國立虎尾科技大學 |

Studies of Adaptive Cruise Control Vehicles Based on Empirical Data.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Studies of Adaptive Cruise Control Vehicles Based on Empirical Data./
Author:	Li, Tienan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
Description:	132 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
Contained By:	Dissertations Abstracts International83-09B.
Subject:	Civil engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28865780
ISBN:	9798790657924

Studies of Adaptive Cruise Control Vehicles Based on Empirical Data.
Li, Tienan.

Studies of Adaptive Cruise Control Vehicles Based on Empirical Data. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 132 p.

Source: Dissertations Abstracts International, Volume: 83-09, Section: B.

Thesis (Ph.D.)--University of Massachusetts Lowell, 2022.

This item must not be sold to any third party vendors.

Emerging automated vehicle (AV) technologies are increasingly being deployed around the world and it is only a matter of time before the transportation landscape changes dramatically. Unfortunately, those changes cannot be well predicted due to the lack of empirical data. But adaptive cruise control (ACC) vehicles are common in the market and can be used to fill this gap. In this thesis, a set of field experiments are proposed to collect the ACC car-following (CF) data. The experiments are carefully designed and executed considering a variety of influential factors in different traffic conditions. Based on the collected data, an in-depth analysis of the ACC behaviors is conducted, which consists of three studies.The first study aims to characterize the empirical microscopic car-following behaviors of a commercial ACC system and understand how ACC behaves in different conditions and the underlying impact mechanism. It is found that for a single ACC: (i) the ACC response time is comparable to human drivers but much larger than the ACC controller time gap and it exhibits small variance, (ii) the ACC response can amplify or dampen an oscillation, (iii) after the oscillation, the stabilization process can exhibit overshooting or undershooting, (iv) these CF behaviors depend largely on the ACC headway setting, speed level, and leader stimulus, which produce the impacts directly and/or indirectly through the mediation of earlier ACC behaviors. For a three-vehicle platoon, the main finding is that the change from one ACC vehicle to the next is progressive for oscillation growth, and regressive for deceleration, acceleration, and overshooting. This implies that in long platoons, oscillation amplitude tends to exacerbate very quickly, which forces ACC vehicles further upstream to apply very strong braking followed by a strong acceleration. This can cause significant overshooting and safety hazards. The second study focuses on the hysteresis and traffic wave features of ACC vehicles in non-equilibrium traffic. Regarding the hysteresis, it is found that (i) CW hysteresis loop is common in ACC systems but CCW loop is rare, (ii) CW loops have profound magnitude, (iii) different ACC systems display different hysteresis features and are distinct from HDV traffic, and (iv) hysteresis is closely related to the delay in ACC's response to leader's speed change. Regarding the traffic wave propagation, it is found the deceleration start wave speed of ACC has a wide range, which is greatly related to the speed and ACC headway setting. Lower speed and large headway both lead to more negative transient waves. The three commercial ACC systems are very different from each other and from human-driven vehicles. The third study presents a comprehensive empirical study on the ACC equilibrium behaviors via the resulting fundamental diagrams. It is found that like human-driven vehicles, ACC systems display a linear equilibrium spacing-speed relationship but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting, equilibrium capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast equilibrium wave speed of 100 kilometers per hour on average. These fast waves are unfamiliar to human drivers and may pose a safety risk. The results also suggest that ACC jam spacing can be much larger than in human traffic.

ISBN: 9798790657924Subjects--Topical Terms:

561339
Civil engineering.
Subjects--Index Terms:

Automated vehicles

Studies of Adaptive Cruise Control Vehicles Based on Empirical Data.
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500 $a Advisor: Chen, Danjue.
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506 $a This item must not be sold to any third party vendors.
520 $a Emerging automated vehicle (AV) technologies are increasingly being deployed around the world and it is only a matter of time before the transportation landscape changes dramatically. Unfortunately, those changes cannot be well predicted due to the lack of empirical data. But adaptive cruise control (ACC) vehicles are common in the market and can be used to fill this gap. In this thesis, a set of field experiments are proposed to collect the ACC car-following (CF) data. The experiments are carefully designed and executed considering a variety of influential factors in different traffic conditions. Based on the collected data, an in-depth analysis of the ACC behaviors is conducted, which consists of three studies.The first study aims to characterize the empirical microscopic car-following behaviors of a commercial ACC system and understand how ACC behaves in different conditions and the underlying impact mechanism. It is found that for a single ACC: (i) the ACC response time is comparable to human drivers but much larger than the ACC controller time gap and it exhibits small variance, (ii) the ACC response can amplify or dampen an oscillation, (iii) after the oscillation, the stabilization process can exhibit overshooting or undershooting, (iv) these CF behaviors depend largely on the ACC headway setting, speed level, and leader stimulus, which produce the impacts directly and/or indirectly through the mediation of earlier ACC behaviors. For a three-vehicle platoon, the main finding is that the change from one ACC vehicle to the next is progressive for oscillation growth, and regressive for deceleration, acceleration, and overshooting. This implies that in long platoons, oscillation amplitude tends to exacerbate very quickly, which forces ACC vehicles further upstream to apply very strong braking followed by a strong acceleration. This can cause significant overshooting and safety hazards. The second study focuses on the hysteresis and traffic wave features of ACC vehicles in non-equilibrium traffic. Regarding the hysteresis, it is found that (i) CW hysteresis loop is common in ACC systems but CCW loop is rare, (ii) CW loops have profound magnitude, (iii) different ACC systems display different hysteresis features and are distinct from HDV traffic, and (iv) hysteresis is closely related to the delay in ACC's response to leader's speed change. Regarding the traffic wave propagation, it is found the deceleration start wave speed of ACC has a wide range, which is greatly related to the speed and ACC headway setting. Lower speed and large headway both lead to more negative transient waves. The three commercial ACC systems are very different from each other and from human-driven vehicles. The third study presents a comprehensive empirical study on the ACC equilibrium behaviors via the resulting fundamental diagrams. It is found that like human-driven vehicles, ACC systems display a linear equilibrium spacing-speed relationship but the key parameters of these relationships can differ significantly from human-driven traffic depending on input settings: At the minimum headway setting, equilibrium capacities in excess of 3500 vehicles per hour are observed, together with an extremely fast equilibrium wave speed of 100 kilometers per hour on average. These fast waves are unfamiliar to human drivers and may pose a safety risk. The results also suggest that ACC jam spacing can be much larger than in human traffic.
590 $a School code: 0111.
650 4 $a Civil engineering. $3 561339
650 4 $a Automotive engineering. $3 1104081
650 4 $a Transportation. $3 558117
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653 $a Adaptive cruise control
653 $a Human-driven vehicles
653 $a ACC jam spacing
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710 2 $a University of Massachusetts Lowell. $b Civil Engineering. $3 1413430
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792 $a 2022
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