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Daniel J. Fagnant

Other affiliations: University of Texas at Austin
Bio: Daniel J. Fagnant is an academic researcher from University of Utah. The author has contributed to research in topics: Travel behavior & Trip generation. The author has an hindex of 9, co-authored 14 publications receiving 4111 citations. Previous affiliations of Daniel J. Fagnant include University of Texas at Austin.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors proposed a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy, which can be used to improve vehicle safety, congestion, and travel behavior.
Abstract: Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.

2,053 citations

01 Jan 2014
TL;DR: In this paper, the authors proposed a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy for personal travel in the United States, which is based on the work of the authors of this paper.
Abstract: Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to the transportation system This new technology has the potential to impact vehicle safety, congestion, and travel behavior All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2,000 to per year per AV, and may eventually approach nearly $4,000 when comprehensive crash costs are accounted for Yet barriers to implementation and mass-market penetration remain Initial costs will likely be unaffordable Licensing and testing standards in the US are being developed at the state level, rather than nationally, which may lead to inconsistencies across states Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy

1,436 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use.
Abstract: Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.

938 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the potential implications of the SAV at a low level of market penetration (1.3% of regional trips) by simulating a fleet of SAVs serving travelers in the 12-mi by 24-mi regional core of Austin, Texas.
Abstract: The emergence of automated vehicles holds great promise for the future of transportation. Although commercial sales of fully self-driving vehicles will not commence for several more years, once these sales are possible a new transportation mode for personal travel promises to arrive. This new mode is the shared autonomous (or fully automated) vehicle (SAV), combining features of short-term, on-demand rentals with self-driving capabilities: in essence, a driverless taxi. This investigation examined the potential implications of the SAV at a low level of market penetration (1.3% of regional trips) by simulating a fleet of SAVs serving travelers in the 12-mi by 24-mi regional core of Austin, Texas. The simulation used a sample of trips from the region’s planning model to generate demand across traffic analysis zones and a 32,272-link network. Trips called on the vehicles in 5-min departure time windows, with link-level travel times varying by hour of day based on MATSIM’s dynamic traffic assignment simulatio...

285 citations

01 Jan 2014
TL;DR: In this paper, the authors present an introduction for transportation professionals and policymakers to AV technology, potential impacts, and hurdles, and suggest that the U.S. and other countries should create nationally recognized licensing structures for AVs, and determine appropriate standards for liability, security, and data privacy.
Abstract: 27 28 Autonomous vehicles (AVs) represent a potentially disruptive and beneficial change to the way 29 in which we travel. This new technology has the potential to impact personal travel across a 30 wide array of impacts including safety, congestion, and travel behavior. All told, major social 31 AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking 32 benefits are likely on the order of $2,000 per year per AV, or $3,000 eventually increasing to 33 nearly $5,000 when comprehensive crash costs are accounted for. 34 35 Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be 36 unaffordable and licensing and testing standards in the U.S. are being developed at the state 37 level, rather than adopting a national framework, which may lead to inconsistencies across states. 38 Liability regimes remain undefined, security concerns linger, and absent new privacy standards, 39 a default lack of privacy for personal travel may become the norm. Finally, with the advent of 40 this new technology, many impacts, interactions with other components of the transportation 41 system, and implementation details remain uncertain. To address these concerns, research in 42 these areas should be expanded, and the U.S. and other countries should create nationally 43 recognized licensing structures for AVs, and determine appropriate standards for liability, 44 security, and data privacy. 45 46 2 INTRODUCTION 1 Over the past years the automobile and technology industries have made significant leaps in 2 bringing computerization into what has for over a century been exclusively a human function: 3 driving. New cars increasingly include features such as adaptive cruise control and parking assist 4 systems that allow cars to steer themselves into parking spaces. Some companies have pushed 5 the envelope even further by creating almost fully autonomous vehicles (AVs) that can navigate 6 highways and urban environments with almost no direct human input. Assuming that these 7 technologies become successful and enter the mass market, AVs have the potential to 8 dramatically change transportation. This paper serves as an introduction for transportation 9 professionals and policymakers to AV technology, potential impacts, and hurdles. 10 11 AVs may fundamentally alter transport systems. They have the potential to avert deadly crashes, 12 provide mobility to the elderly and disabled, increase road capacity, save fuel, and lower harmful 13 emissions. Complementary trends (in shared rides and vehicles) may lead us …

78 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, the authors calculate the number of miles of driving that would be needed to provide clear statistical evidence of autonomous vehicle safety and show that fully autonomous vehicles would have to be driven hundreds of millions of miles and sometimes hundreds of billions of miles to demonstrate their reliability in terms of fatalities and injuries.
Abstract: How safe are autonomous vehicles? The answer is critical for determining how autonomous vehicles may shape motor vehicle safety and public health, and for developing sound policies to govern their deployment. One proposed way to assess safety is to test drive autonomous vehicles in real traffic, observe their performance, and make statistical comparisons to human driver performance. This approach is logical, but it is practical? In this paper, we calculate the number of miles of driving that would be needed to provide clear statistical evidence of autonomous vehicle safety. Given that current traffic fatalities and injuries are rare events compared to vehicle miles traveled, we show that fully autonomous vehicles would have to be driven hundreds of millions of miles and sometimes hundreds of billions of miles to demonstrate their reliability in terms of fatalities and injuries. Under even aggressive testing assumptions, existing fleets would take tens and sometimes hundreds of years to drive these miles—an impossible proposition if the aim is to demonstrate their performance prior to releasing them on the roads for consumer use. These findings demonstrate that developers of this technology and third-party testers cannot simply drive their way to safety. Instead, they will need to develop innovative methods of demonstrating safety and reliability. And yet, the possibility remains that it will not be possible to establish with certainty the safety of autonomous vehicles. Uncertainty will remain. Therefore, it is imperative that autonomous vehicle regulations are adaptive—designed from the outset to evolve with the technology so that society can better harness the benefits and manage the risks of these rapidly evolving and potentially transformative technologies.

939 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use.
Abstract: Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.

938 citations

01 Jan 2015
TL;DR: In this article, the authors explore the impacts that autonomous vehicles are likely to have on travel demands and transportation planning and explore how they will affect planning decisions such as optimal road, parking and public transit supply.
Abstract: This paper explores the impacts that autonomous (also called self-driving, driverless or robotic) vehicles are likely to have on travel demands and transportation planning. It discusses autonomous vehicle benefits and costs, predicts their likely development and implementation based on experience with previous vehicle technologies, and explores how they will affect planning decisions such as optimal road, parking and public transit supply. The analysis indicates that some benefits, such as independent mobility for affluent non-drivers, may begin in the 2020s or 2030s, but most impacts, including reduced traffic and parking congestion (and therefore road and parking facility supply requirements), independent mobility for low-income people (and therefore reduced need to subsidize transit), increased safety, energy conservation and pollution reductions, will only be significant when autonomous vehicles become common and affordable, probably in the 2040s to 2060s, and some benefits may require prohibiting human-driven vehicles on certain roadways, which could take longer.

764 citations