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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Some people may be more willing to take advantage of a self-driving car that yields—but the evidence does not show how often that happens on public roads. Studies so far measure judgments in a video survey, behavior in driving simulators, and choices in an online game. Together, they point to a plausible interaction risk, not proof that bullying autonomous vehicles is common or inevitable.
What does “bullying” an autonomous car mean?
In this research, bullying means a human road user using forceful or unfair behavior to make an automated vehicle yield—for example, repeatedly braking in front of it or taking its turn at a narrow crossing. The term describes the behavior being studied; it does not establish how widespread that behavior is in ordinary traffic.
The evidence also uses “aggressive” in more than one way. Some studies ask observers to judge a human driver’s conduct; simulator studies compare driving-style conditions in which an AV maintains its right-of-way or yields. An experimental label such as “aggressive AV” is not an endorsement of speeding, unsafe maneuvers, or breaking traffic rules.
What studies have found
People judged the same behavior differently when the target was an AV
In a 2022 survey experiment, Peng Liu, Siming Zhai, and Tingting Li randomly assigned 956 participants to one of four video conditions. The clip showed a car repeatedly braking suddenly in front of either an AV or a human-driven car; the researchers also varied whether the target’s identity was highlighted. When participants knew the target was an AV, they judged the behavior as more acceptable and less risky, negative, and immoral than when the target was a human-driven car. When the target’s identity was not highlighted, judgments did not differ. These were survey appraisals of a video, not observations of drivers bullying AVs on roads. Read the study in Accident Analysis & Prevention.
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The authors suggested that AVs might need to blend visually and behaviorally with ordinary cars. That is a proposed implication, not an established design rule.
In a simulator, communication and right-of-way behavior affected interactions
A 2026 simulator study by Haitao Chen and Yiqi Zhang involved 48 participants assigned to defensive, moderate, or aggressive human-driving-style groups. It compared interactions with V2V communication off and on, alongside defensive and aggressive AV-style conditions. The authors reported that V2V communication reduced confusion and aggressive driving in the tested interactions. Participants were less confused by AVs that asserted their right-of-way than by AVs more inclined to yield. The authors describe the relevant assertive behavior as rule-compliant; the finding does not mean an AV should force its way through a conflict. Read the simulator study in Accident Analysis & Prevention.
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A second simulator study found that preferences depend on who has priority
In a January 2026 simulator study, 36 human drivers interacted with defensive and aggressive AV styles. In the tested scenarios, drivers behaved less aggressively around the assertive AV condition, as reflected in longer time-to-collision. Drivers’ own styles influenced some decisions and evaluations. Participants also reported lower trust and greater perceived risk with defensive AVs, with effects varying by driver style. These simulator outcomes do not establish what drivers will do in public-road encounters. Read the study in Accident Analysis & Prevention.
A separate March 2026 video survey of 103 UK drivers adds an important qualification: respondents preferred assertive AV behavior when the AV had priority, but preferred defensive behavior when the human driver had priority or priority was unclear. The setting was a video survey, so it records stated preferences rather than observed driving. Read the UK driver survey.
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An online game tested a strategy to deter repeat bullying
A 2019 study by Cooper and colleagues tested a virtual AV in an online game simulating a one-lane bridge. A participant could make the vehicle yield even when the AV’s car was closer to the bridge and considered to have right-of-way. In that repeated game, an adaptive punishment policy significantly reduced repeat bullying (Fisher exact test, p = 0.0016). This was a simplified game experiment, not a road test. The authors identified integration with production-vehicle safety features and more complex social scenarios as future work. Read the paper.
What the evidence can—and cannot—tell drivers and designers
The studies examine different outcomes, so their results should not be collapsed into one claim about “aggression.” The survey measured judgments about acceptability and morality; simulator studies measured confusion, driving behavior, trust, and perceived risk; the game measured repeat behavior in a simplified negotiation.
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| Evidence | Setting and sample | What it measured | What it does not establish |
|---|---|---|---|
| Liu, Zhai, and Li (2022) | Video survey experiment; 956 participants | Judgments of behavior toward an AV or human-driven car | Whether participants actually behave more aggressively toward AVs on public roads |
| Chen and Zhang (2026), V2V study | Driving simulator; 48 participants | Confusion and aggressive driving in tested interactions | Whether V2V communication will produce the same effects in real traffic |
| Chen and Zhang (2026), driving-style study | Driving simulator; 36 drivers | Behavior, trust, and perceived risk around different AV styles | How frequently drivers exploit AVs in ordinary traffic |
| Zhou and colleagues (2026) | Video survey; 103 UK drivers | Stated preferences across right-of-way situations | How respondents would behave behind the wheel in those situations |
| Cooper and colleagues (2019) | Online one-lane-bridge game | Whether a strategy reduced repeat bullying in the game | Effectiveness or safety of that strategy in production vehicles |
Across these settings, a useful design question is not whether an AV should always be “more aggressive.” It is whether it can communicate clearly and behave predictably in context: maintain priority when it has the right-of-way, yield when another road user has priority, and handle ambiguity without provoking unsafe conflict. The UK preference survey supports the importance of that distinction, while simulator findings suggest that communication and predictable right-of-way behavior merit further real-world evaluation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is bullying likely to become a widespread road problem?
The available studies do not provide a representative estimate of how often people bully AVs on public roads. The 956-person survey measured judgments, not road behavior; simulator and game studies tested controlled or simplified interactions. A 2022 study by Paschalidis and Chen developed a moral-disengagement scale for human interactions with AVs and examined its relationship to driver traits, styles, and attitudes, but it likewise does not establish a public-road frequency. Read the study in Transportation Research Part F.
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So the careful answer is that some drivers may treat an AV differently, and cautious behavior could create opportunities for exploitation in particular encounters. Whether that translates into a frequent real-world problem remains unknown from this evidence.
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