Régulateur de vitesse automatique

Regulatory gaps in restart and cold/hot start emissions overlooked by current periodic technical inspection (PTI), and driving behaviors significantly impact plug-in hybrid electric vehicle (PHEV) particle number (PN) emissions under real driving conditions. Using portable emissions measurement systems (PEMS), this study builds cumulative PN emissions by key segments (cold-start, restart) and instantaneous high-emission events across four distinct behaviors. Key findings reveal that calm and...

Adaptive cruise control (ACC) plays a critical role in enhancing road safety and energy efficiency in electric vehicles (EVs). Traditional ACC approaches often face challenges in adapting to complex, dynamic driving environments. AI-driven reinforcement learning (RL) has emerged as a promising solution; however, its real-world adoption faces key challenges, including training stability, convergence speed, and robustness in diverse scenarios. This work reformulates the ACC control structure using...

CONCLUSION: Short, targeted training can significantly improve safe and effective VA system use, particularly for senior drivers. These results highlight training as a proactive safety intervention to reduce human-automation mismatch and enhance system reliability in real-world driving.

Understanding the root causes of autonomous vehicle (AV) crashes is crucial for enhancing road safety and advancing the commercialization of autonomous driving. This study aims to investigate the relative contributions of system functions, driver behaviors, and kinematics to AV crash causations, with a focus on how they affect crash injury severity. To accurately capture the thorough growth processes of crashes near injuries, we analyzed 19 AV crash cases obtained from the Traffic Accident...

The growing reliance on Vehicle-to-Vehicle (V2V) communication has heightened the vulnerability of Adaptive Cruise Control (ACC) systems to cybersecurity threats, such as manipulation or forgery of V2V messages. This paper investigates the impact of three types of false information injection (FII) on vehicle collision risk and driving efficiency. To address these vulnerabilities, we develop a novel machine learning-based onboard model, ACC anomaly Detection and Mitigation (ACCDM), designed to...

Driven by advancements in emerging technologies and data-driven innovations, the global automotive industry is focusing on intelligent and connected vehicles (ICVs), which involve complex electronic systems and vast data interactions. Safety concerns have expanded beyond traditional safety measures to include functional safety, safety of the intended functionality (SOTIF), and cybersecurity. Despite their interconnected nature, current methods often address these domains separately, risking...

This paper proposes a practical design guideline for selecting control parameters in adaptive cruise control (ACC) systems to ensure both individual vehicle stability and string stability in vehicle following systems with homogeneous longitudinal dynamics. The primary control objective is to regulate spacing errors under a constant time-gap policy, which is commonly adopted in ACC applications. By employing a simple proportional-derivative (PD) controller, we present a clear methodology for...

In this paper, we propose systematic controller design guidelines to ensure both individual vehicle stability and string stability in cooperative adaptive cruise control (CACC)-based platoon systems, assuming a homogeneous platoon where all vehicles share identical dynamic models. We rigorously demonstrate that the limitation of conventional adaptive cruise control (ACC) in maintaining the target inter-vehicle distance can be effectively overcome by incorporating the desired acceleration of the...

INTRODUCTION: Partial automation is still evolving. There is need to understand how behavior changes over time as drivers develop familiarity with the technology. In Reagan et al. (2021;Transportation Research Part F,82), volunteers driving a Volvo S90 with adaptive cruise control (ACC) and Pilot Assist, which couples ACC and continuous lane centering, hadhigher likelihood ofvisual-manual disengagement when using Pilot Assist in the second portion of a 4-week field trial compared with manual...

Drivers of partially automated vehicles are relieved from operational driving tasks but are still expected to be prepared to assume control of the vehicle when the capabilities of driving automation are exceeded. Thus, drivers' capability to perceive hazards and react proactively may still benefit driving safety in the context of driving automation. Previous research has found that experience and distractions can affect drivers' hazard perception performance in vehicles without automation, while...

This study presents an analytical solution for the vehicle state evolution of Adaptive Cruise Control (ACC) systems under cut-in scenarios, incorporating sensing delays and anticipation using the Lambert W function. The theoretical analysis demonstrates that the vehicle state evolution and the corresponding safety of ACC in cut-in situations are influenced by multiple factors, including the original leading vehicle's state, the initial conditions of the cut-in vehicle, subsequent cut-in...