Automatic Cruise Control

The rapid advancement of automotive technologies has spurred the development of innovative applications within intelligent transportation systems (ITS), aimed at enhancing safety, efficiency and sustainability. These applications, such as advanced driver assistance systems (ADAS), vehicle-to-everything (V2X) communication and autonomous driving, are transforming transportation by enabling adaptive cruise control, lane-keeping assistance, real-time traffic management and predictive maintenance....

CONCLUSIONS: Optimization of key parameters such as triggering strategy, deceleration, sensor range, and field of view is crucial for maximizing the effectiveness of ARAS in motorcycle safety applications. These findings provide valuable insights for manufacturers and policymakers, highlighting the need for tailored approaches to system design and implementation. By refining these systems based on empirical data and analysis, significant improvements can be made in motorcycle safety, ultimately...

INTRODUCTION: While SAE Level 2 systems combining Adaptive Cruise Control (ACC) and lane centering functionality can conveniently reduce the need for the driver to frequently brake, accelerate, and steer the vehicle, the potential safety benefit of such systems merit further exploration.

OBJECTIVE: Although partial driving automation systems are usually discussed as convenience features, consumers sometimes consider them to be safety features. The goal of this study was to assess if partial driving automation reduces rear-end and lane departure crashes beyond safety systems like automatic emergency braking (AEB) and lane departure prevention (LDP).

Traffic signals, while reducing conflicts within intersections, often lead to stop-and-go behaviors in approaching vehicles, negatively impacting traffic flow in terms of safety, efficiency, and fuel consumption. Aimed at minimizing the traffic oscillations caused by traffic signals through Connected and Autonomous Vehicles (CAVs) and meeting real-time operational needs, this paper proposes a Risk-Based Adaptive Cruise Control (RACC). RACC designs the constraints of approaching a signalized...

This paper presents a comprehensive analysis of the impact of adaptive cruise control on energy consumption in real-world driving conditions based on a natural experiment: a large-scale observational dataset of driving data from a diverse fleet of vehicles and drivers. The analysis is conducted at two different fidelity levels: (1) a macroscopic trip-level benefit estimate that compares trips with and without cruise control in a counterfactual way using statistical methods, and (2) a...

Vehicle platooning improves energy savings via vehicle-to-vehicle (V2V) communication. Ecological cooperative adaptive cruise control (Eco-CACC) is implemented in platoons for merging task by using regrouped platoon models. The merging positions are selected in the middle and tail of an original platoon with a two-vehicle sub-platoon. The distributed nonlinear model predictive controller based on signal temporal logic (DNMPC-STL) approach is developed to model the Eco-CACC merging strategy. The...

Mixed traffic environments combining human-driven vehicles (HDVs) and those equipped with Adaptive Cruise Control (ACC) have already become prevalent. This study tackles the critical yet underexplored threat of sensing attacks, such as jamming and spoofing, on ACC systems. By applying stochastically calibrated ACC and HDV car-following models grounded in field data, we constructed an integrated and high-fidelity framework to simulate mixed traffic. This allows us to comprehensively analyze...

This paper aims to thoroughly examine and compare advanced driver-assistance systems (ADASs) in the context of their impact on safety and driving comfort. It also sought to determine the level of acceptance and trust drivers have in these systems. The first chapter of this document describes the sensory detectors used in ADASs, including radars, cameras, LiDAR, and ultrasonics. The subsequent chapter presents the most popular driver assistance systems, including adaptive cruise control (ACC),...

The development of autonomous driving vehicles has increased the global demand for robust and efficient automotive radar systems. This study proposes an automotive radar-based ego-vehicle speed detection network (AVSD Net) model using convolutional neural networks for estimating the speed of the ego vehicle. The preprocessing and postprocessing methods used for vehicle speed correction are presented in detail. The AVSD Net model exhibits characteristics that are independent of the angular...

Extensive experimental analyses concerned with Adaptive Cruise Control (ACC) have clearly shown that such systems have failed to deliver the promise of safe and traffic-flow effective car-following. On the contrary, large reaction times and poor string stability performances characterize commercial ACCs. While a huge research line is investigating the introduction of communication among vehicles to overcome the mentioned limitation, market adoption of connectivity-enhanced vehicles is...

Parkinson's disease (PD) negatively affects driver fitness. Few studies document the benefits of in-vehicle information systems (IVIS) and advanced-driver assistance systems (ADAS), the focus of this study, for drivers with PD. This study quantified the impact of IVIS and ADAS on the number of on-road driving errors. Drivers with PD (N = 107) drove a vehicle equipped with IVIS and ADAS in traffic. The activation of IVIS and ADAS resulted in fewer driver errors. Specifically, adaptive cruise...

Car-following models are crucial in adaptive cruise control systems, making them essential for developing intelligent transportation systems. This study investigates the characteristics of high-speed traffic flow by analyzing the relationship between headway distance and dynamic desired distance. Building upon the optimal velocity model theory, this paper proposes a novel traffic car-following computing system in the time domain by incorporating an absolutely safe time headway strategy and a...

In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajectory tracking, adaptive cruise control (ACC), and active obstacle avoidance under high vehicle speed. Firstly, an MPC-based trajectory tracking controller is designed based on the vehicle dynamics model. Then, the MPC was combined with ACC to design...

In this manuscript, we delve into the realm of lattice ordered complex linear diophantine fuzzy soft set, which constitutes an invaluable extension to the existing Fuzzy set theories. Within this exploration, we investigate basic operations such as ⊕ and ⊗ , together with their properties and theorems. This manuscript is more amenable in two ways, i.e., it enables real-life problems involving parametrization tool and applications with an existing order between the components of the parameter set...