Effects of road-risk head-up display warning on truck drivers' risk-avoidance behavior

In the context of connected vehicles, head-up displays (HUD) have been widely used to provide warning information and enhance driving safety. However, existing systems still lack effective ways to present information about inherent road risk, which is particularly crucial for truck drivers in complex road scenarios. To address insufficient support for truck drivers' evasive maneuvers in scenarios involving overlapping road-vehicle risk factors, this study focused on a high-risk situation involving sudden braking by a preceding vehicle on a curve. Based on the International Road Assessment Programme (iRAP) methodology, a Road-risk Head-Up Display (RHUD) warning system integrating quantified road-risk information was developed. A driving simulation experiment was conducted using a scenario based on the Qingyin Expressway prototype, in which a traditional HUD and an enhanced RHUD were implemented for comparison. Thirty-seven professional truck drivers completed simulated driving tasks involving sudden lead-vehicle braking on a curved segment under both display conditions. The longitudinal safety margin index was selected as the primary metric for risk-avoidance behavior. Survival analysis showed that, in the scenario of sudden braking before a curve, the RHUD significantly improved drivers' risk-avoidance behavior (χ² = 7, p = 0.008), yielding improvements of 27.68%, 32.67%, and 37.94% at the 25th, 50th, and 75th percentiles, respectively. Further analysis revealed that under the RHUD condition, the effects of demographic factors such as age were substantially attenuated, whereas driving performance was primarily governed by situational variables, particularly driving experience and initial speed. This suggests that structured road-risk information helps reduce individual differences in drivers' responses to high-risk events. These findings demonstrate the effectiveness of incorporating road-risk information into truck HUD warning design and confirm the feasibility of linking iRAP-based quantitative road-risk information with in-vehicle warning systems. The proposed approach provides empirical support for optimizing truck warning strategies based on road-risk assessment results and offers practical implications for improving safety in complex road environments.