Vehicles

Crosswind-induced traffic control can require drivers to interpret diversion guidance and complete successive lane changes within limited distance. This study compared four variable message sign (VMS) configurations for upstream exit diversion on an eight-lane divided expressway. Thirty drivers completed simulator trials under single-phase text (A, baseline), two-phase text (B), graphic–text symbol (C), and graphic–text arrow (D) configurations. The VMS was positioned 750 m upstream of the diversion point, and no crosswind forces were applied to the simulated vehicle. Six metrics assessed response timeliness and driving stability. Repeated-measures ANOVA showed significant overall differences among configurations for all six metrics. Compared with Scheme A, Scheme D shifted first lane-change initiation 50.05 m upstream on average and reduced mean lane-change duration by 0.34 s (5.6%). Longitudinal acceleration variability and peak braking intensity decreased by 20.5% and 27.2%, while mean steering control intensity and peak steering control amplitude decreased by 8.1% and 14.8%, respectively. Scheme C had the most favorable mean values across all six metrics. The tested graphic–text configurations showed no behavioral deterioration indicative of information overload. These findings support the tested graphic–text configurations for upstream diversion, although the independent effects of individual information elements could not be isolated.

This paper presents a context-aware trajectory planning framework for autonomous vehicles that integrates Frenet-based geometry, geometric feasibility, obstacle-aware filtering and interpretable multicriteria decision making. Candidate trajectories are generated as polynomial lateral profiles, transformed to global simulator coordinates and rejected when they violate road, smoothness or clearance constraints. Feasible alternatives are ranked through explicit criteria related to lateral stability, smoothness, progress and obstacle separation. The framework is implemented in BeamNG.tech as an ego-controlled multi-participant environment: only the ego vehicle is actively controlled by the planner, while static obstacles and dynamic non-ego traffic participants are represented as observable spatial or spatio-temporal constraints. Recorded experiments cover free-driving, sequential static-obstacle and dynamic traffic-participant scenarios. Two completed static runs and eight completed dynamic executions provide closed-loop repeatability evidence, including three supplementary cases with distinct initial traffic conditions. Across the static runs, the minimum observed centre-to-centre obstacle distance was 3.169–3.177 m; across the five retained dynamic runs it was 3.497–3.528 m. No geometric collision-proxy event occurred in these runs or the three supplementary cases. The method provides an auditable decision layer rather than an opaque end-to-end policy, while its conclusions remain limited to the tested low-speed conditions.

The automotive industry is moving toward cleaner and more sustainable solutions, with vehicle lightweighting emerging as a key strategy to reduce greenhouse gas and nitrogen oxides emissions. While the energy benefits of lightweighting are well documented, its influence on vehicle dynamics and active safety remains less explored. Focusing on a D-segment passenger car during double lane change manoeuvres, this study evaluates the effects of mass variations on pure lateral dynamics. A virtual vehicle model was developed within the VI-CarRealTime^® environment and calibrated to replicate the real vehicle behaviour measured during on-track testing. The model tuning process was enhanced by the installation of several measurement devices that provided experimental signals of both driver inputs and vehicle outputs, to perform realistic offline simulations. Finally, the use of a driving simulator integrating the tuned simulation model and Driver-In-the-Loop (DiL) allows for the investigation of various loading conditions. Since physical weight reduction was not feasible, additional mass was applied through ballasts to assess how increased weight alters the vehicle’s dynamic response compared to the unloaded condition. Meanwhile, lightweight configurations were evaluated solely in simulation across two distinct scenarios. Double Lane Change manoeuvres performed in the driving simulator highlighted differences in vehicle dynamics across mass configurations, although quantitative metrics were limited by the simulator feedback characteristics and driver variability. Despite these constraints, the simulator experiments offered qualitative insights consistent with theoretical expectations, confirming the sensitivity of vehicle handling and stability to mass distribution and total weight, and supporting the validity of the digital twin for future investigations.