Design of string stable adaptive cruise controllers for highway and urban missions

Bayezit, İsmail; Veldhuizen, Tjalling; Fi̇dan, Barış; Huissoon, Jan P.; Lupker, Henk

doi:10.1109/allerton.2012.6483206

Cited by 9 publications

(6 citation statements)

References 3 publications

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“…The controller dynamics in (22) and spacing policy dynamics in (23) are depicted in Fig. 7 [17]. In this figure, Hi = hd, is represents spacing dynamics, Xi and Xi-l represent the actual positions of our vehicle and the vehicle immediately ahead.…”

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

“…Feedback adaptive cruise controller in (22) is a PD filter with a breakpoint at WK,i radls, which is assumed to satisfy the condition � » WK,i [17]. This controller also has a mass factor that eliminates the mass constant in system dynamics.…”

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

“…The vehicles' acceleration shockwave attenuation in the upstream of the platoon is calculated with string stability formulation. The aim of control and external UAV support for keeping the inter-vehicle and inter-platoon string stability condition lower than or equal to 1 [17].…”

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

“…Then, we will give brief details of longitudinal platoon control strategy for cars at highways [17]. Finally, the mathematical background of the contribution of autonomous UAVs on traffic flow as dynamic roadside agents will be provided.…”

Section: Control Designmentioning

confidence: 99%

“…), which is modeled as a first order system (Ga c tJ as it can be seen in (21). For stabilizing the vehicle's longitudinal motion and keeping a safe distance between vehicles in a platoon, both position error epi and velocity error evi are considered and desired force is generated as the output of high-level control block [17].…”

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

See 4 more Smart Citations

Experimental modeling and adaptive control of an unmanned aerial vehicle as roadside assistance

Bayezit

Tsourdos

Fi̇dan

et al. 2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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Small scale fixed-wing unmanned aerial vehicles (UAV) are an emerging technology, and have been widely used in many many manned/unmanned and cooperative operations as research testbeds. This paper describes the realistic mod eling and adaptive autonomous control of a small scale UAV that serves as a dynamic roadside agent to provide critical roadside assistance and manage highway traffic. Additionally, the importance and implementation of dynamic roadside op erations to optimize platoon acceleration and avoid rush hour traffic congestion are discussed. The steady-state flight trim and model-decomposition of 6 Degree-of-Freedom (DOF) UAV model using small perturbation theory are provided. Finally, the implementation of an autonomous adaptive control approach is given which is advantageous over other linear based control approaches for small-scale UAVs.

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Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

Section: Control Designmentioning

confidence: 99%

Section: B Adaptive Cruise Control Strategy For Highway Platoonmentioning

confidence: 99%

See 3 more Smart Citations

Experimental modeling and adaptive control of an unmanned aerial vehicle as roadside assistance

Bayezit

Tsourdos

Fi̇dan

et al. 2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

Self Cite

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Impact of Communications Delay on Safety and Stability of Connected and Automated Vehicle Platoons: Empirical Evidence From Experimental Data

Khattak,

Rios-Torres,

Fontaine

2023

IEEE Access

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Advances in communications and sensing technology have enabled the development of cooperative ITS technologies such as connected and automated vehicle (CAV) applications including adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) that could perform driving tasks with little human feedback. However, there are some key concerns and knowledge gaps regarding the impact of delay in communicated messages on CAV platoon safety and stability. This study contributes by analyzing the impact of delay while controlling for other factors on CAV platoon safety and stability using the concept of driving volatility. Real-world experimental data from a field test were used to examine the lead vehicle (LV) and following vehicles (FVs) behavior in a five-vehicle platoon with multiple scenarios by developing switching regime models. Results show that CACC reduces volatility in both LV and FVs compared to ACC system which can be attributed to the vehicular communication and motion synchronization of CACC. However, delay is observed to increase the likelihood of volatility and contribute to instability of platoons. FVs have more volatile behavior as compared to LV since the instability is transmitted through the string of the platoon. Further, Bayesian model reveals that a unit increase in delay is observed to increase the collision risk by 4%. Other confounding factors such as disengagement and ACC override contribute to higher volatility of platoon while the likelihood of high volatility in both LV and FVs decreases with increases in gap to the preceding vehicle. The risk of collision is expected to increase by 6.2% in response to a unit increase in disengagements. Likewise, ACC override increases the risk of collisions by 5.4%. These results have practical implications for considering delays in CAV performance analysis and for designing robust CACC algorithms with minimum delays in the future.

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Deadzone switching based cooperative adaptive cruise control with rear-end collision check

Sancar

Fi̇dan

Huissoon

2015

2015 International Conference on Advanced Robotics (ICAR)

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Design of string stable adaptive cruise controllers for highway and urban missions

Cited by 9 publications

References 3 publications

Experimental modeling and adaptive control of an unmanned aerial vehicle as roadside assistance

Experimental modeling and adaptive control of an unmanned aerial vehicle as roadside assistance

Impact of Communications Delay on Safety and Stability of Connected and Automated Vehicle Platoons: Empirical Evidence From Experimental Data

Deadzone switching based cooperative adaptive cruise control with rear-end collision check

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