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FIELD EXPERIMENT ON THE CAPACITY IMPACT OF VEHICLE AUTOMATION ON ELECTRIC VEHICLES (EVS) – CASE STUDY OF ADAPTIVE CRUISE CONTROL (ACC)

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Date Issued:
2023
Abstract/Description:
Today’s mainstream vehicles are partially automated via an Advanced Driver Assistance Feature (ADAS) known as Adaptive Cruise Control (ACC). ACC relies on data from onboard sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, when ACC is paired with fully electric vehicles (EVs), EV’s unique powertrain characteristics such as instantaneous torque and aggressive regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of car following field experiments. Field experiments demonstrate that EVs with ACC can achieve a capacity as high as 3333 veh/hr/lane when cruising in steady state conditions at typical freeway speeds (60 mph and 55 mph) and arterial speeds (45 mph and 35 mph). Furthermore, speed fluctuations and disturbances that may come from queues forming at or near the bottleneck do not reduce the capacity, unlike ACC-equipped internal combustion engine (ICE) vehicles, making ACC-equipped EVs outperform ICE vehicles with ACC, as well as human drivers.
Title: FIELD EXPERIMENT ON THE CAPACITY IMPACT OF VEHICLE AUTOMATION ON ELECTRIC VEHICLES (EVS) – CASE STUDY OF ADAPTIVE CRUISE CONTROL (ACC).
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Name(s): Majumder, Tasnim Anika, author
Kan, David , Thesis advisor
Florida Atlantic University, Degree grantor
Department of Civil, Environmental and Geomatics Engineering
College of Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2023
Date Issued: 2023
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 90 p.
Language(s): English
Abstract/Description: Today’s mainstream vehicles are partially automated via an Advanced Driver Assistance Feature (ADAS) known as Adaptive Cruise Control (ACC). ACC relies on data from onboard sensors to automatically adjust speed to maintain a safe following distance with the preceding vehicle. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, when ACC is paired with fully electric vehicles (EVs), EV’s unique powertrain characteristics such as instantaneous torque and aggressive regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of car following field experiments. Field experiments demonstrate that EVs with ACC can achieve a capacity as high as 3333 veh/hr/lane when cruising in steady state conditions at typical freeway speeds (60 mph and 55 mph) and arterial speeds (45 mph and 35 mph). Furthermore, speed fluctuations and disturbances that may come from queues forming at or near the bottleneck do not reduce the capacity, unlike ACC-equipped internal combustion engine (ICE) vehicles, making ACC-equipped EVs outperform ICE vehicles with ACC, as well as human drivers.
Identifier: FA00014283 (IID)
Degree granted: Thesis (MS)--Florida Atlantic University, 2023.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Automated vehicles
Electric vehicles
Adaptive control systems
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00014283
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Host Institution: FAU