An Analysis of Possible Energy Impacts of Automated Vehicles

Brown, Austin; Gonder, Jeffrey; Repac, Brittany

doi:10.1007/978-3-319-05990-7_13

Cited by 171 publications

(160 citation statements)

References 6 publications

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“…Wadud et al (2016) concluded that annual VMT could rise as much as 10% from increased travel due to new users. Brown et al (2014) Other studies have estimated how VMT per vehicle and daily VMT could change as a result of automation. Schoettle and Sivak (2015) estimated that VMT per automated vehicle could increase by as much as 75% due to a reduction in vehicle ownership rates, while Fagnant and Kockelman.…”

Section: Summary Of Previous Studiesmentioning

confidence: 99%

“…Páez et al (2012) found that people with disabilities who have used a car within the past 12 months are about 28% more likely to desire more leisure activities compared to those who have not (Páez and Farber, 2012) Many companies have announced plans to develop self-driving vehicles, and twelve companies have applied to test self-driving cars in California as of 2016 (Chew, 2016). Vehicle automation has the potential to greatly improve travel by reducing congestion, travel times, crashes, and potentially energy consumption (Anderson et al, 2014;Brown et al, 2014;Harper et al, 2016;Levin and Boyles, 2015;Mersky and Samaras, 2016;Wadud et al, 2016). The ability for smart vehicles to interact with smartphones and act as a taxi service to transport people to their destinations also serves as an advantage, reducing travel costs by almost 75 percent (Litman, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…One of the scenarios examined in this analysis assumed road capacity will increase by 30% while the value of travel times and parking costs will decrease by 65% and 50%, respectively, resulting in a 20% increase in VMT (Childress et al, 2015). Brown et al (2014) estimated that new demand from underserved populations could increase VMT by as much as 40%, using the 2009 NHTS and the 2003 "Freedom of Travel" study (Brown et al, 2014). This upper bound is estimated by assuming that each population segment from age 16 to 85 begins to travel as much as the top decile or travelers.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Harper

Hendrickson

Mangones

et al. 2016

Transportation Research Part C: Emerging Technologies

359

168

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Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19-64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.

show abstract

Section: Summary Of Previous Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Harper

Hendrickson

Mangones

et al. 2016

Transportation Research Part C: Emerging Technologies

359

168

View full text Add to dashboard Cite

show abstract

“…Connected driving can prevent, reduce or avoid stop-and-go traffic and congestion [13,36]. The so-called platooning (travelling close together at high speed) can be used to improve traffic safety, optimize traffic flow, and reduce CO2 emissions, since vehicles can exchange data with each other and coordinate driving speed, braking characteristics and distances between vehicles [7,40]. Thus, energy consumption could be reduced [7].…”

Section: Positive Environmental Effects A) Positive Impacts On Traffimentioning

confidence: 99%

“…The so-called platooning (travelling close together at high speed) can be used to improve traffic safety, optimize traffic flow, and reduce CO2 emissions, since vehicles can exchange data with each other and coordinate driving speed, braking characteristics and distances between vehicles [7,40]. Thus, energy consumption could be reduced [7]. As accidents are avoided by using autonomous and connected cars, vehicles require lower safety standards such as airbags and steel constructions than today and would therefore lose weight [2,4].…”

Section: Positive Environmental Effects A) Positive Impacts On Traffimentioning

confidence: 99%

Shared Autonomous Vehicles: Potentials for a Sustainable Mobility and Risks of Unintended Effects

Pakusch¹,

Stevens²,

Bossauer³

EPiC Series in Computing

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Automated and connected cars could significantly reduce congestion and emissions through a more efficient flow of traffic and a reduction in the number of vehicles. An increase in demand for driving with autonomous vehicles is also conceivable due to higher comfort and improved quality of time using driverless cars. So far, empirical evidence supporting this hypothesis is missing. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as an indicator for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 German participants. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether traditional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more effort should be placed in making public transportation more attractive if sustainable mobility is to be developed.

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Connected autonomous vehicles: State of practice

Islam

Newaz

Song

et al. 2023

Appl Stoch Models Bus & Ind

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Connected autonomous vehicles (CAVs) have the potential to deal with the steady increase in road traffic while solving transportation related issues such as traffic congestion, pollution, and road safety. Therefore, CAVs are becoming increasingly popular and viewed as the next generation transportation solution. Although modular advancements have been achieved in the development of CAVs, these efforts are not fully integrated to operationalize CAVs in realistic driving scenarios. This paper surveys a wide range of efforts reported in the literature about the CAV developments, summarizes the CAV impacts from a statistical perspective, explores current state of practice in the field of CAVs in terms of autonomy technologies, communication backbone, and computation needs. Furthermore, this paper provides general guidance on how transportation infrastructures need to be prepared in order to effectively operationalize CAVs. The paper also identifies challenges that need to be addressed in near future for effective and reliable adoption of CAVs.

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An Analysis of Possible Energy Impacts of Automated Vehicles

Cited by 171 publications

References 6 publications

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Shared Autonomous Vehicles: Potentials for a Sustainable Mobility and Risks of Unintended Effects

Connected autonomous vehicles: State of practice

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