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.

https://www.aamva.org/WorkArea/DownloadAsset.aspx?id=6738

Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has been an area of research focus for many decades. However, in the absence of detailed driving data that would help improve the identification of cause and effect relationships with individual vehicle crashes, most researchers have addressed this problem by framing it in terms of understanding the factors that affect the frequency of crashes - the number of crashes occurring in some geographical space (usually a roadway segment or intersection) over some specified time period. This paper provides a detailed review of the key issues associated with crash-frequency data as well as the strengths and weaknesses of the various methodological approaches that researchers have used to address these problems. While the steady march of methodological innovation (including recent applications of random parameter and finite mixture models) has substantially improved our understanding of the factors that affect crash-frequencies, it is the prospect of combining evolving methodologies with far more detailed vehicle crash data that holds the greatest promise for the future.

http://ceprofs.tamu.edu/dlord/Papers/Lord-Mannering_Review.pdf

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

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

Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations

Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging.

We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.

/pdf/a-multiagent-approach-to-autonomous-intersection-management-ndv1gqtnse.pdf

A multiagent approach to autonomous intersection management

Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing

Congestion continues to grow in America's urban areas. Despite a slow growth in jobs and travel in 2003, congestion caused 3.7 billion hours of travel delay and 2.3 billion gallons of wasted fuel, an increase of 79 million hours and 69 million gallons from 2002 to a total cost of more than $63 billion. The solutions to this problem will require commitment by the public and by national, state and local officials to increase investment levels and identify projects, programs and policies that can achieve mobility goals. The 2005 Urban Mobility Report shows that the current pace of transportation improvement, however, is not sufficient to keep pace with even a slow growth in travel demands in most major urban areas.

/pdf/the-2005-urban-mobility-report-3go2pe5eys.pdf

The 2005 Urban Mobility Report

Findings in the 2015 Urban Mobility Scorecard are drawn from traffic speed data collected by INRIX on 1.3 million miles of urban streets and highways, along with highway performance data from the Federal Highway Administration. This edition provides a comprehensive analysis of traffic conditions in 471 urban areas across the United States. Travel delays due to traffic congestion caused drivers to waste more than 3 billion gallons of fuel and kept travelers stuck in their cars for nearly 7 billion extra hours – 42 hours per rush-hour commuter. The total nationwide price tag: $160 billion, or $960 per commuter. Washington, D.C. tops the list of gridlock-plagued cities, with 82 hours of delay per commuter, followed by Los Angeles (80 hours), San Francisco (78 hours), New York (74 hours), and San Jose (67 hours). Drivers on America’s Top 10 worst roads waste on average 84 hours or 3.5 days a year on average in gridlock – twice the national average. Of these roads, six are in Los Angeles, two are in New York and the remaining two are in Chicago. The report predicts urban roadway congestion will continue to get worse without more assertive approaches on the project, program, and policy fronts.

2015 Urban Mobility Scorecard

Congestion is still a problem in America's 439 urban areas. The economic recession and slow recovery of the last three years, however, have slowed the seemingly inexorable decline in mobility. Readers and policy makers might be tempted to view this as a change in trend, a new beginning or a sign that congestion has been "solved." However, the data do not support that conclusion. First, the problem is very large. In 2009, congestion caused urban Americans to travel 4.8 billion hours more and to purchase an extra 3.9 billion gallons of fuel for a congestion cost of $115 billion. Second, 2008 appears to be the best year for congestion in recent times; congestion worsened in 2009. Third, there is only a short-term cause for celebration. Prior to the economy slowing, just 3 years ago, congestion levels were much higher than a decade ago; these conditions will return with a strengthening economy. There are many ways to address congestion problems; the data show that these are not being pursued aggressively enough. The most effective strategy is one where agency actions are complemented by efforts of businesses, manufacturers, commuters and travelers. There is no rigid prescription for the "best way" - each region must identify the projects, programs and policies that achieve goals, solve problems and capitalize on opportunities.

2010 Urban Mobility Report

The 18 years of data presented in this report document the growth of congestion levels on the major roads systems of 68 U.S. urban areas. Major transportation system improvements require time for planning, design and implementation, and often a significant amount of funding as well. Communicating the condition and the need for improvements is a goal of this report. Some of the broad conclusions drawn from this research include the following. 1. Congestion is growing in areas of every size. The 68 urban areas in this report range from New York City down to those with 100,000 population. 2. Congestion costs can be expressed in a log of different factors, but they are all increasing. The total congestion "bill" for the 68 areas in 1999 came to $78 billion, which was the value of 4.5 billion hours of delay and 6.8 billion gallons of excess fuel consumed. 3. Road expansions slow the growth in congestion. In areas where the rate of roadway additions were approximately equal to travel growth, travel time grew at about one-fourth to one-third as fast as areas where traffic volume grew much faster than roads were added. 4. By themselves, however, additional roadways do not seem to be the answer. The need for new roads exceeds the funding capacity and the ability to gain environmental and public approval. 5. The "solution" is really a diverse set of options that require funding commitments, as well as a variety of changes in the ways that transportation systems are used. These options and changes include more roads and more transit, more efficient operations, and modifications to the way in which travelers use the transportation network to accommodate more demand. 6. Improving the reliability of the transportation system is an important aspect of the programs in most large cities.

2001 Urban Mobility Report

Reliability and variability in transportation are being discussed for a variety of reasons. The two terms are related, but different in their focus, how they are measured, how they are communicated and, in some respects, how they might frame the discussion about potential solutions. Reliability is commonly used in reference to the level of consistency in transportation service for a mode, trip, route or corridor for a time period. Typically, reliability is viewed by travelers in relation to their experience. Variability might be thought of as the amount of inconsistency in operating conditions. This definition takes more of a facility perspective and, therefore, relates to the concerns of transportation agencies. Both of these concepts are useful, but the term reliability may have a more "marketable" connotation for the purposes of reporting performance measures to the public because it relates to an "outcome" of transportation--the quality of the service provided. Variability seems to be more related to the change in transportation system operations. The traveling public and a variety of companies or product sectors use the term "reliability" in their goal statements and it would seem this is the term that should be used with a performance measure. This report discusses the background for developing reliability measures as a component of mobility performance metrics, the factors to consider before selecting a measure and defines the calculation procedures for typical reliability analyses. This might involve a change in thinking about how mobility service is conceptualized and communicated. The terms "recurring" and "non-recurring" congestion are misnomers--variations in weather, traffic volume and a range of other factors can be termed "recurring" but have traditionally been included outside the "regular" congestion label.

/pdf/selecting-travel-reliability-measures-1sciijnek2.pdf

Timothy J Lomax

Papers

The 2005 Urban Mobility Report

2015 Urban Mobility Scorecard

2010 Urban Mobility Report

2001 Urban Mobility Report

Selecting travel reliability measures