Augmenting human hazard situational awareness with haptic interface for heterogeneous autonomous vehicles
| dc.contributor.author | Xing, Yang | |
| dc.contributor.author | Wang, Ziyue | |
| dc.contributor.author | Kong, Xiangqi | |
| dc.contributor.author | Guo, Weisi | |
| dc.contributor.author | Tsourdos, Antonios | |
| dc.date.accessioned | 2026-06-11T08:41:30Z | |
| dc.date.available | 2026-06-11T08:41:30Z | |
| dc.date.freetoread | 2026-06-11 | |
| dc.date.issued | 2026-12-31 | |
| dc.date.pubOnline | 2026-05-21 | |
| dc.description.abstract | As vehicle autonomy increases, human operators become more susceptible to distractions and a loss of situational awareness (SA) due to cognitive limitations. Rapidly enhancing human SA in hazardous situations is, therefore, critical for timely hazard perception and collision avoidance, particularly in human-vehicle teaming contexts that demand fast, accurate hazard reasoning. This study evaluates the efficiency of a low-cost vibrotactile interface for enhancing hazard SA of human operators when teaming with heterogeneous autonomous vehicles, including both ground and aerial autonomous vehicles. To do so, we evaluate the effectiveness of a vibrotactile interface in challenging time-critical scenarios considering adversarial attacks to better understand the cognitive constraints faced by human operators. Our quantitative analysis, based on the data collected from 39 participants, demonstrates that: first, haptic cues can significantly enhance human hazard SA across various metrics for the ground and aerial scenarios; second, perception of aerial attacks in a 3-D environment is more challenging than ground risk perception. | |
| dc.description.journalName | IEEE Transactions on Human-Machine Systems | |
| dc.description.sponsorship | This work was supported by the Royal Society Research under Grant GS/R1/231037. | |
| dc.format.extent | pp. xx-xx | |
| dc.identifier.citation | Xing Y, Wang Z, Kong X, et al., (2026) Augmenting human hazard situational awareness with haptic interface for heterogeneous autonomous vehicles. IEEE Transactions on Human-Machine Systems, Available online 21 May 2026 | en_UK |
| dc.identifier.eissn | 2168-2305 | |
| dc.identifier.elementsID | 870720 | |
| dc.identifier.issn | 2168-2291 | |
| dc.identifier.uri | https://doi.org/10.1109/thms.2026.3688755 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/25308 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_UK |
| dc.publisher.uri | https://ieeexplore.ieee.org/document/11533579 | |
| dc.relation.isreferencedby | https://github.com/YXING-CC/EEG-EMG-DATASET | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Autonomous vehicles | en_UK |
| dc.subject | human-machine teaming | en_UK |
| dc.subject | situational awareness | en_UK |
| dc.subject | vibrotactile interface | en_UK |
| dc.subject | 46 Information and Computing Sciences | en_UK |
| dc.subject | 4602 Artificial Intelligence | en_UK |
| dc.title | Augmenting human hazard situational awareness with haptic interface for heterogeneous autonomous vehicles | en_UK |
| dc.type | Article | |
| dc.type.subtype | Journal Article | |
| dcterms.dateAccepted | 2026-04-25 |
