Adaptive cruise control design for active congestion avoidance

Kesting, Arne; Treiber, Martin; Schönhof, Martin; Helbing, Dirk

doi:10.1016/j.trc.2007.12.004

Cited by 529 publications

(279 citation statements)

References 21 publications

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“…These connected vehicles with some common interests can cooperatively drive on the road, e.g., platoon-based driving pattern, which may significantly improve the traffic safety and efficiency (Farah and Koutsopoulos, 2014, Kesting et al, 2010a, 2008, Milans et al, 2014, Monteil et al, 2013, Ngoduy, 2013a, van Arem et al, 2006.…”

Section: Introductionmentioning

confidence: 99%

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

Jia

Ngoduy

2016

Transportation Research Part C: Emerging Technologies

234

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Recent developments of information and communication technologies (ICT) have enabled vehicles to timely communicate with each other through wireless technologies, which will form future (intelligent) traffic systems (ITS) consisting of so-called connected vehicles. Cooperative driving with the connected vehicles is regarded as a promising driving pattern to significantly improve transportation efficiency and traffic safety. Nevertheless, unreliable vehicular communications also introduce packet loss and transmission delay when vehicular kinetic information or control commands are disseminated among vehicles, which brings more challenges in the system modelling and optimization. Currently, no data has been yet available for the calibration and validation of a model for ITS, and most research has been only conducted for a theoretical point of view. Along this line, this paper focuses on the (theoretical) development of a more general (microscopic) traffic model which enables the cooperative driving behaviour via a so-called inter-vehicle communication (IVC). To this end, we design a consensus-based controller for the cooperative driving system (CDS) considering (intelligent) traffic flow that consists of many platoons moving together. More specifically, the IEEE 802.11p, the de-facto vehicular networking standard required to support ITS applications, is selected as the IVC protocols of the CDS, in order to investigate how the vehicular communications affect the features of intelligent traffic flow. This study essentially explores the relationship between IVC and cooperative driving, which can be exploited as the reference for the CDS optimization and design.

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Section: Introductionmentioning

confidence: 99%

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

Jia

Ngoduy

2016

Transportation Research Part C: Emerging Technologies

234

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“…9, a hierarchical view can be used to represent the dependencies and inherited properties which makes use of the object-oriented programming paradigm by representing and abstracting functional units as classes. The best example is the representation of a driver-vehicle agent as an abstract class with several possible designs for human drivers, vehicles equipped with adaptive cruise control [KTSH07,KTSH08] or even driverless ones as recently demonstrated in reality [ (DA07]. However, each agent has a number of defining properties such as length, width, weight, form and color.…”

Section: Simulator Designmentioning

confidence: 99%

Agents for Traffic Simulation

Kesting¹,

Treiber²,

Helbing³

2009

Computational Analysis, Synthesis, &Amp; Design Dynamic Systems

Self Cite

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Vehicular traffic is a classical example of a multi-agent system in which autonomous drivers operate in a shared environment. The article provides an overview of the state-of-the-art in microscopic traffic modeling and the implications for simulation techniques. We focus on the short-time dynamics of car-following models which describe continuous feedback control tasks (acceleration and braking) and models for discrete-choice tasks as a response to the surrounding traffic. The driving style of an agent is characterized by model parameters such as reaction time, desired speed, desired time gap, anticipation etc. In addition, internal state variables corresponding to the agent's "mind" are used to incorporate the driving experiences. We introduce a time-dependency of some parameters to describe the frustration of drivers being in a traffic jam for a while. Furthermore, the driver's behavior is externally influenced by the neighboring vehicles and also by environmental input such as limited motorization and braking power, visibility conditions and road traffic regulations. A general approach for dealing with discrete decision problems in the context of vehicular traffic is introduced and applied to mandatory and discretionary lane changes. Furthermore, we consider the decision process whether to brake or not when approaching a traffic light turning from green to amber. Another aspect of vehicular traffic is related to the heterogeneity of drivers. We discuss a hybrid system of coupled vehicle and information flow which can be used for developing and testing applications of upcoming inter-vehicle communication techniques.

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“…Various authors have shown that if 30% of vehicles had ACC, the formation of jams in heavy traffic could be eliminated [1][2][3][4][5][6][7][8][9][10]. The ACC vehicles are assumed to be governed by control parameters that give string stability [11].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear dynamics of autonomous vehicles with limits on acceleration

Davis¹

2014

Physica A: Statistical Mechanics and its Applications

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The stability of autonomous vehicle platoons with limits on acceleration and deceleration is determined.If the leading-vehicle acceleration remains within the limits, all vehicles in the platoon remain within the limits when the relative-velocity feedback coefficient is equal to the headway time constant [ ⁄ .Furthermore, if the sensitivity ⁄ , no collisions occur. String stability for small perturbations is assumed and the initial condition is taken as the equilibrium state. Other values of and that give stability with no collisions are found from simulations. For vehicles with non-negligible mechanical response, simulations indicate that the acceleration-feedback-control gain might have to be dynamically adjusted to obtain optimal performance as the response time changes with engine speed. Stability is demonstrated for some perturbations that cause initial acceleration or deceleration greater than the limits, yet do not cause collisions.

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Adaptive cruise control design for active congestion avoidance

Cited by 529 publications

References 21 publications

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

Agents for Traffic Simulation

Nonlinear dynamics of autonomous vehicles with limits on acceleration

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