A Truth-Oriented Trust Evaluation Model of Shared Traffic Messages in the Internet of Vehicles
Jiamin Zhang, Lisha Shuai, Jiuling Dong, Gaoya Dong, Xiaolong Yang, Keping Long
TL;DR
This paper introduces a trust model for vehicle messages in the Internet of Vehicles, inspired by human trust mechanisms, to improve traffic safety and decision-making.
Contribution
A novel truth-oriented trust evaluation model (HS-TEM) is proposed, integrating self-experience and peer-recommendation trust mechanisms.
Findings
The HS-TEM model effectively evaluates message credibility by fusing self-experience and peer-based trust.
Simulation results show HS-TEM improves fairness and accuracy in trust evaluation for vehicle messages.
The model reduces individual bias and instability in trust assessment under small-sample conditions.
Abstract
The Internet of Vehicles (IoV) provides an effective solution for alleviating traffic congestion and enhancing road safety. However, shared traffic messages in IoV may deviate from on-road conditions due to self-interest protection or insufficient sensor performance. Therefore, evaluating the trustworthiness of shared messages is essential for vehicles to make informed decisions. To this end, a truth-oriented trust model for shared traffic message is proposed, which is inspired by human trust establishment mechanisms (HS-TEMs). Firstly, we quantify the integrated trust value (I-VT) of the message sender by fusing self-experience-based vehicle trust (SEB-VT) and peer-recommendation-based vehicle trust (PRB-VT). In SEB-VT, a sample-size-dependent smoothing factor dynamically trades off prior information and empirical evidence, reducing instability under small-sample conditions. In PRB-VT,…
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Taxonomy
TopicsVehicular Ad Hoc Networks (VANETs) · Autonomous Vehicle Technology and Safety · Traffic control and management