Energy and Autonomous Urban Land Vehicles

Folsom, Tyler C.

doi:10.1109/mts.2012.2196339

Cited by 24 publications

(21 citation statements)

References 16 publications

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“…It is notable that they were not including driver comfort, acceptance, or average use conditions. Finally, several recent works have bounded the energy implications from automated vehicles (Anderson, J. et al, 2014;Brown et al, 2014;Daniel J. Fagnant, 2014;Fagnant and Kockelman, 2015;Feng et al, 2015;Folsom, 2012;Gonder et al, 2012;Greenblatt and Saxena, 2015;Iii et al, 2014;Shladover, S, 2012;Wadud Z et al, 2013)], but fuel economy modeling and implications remains a critical research need.…”

Section: 2: Current Drive Cyclesmentioning

confidence: 99%

Fuel economy testing of autonomous vehicles

Mersky

Samaras

2016

Transportation Research Part C: Emerging Technologies

141

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Section: 2: Current Drive Cyclesmentioning

confidence: 99%

Fuel economy testing of autonomous vehicles

Mersky

Samaras

2016

Transportation Research Part C: Emerging Technologies

141

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“…Furthermore, a platoon of closely spaced AVs that stops or slows down less often will resemble a train. The result is expected to result in lower peak speeds (improving fuel economy) but higher effective speeds (improving travel time) [63,64].…”

Section: Environment (Energy and Emission)mentioning

confidence: 99%

Autonomous vehicles: challenges, opportunities, and future implications for transportation policies

et al. 2016

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This study investigates the challenges and opportunities pertaining to transportation policies that may arise as a result of emerging autonomous vehicle (AV) technologies. AV technologies can decrease the transportation cost and increase accessibility to low-income households and persons with mobility issues. This emerging technology also has far-reaching applications and implications beyond all current expectations. This paper provides a comprehensive review of the relevant literature and explores a broad spectrum of issues from safety to machine ethics. An indispensable part of a prospective AV development is communication over cars and infrastructure (connected vehicles). A major knowledge gap exists in AV technology with respect to routing behaviors. Connectedvehicle technology provides a great opportunity to implement an efficient and intelligent routing system. To this end, we propose a conceptual navigation model based on a fleet of AVs that are centrally dispatched over a network seeking system optimization. This study contributes to the literature on two fronts: (i) it attempts to shed light on future opportunities as well as possible hurdles associated with AV technology; and (ii) it conceptualizes a navigation model for the AV which leads to highly efficient traffic circulations.

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“…Vehicles that communicate with one another could reduce the time they are stopped, improving both traffic and drive-cycle efficiencies. Further, a platoon of closely spaced AVs that stops or slows down less often thereby resembles a train, enabling lower peak speeds (improving fuel economy) but higher effective speeds (improving travel time) (Folsom, 2012).…”

Section: Car Mpgmentioning

confidence: 99%

“…Folsom (2012) estimates that a networked pod car AV system could enable fuel economies as much as 500 to 1,000 mpg. 9 Using these estimates, we present ranges of potential fuel economy improvements for conventional cars, hybrid cars, and autonomous cars (omitting light trucks) in Figure 2.6.…”

Section: Car Mpgmentioning

confidence: 99%