ﻻ يوجد ملخص باللغة العربية
Experimental measurements on commercial adaptive cruise control (ACC) vehicles is becoming increasingly available from around the world, providing an unprecedented opportunity to study the traffic flow characteristics that arise from this technology. This paper adds new experimental evidence to this knowledge base and presents a comprehensive empirical study on the ACC equilibrium behaviors via the resulting fundamental diagrams. We find that like human-driven vehicles, ACC systems display a linear speed-spacing relationship (within the range of available data) but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting, capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast congested wave speed of 50 miles per hour on average. These fast waves are unfamiliar to human drivers, and may or may not pose a safety risk. We also find that ACC jam spacing is much larger than in human traffic, which reduces the network storage capacity. Our findings suggest that future research directions should include ACC in very low speed and complete stop conditions and also the responses of human-drivers to ACC.
This paper investigates the accuracy and robustness of car-following (CF) and adaptive cruise control (ACC) models used to simulate measured driving behaviour of commercial ACCs. To this aim, a general modelling framework is proposed, in which ACC an
Current commercial adaptive cruise control (ACC) systems consist of an upper-level planner controller that decides the optimal trajectory that should be followed, and a low-level controller in charge of sending the gas/brake signals to the mechanical
This paper demonstrates that the acceleration/deceleration limits in ACC systems can make a string stable ACC amplify the speed perturbation in natural driving. It is shown that the constrained acceleration/deceleration of the following ACCs are like
We propose a learning-based, distributionally robust model predictive control approach towards the design of adaptive cruise control (ACC) systems. We model the preceding vehicle as an autonomous stochastic system, using a hybrid model with continuou
In the era of digitalization, utilization of data-driven control approaches to minimize energy consumption of residential/commercial building is of far-reaching significance. Meanwhile, A number of recent approaches based on the application of Willem