faces two challenges: defining societal value across scenarios and translating ethical rules into a machine-understandable language without human intervention.

“The process of formulating the ethical rules in AVs faces two main challenges. The first one is how to define the value of the society across different scenarios. The second challenge is how to translate the set of ethical rules into a language that the vehicle can understand independently from any human intervention.”

Probably not a substantial claim: may not pass S3 (load-bearing).

When the system is linear and error is Gaussian, Kalman filters can produce optimal statistical estimates.

“In case the system can be represented as a linear model and the error can be represented as a Gaussian noise, the filters can estimate the optimal statistical estimations [114].”

• cites [114] Luo, R.C., Kay, M.G.: Data fusion and sensor integration: state-of-the-art 1990s. In: Abidi, M., Gonzalez, R. (eds.) Data Fusion in Robotics and Machine Intelligence, pp. 7–135. Academic Press, San Diego (1992)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

AV faults can come from hardware defects or software imperfections and are classified as hard (sudden) or soft (gradual), with a service outage period when data are faulty.

“There are two sources of fault that might occur in AVs as follows: hardware defect, or software imperfections. In order of appearance, faults can be divided into two categories hard or soft faults.”

• cites [129] Realpe, M., Vintimilla, B.X., Vlacic, L.: A fault tolerant perception system for autonomous vehicles. In: 2016 35th Chinese Control Conference (CCC), Chengdu, pp. 6531–6536 (2016). https://doi.org/10.1109/ChiCC.2016.7554385 sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The modified Kalman filter's main drawback is expensive Jacobian computation; linearization can reduce cost but may add errors and instability.

“However, the major drawback of this approach is the computation of the Jacobians which is extremely expensive, but some research has been made on this area to reduce the computational costs such as applying linearization, but this approach may introduce new errors in the filter and thus makes it more unstable [109].”

• cites [109] Mohamed, A., Ren, J., El-Gindy, M., Lang, H., Ouda, A.N.: Literature survey for autonomous vehicles: sensor fusion, computer vision, system identification and fault tolerance. Int. J. Autom. Control 12(4), 555–581 (2018) sourceNot checked — no full text of the source

May combine two claims.

In complex systems a fault-free system is impossible, so fault forecasting or fault tolerance is preferred; AVs most commonly use fault tolerance.

“In complex systems, it is not possible to achieve a fault-free system, so the fault forecasting or fault tolerance approaches are the preferred approaches. For AVs, the fault tolerance approach is the most common approach followed [129].”

• cites [129] Realpe, M., Vintimilla, B.X., Vlacic, L.: A fault tolerant perception system for autonomous vehicles. In: 2016 35th Chinese Control Conference (CCC), Chengdu, pp. 6531–6536 (2016). https://doi.org/10.1109/ChiCC.2016.7554385 sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Machine-learning sensor fusion can underestimate distribution variance, which may cause data bias.

“Additionally, this method might underestimate the distribution variance, which might lead to data biases.”

• cites [111] Brown, C., Durrant-Whyte, H., Leonard, J., Rao, B., Steer, B.: Distributed data fusion using Kalman filtering: a robotics application. In: Data Fusion in Robotics and Machine Intelligence, San Diego, CA, pp. 267–309 (1992)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

The consequentialism approach can formulate ethical decision making as an optimization problem that maximizes overall utility.

“This approach has the potential to formulae the ethical decision making as an optimization problem [165] that maximizes the overall utility.”

• cites [165] Driver, J.: The history of utilitarianism (2009)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing).

The rational approach divides into deontological (following principles) and consequentialism (optimizing overall benefits).

“The rational approach can be divided into two subcategories: deontological, and consequentialism. The deontological rules force the vehicle to follow a set of principles, while the consequentialism approach is an optimization approach that maximizes the overall benefits of the system.”

May combine two claims.

Sirkin et al. found that 58% of respondents could correctly differentiate events with visible alert, 83% with audible alert, and 95% with visible and audible alerts; average response time to take control is 5-9 s depending on alert method.

“Results show that 58% of respondents could correctly differentiate between different events in case of visible alert, 83% in case of audible alert, and 95% in the case of visible and audible alerts. Additionally, respondents need an average response time of 5–9 s in order to take control back depending on the alert method [193].”