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

APPENDIX A : PAVEMENT QUALITY (Zhanmin Zhang, Michael R. Murphy, Robert Harrison), 7 pages -- APPENDIX B : BRIDGE QUALITY (Jose Weissmann, Angela J. Weissmann), 6 pages -- APPENDIX C : URBAN TRAFFIC CONGESTION (Tim Lomax, David Schrank), 32 pages -- APPENDIX D: RURAL CORRIDORS (Tim Lomax, David Schrank), 6 pages -- APPENDIX E: ADDITIONAL REVENUE SOURCE OPTIONS FOR PAVEMENT AND BRIDGE MAINTENANCE (Mike Murphy, Seokho Chi, Randy Machemehl, Khali Persad, Robert Harrison, Zhanmin Zhang), 81 pages -- APPENDIX F: FUNDING TRANSPORTATION IMPROVEMENTS (David Ellis, Brianne Glover, Nick Norboge, Wally Crittenden), 19 pages -- APPENDIX G: ESTIMATING VEHICLE OPERATING COSTS AND PAVEMENT DETERIORATION (by Robert Harrison), 4 pages

It's about time: Investing in transportation to keep Texas economically competitive - Appendices

This year's Urban Mobility Report, the nation's longest running traffic study, out of the Texas Transportation Institute, suggests that the threats posed by congestion are threefold: the time penalty has risen for those who travel in rush hour; the times of day when travelers are likely to encounter traffic are more frequent; and the share of streets and freeways that are congested is higher. Making roadways perform more reliably is a large component in easing overall congestion, researchers say. That allows road users to keep their travel "costs" in terms of time predictable, which is why traffic management systems such as ramp meters and carpool lanes have value. A new measure in the study gives a clearer picture of delays that travelers experience when demand is highest.

Annual study shows traffic jams as a growing triple threat

This annual report includes 20 years (1982-2001) of data on mobility and traffic congestion for 75 urban areas in the United States. Statistics from generally available data sources are used to provide information about mobility trends at the urban area level of detail. In addition to presenting statistics, the report reviews what happened to those areas during the 20 years studied: traffic congestion grew in areas of every size, roads and public transportation systems handled more trips, and traffic congestion costs increased. The study includes an estimate of the effects of several common solutions to congestion problems, including additional road lanes and demand management and demand reduction programs. Freeway entrance ramp metering, freeway incident management, traffic signal coordination, public transportation service and high-occupancy vehicle lanes are also addressed.

2003 urban mobility report

This current report, It’s About Time: Investing in Transportation to Keep Texas
Economically Competitive, updates the February 2009 report by providing
an enhanced analysis of the current state of the Texas transportation system,
determining the household costs of under-investing in the system and identifying
potential revenue options for funding the system. However, the general conclusion
has not changed. There are tremendous needs and high costs associated with “doing
nothing new.”

It's about time : investing in transportation to keep Texas economically competitive

The Dallas Freeway/High-Occupancy Vehicle (HOV) System Planning Study is a joint project in cooperation with the Texas Department of Transportation (TxDOT), Dallas Area Rapid Transit (DART), the North Central Texas Council of Governments (NCTCOG), and the Texas Transportation Institute (TTI). The mission of the study is to provide an intermediate planning step between the macroscopic-level planning performed by TxDOT's Regional Planning Office and the NCTCOG and the detailed corridor design analyses performed by the district office of TxDOT. The intent of this effort is to assist in the development of an area-wide freeway/HOV system that recognizes implementation constraints (right-of-way and construction costs), and provides reasonable peak-hour operating conditions on all freeway facilities, while incorporating the long-range plans developed by TxDOT, DART, and NCTCOG. The proposed system is a set of recommendations to be considered and evaluated as part of the development of the Mobility 2010 Plan Update, the long-range transportation plan for the Dallas area. The recommended system in the Dallas System Planning Study was developed using a methodology that focuses on peak-hour passenger travel demand in the year 2015 (derived from the year 2010 24-hour volume assignment provided by NCTCOG) for the freeways in Dallas and surrounding counties. The goal of the Dallas System Planning Study has been to find the lowest public cost alternative in each corridor, for a given volume of peak-hour person trips. This framework views travel delay, construction, and operation of roadways as costs to the public. It also recognizes that some motorists will change their mode of travel when given the opportunity to avoid congestion, resulting in more transit and carpool use (rail passenger volumes were held constant as provided by NCTCOG). The Dallas System Planning Study methodology uses an iterative process to examine congestion and the consequent shift in mode so that these two factors are consistent for an alternative. The proposed system balances money saved in construction against money lost in delay to find the optimum combination of mixed-flow, HOV, and express lanes necessary to move the demand.

Timothy J Lomax

Papers

It's about time: Investing in transportation to keep Texas economically competitive - Appendices

Annual study shows traffic jams as a growing triple threat

2003 urban mobility report

It's about time : investing in transportation to keep Texas economically competitive

The Dallas freeway/HOV system planning study: year 2015