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0-6838, Link to appendices is included., This project develops and demonstrates a variety of smart-transport technologies, policies, and practices for, highways and freeways using connected autonomous vehicles (CAVs), smartphones, roadside equipment, and related, technologies. The intent is to maximize the benefit of these technologies in terms of improved driver safety, reduced, congestion, and agency cost savings. For example, in a well-implemented system, advanced CAV technologies may, reduce current crash costs by at least $390 billion per year. A poorly implemented system could significantly detract, from or reverse these benefits., The project’s Phase 1, documented in this report, showcased DSRC-instrumented vehicles for wrong-way driving, alerts, vehicle guidance, and road-surface condition monitoring demonstrations. It developed algorithms for more, accurate vehicle-position information and real-time traffic flow monitoring. It delivered statewide and national, forecasts of fleet evolution, consumer preferences, and Texans’ opinions of CAV policies and technologies. It also, simulated various strategies for smart ramp merges and smart intersection and network operations, under thousands of, case settings, with calculated delay reductions. It anticipated emissions savings from more thoughtful automated, driving and crash savings from more conflict-aware driving. It also analyzed the benefits of shared autonomous vehicle, transit. Recommendations are provided for guiding TxDOT as technologies increasingly become available to the, public, estimated to impact the U. S. economy by as much as $1.3 trillion per year. Recommendations focus on the, need for increasing TxDOT in-house expertise, simulating new systems, developing policy, and updating design, manuals.

0-6847, The project began by understanding the current state of practice and trends. NHTSA’s four-level taxonomy for automated vehicles was used to classify smart driving technologies and infrastructure needs. The project used surveys to analyze and gain an understanding of the U.S. general public’s perception towards such technologies and their willingness to adopt such technologies. Respondents were asked several anticipatory questions including their technology preferences (buying/selling their vehicles or simply adding new technologies to their current vehicles), and their comfort with and willingness to pay for connected and autonomous vehicles (CAVs). The team found that advanced automation technologies are not yet popular., This research report also describes the potential crash, congestion, and other impacts of CAVs in Texas, and provides initial monetary estimates of those impacts, at various levels of market penetration. Our findings indicate that CAVs will lead to increased vehicle miles traveled (VMT) because, essentially, drivers experience falling travel time burdens. Their values of travel time that make using a vehicle “costly” tend to decrease because they are more comfortable heading to more distant locations and those unable to drive themselves, such as the handicapped, can now safely travel.

DTRT12-G-UTC06, This report presents a new boundary condition estimation framework for transportation networks in which, the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a, Hamilton-Jacobi equation, we pose the problem of estimating the boundary conditions of the system on a, network, as a Mixed Integer Linear Program (MILP). We show that this framework can handle various, types of traffic flow measurements, including floating car data or flow measurements. To regularize the, solutions, we propose a compressed sensing approach in which the objective is to minimize the variations, over time (in the L1 norm sense) of the boundary flows of the network. We show that this additional, requirement can be integrated in the original MILP formulation, and can be solved efficiently for small to, medium scale problems.

Technological change (TC) is a critical process in every industry. However, old technologies and products rarely disappear from the market after TC. Incumbent firms might support old technology and revitalize or retrofit old products. Similarly users can proactively act in order to prolong the lifetime of the older technology. In so doing they may trigger a wave of technological innovation aimed at bridging the old with the new technology or with other existing complementary products. The research question of this article is therefore: how do old technology users contribute to technological change? The paper reports three illustrations of communities of practice providing critical evidences about this unexplored phenomenon. Drawing on the illustrations, some prescriptions are developed.JEL Codes: O31, O33