Thomas Stephens

Analysis of the Effects of Connected–Automated Vehicle Technologies on Travel Demand

Connected–automated vehicle (CAV) technologies are likely to have significant effects not only on how vehicles operate in the transportation system, but also on how individuals behave and use their vehicles. While many CAV technologies—such as connected adaptive cruise control and ecosignals—have the potential to increase network throughput and efficiency, many of these same technologies have a secondary effect of reducing driver burden, which can drive changes in travel behavior. Such changes in travel behavior—in effect, lowering the cost of driving—have the potential to increase greatly the utilization of the transportation system with concurrent negative externalities, such as congestion, energy use, and emissions, working against the positive effects on the transportation system resulting from increased capacity. To date, few studies have analyzed the potential effects on CAV technologies from a systems perspective; studies often focus on gains and losses to an individual vehicle, at a single intersection, or along a corridor. However, travel demand and traffic flow constitute a complex, adaptive, nonlinear system. Therefore, in this study, an advanced transportation systems simulation model—POLARIS—was used. POLARIS includes cosimulation of travel behavior and traffic flow to study the potential effects of several CAV technologies at the regional level. Various technology penetration levels and changes in travel time sensitivity have been analyzed to determine a potential range of effects on vehicle miles traveled from various CAV technologies.

Potential Reductions in Emissions and Petroleum Use in Transportation: Perspectives from the Transportation Energy Futures Project

The use of energy-efficient technologies and renewable energy sources in transportation could reduce petroleum use and greenhouse gas emissions, but these approaches may face challenges in consumer adoption, infrastructure requirements, and resource constraints. The Transportation Energy Futures project of the U.S. Department of Energy reviewed opportunities for significant reductions in petroleum use and greenhouse gas emissions. On the basis of that review, a diverse set of strategies is explored: reduced energy intensity of transportation modes, lower use intensity of motorized transport, and reduced carbon or petroleum intensity through the use of electricity and hydrogen from renewable energy as well as the use of biofuels. Energy efficiency and demand-side approaches could stop the growth in total transportation energy. In the light-duty vehicle sector, growth in energy use already is projected to flatten; the deployment of technologies for energy efficiency could limit growth in the non-light-duty sector. Travel reduction and built environment changes could moderate personal transportation demand. Freight mass reductions and mode switching could slow or stabilize freight demand. Vehicles using electricity or hydrogen could enable access to renewable energy resources other than biomass. Challenges in fueling infrastructure expansion and market uptake of advanced vehicles are considered. Competition for biomass also is explored, considering markets for electricity, gasoline, diesel, jet fuel, and bunker fuel. The potential for the implementation of these strategies to displace U.S. petroleum use and reduce greenhouse gas emissions in the transportation sector is discussed along with the barriers to realizing this potential in the market.

Assessing Energy Impacts of Connected and Automated Vehicles at the U.S. National Level—Preliminary Bounds and Proposed Methods

Connected and automated vehicles (CAVs) can have tremendous impacts on transportation energy use. Using published literature to establish bounds for factors impacting vehicle demand and vehicle efficiency, we find that CAVs can potentially lead to a threefold increase or decrease in light-duty vehicle energy consumption in the United States. Much of this uncertainty is due to possible changes in travel patterns (in vehicle miles traveled) or fuel efficiency (in gallons per mile), as well as future adoption levels and patterns of use. This chapter details the factors which go into these estimates, and presents a methodological approach for refining this wide range of estimated fuel consumption.

Developing a Spatial Transferability Platform to Analyze National-Level Impacts of Connected Automated Vehicles

A recent application of the spatial transferability approach is to assess the potential impacts of the emerging connected automated mobility technology on people’s travel behavior at the national level. While there are a few transportation simulation frameworks which can account for potential impacts of this technology in a simulated geographical context, there is yet to be any literature documenting disaggregated estimates of large-scale impacts of connected automated vehicles (CAVs) on travel behavior at the national level. Therefore, in order to provide a platform to assess national-level impacts of CAVs, this study develops a methodological framework based on transferability techniques, which uses data and models from a smaller geographical area—the POLARIS simulation results for the CAVs scenario in the Chicago metropolitan area—to generate disaggregate travel data at the national level. Comparison of the distributions of the transferred variables at the regional and the national contexts indicates that the platform is capable of transferring travel behavior indices to the national level with high level of accuracy.

Dynamic Household Vehicle Decision Modeling Considering Plug-In Electric Vehicles

Plug-in electric vehicles (PEVs) offer alternatives to traditional vehicles that rely on petroleum-based fuels. While PEV customers can enjoy significant reductions in fuel costs, they incur a larger capital cost than users of traditional vehicles because PEV technology is still maturing. Therefore, consumers adopting PEVs face a trade-off between fuel cost savings with environmental benefits and extra capital cost. It is thus crucial for policy makers and PEV manufacturers to understand people’s vehicle decision-making process while considering their socio-economic and travel pattern characteristics as well as the built-environment factors. This paper presents a connected, two-stage, dynamic model of PEV adoption and vehicle-transaction decision-making. Two connected nested logit (NL) models are estimated. The upper level is a two-level NL model to predict choice of vehicle type between four fuel types: gasoline, diesel, hybrid gasoline–electric, and PEV. The lower level is an NL model of vehicle-transaction choice which accommodates four transaction decisions of buy, trade, dispose, and do nothing, while accounting for the log-sum from the vehicle-type choice model, and is estimated using two waves of a panel data set. We find that households with higher levels of income and education are more likely to adopt a PEV. We also found that primarily decision makers take into account the accessibility to charging stations as a critical factor in choosing PEVs.

Truck Automation Opportunities

This paper gives a summary of a recent session dedicated to truck automation opportunities held as part of the Transportation Research Board/Association for Unmanned Vehicle Systems International (TRB/AUVSI) 2014 Automated Vehicle Symposium. Improved safety, efficiency, and productivity, with lower environmental impacts, are all potential benefits of heavy truck automation. Near-term opportunities for more advanced automation technologies in trucks are platooning and low-speed maneuvering. Advanced technologies are being developed for more automated truck operation. This chapter presents the status and trends of truck automation technologies, technical challenges, barriers to deployment, and possible pathways to automation.

Transportation Energy Futures Series. Vehicle Technology Deployment Pathways. An Examination of Timing and Investment Constraints

Analysts may develop scenarios of the deployment of new vehicle technologies for a variety of reasons, ranging from pure thought exercises for hypothesizing about the future, to careful examinations of the possible outcomes of future policies or trends in technology, to examination of the feasibility of broad goals of reducing greenhouse gases and/or oil use. To establish a scenario’s plausibility, analysts will seek to make their underlying assumptions clear and to “reality check” the story they tell about technology development and deployment in the marketplace. This report examines two aspects of “reality checking”—(1) whether the timing of the vehicle deployment envisioned by the scenarios corresponds to recognized limits to technology development and market penetration and (2) whether the investments that must be made for the scenario to unfold seem viable from the perspective of the investment community. There are some excellent examples of scenario development that have taken a considerable effort to account for timing issues—the Massachusetts Institute of Technology report On the Road in 2035 (Bandivadekar et al. 2008) is one such example. However, a review of the literature shows that many reports discussing scenario analyses do not reveal the genesis of the deployment schedule embodied by the scenarios. The literature review also reveals that the perspective of the investment community apparently was not considered or was considered by using techniques that do not take into account the role of risk in investment decisions. This result may not be surprising—conducting an investment analysis is difficult given the variety of investment actors, the uncertainty in future costs, and a scarcity of literature on the capital costs of the key building blocks of a new technology vehicle deployment. Nevertheless, a method for examining the potential attractiveness of the required capital investments to the investment community would be extremely attractive both from the perspective of improving the credibility of scenario analyses and allowing better analysis of policies designed to stimulate investment. This report develops a proposed timeline for introduction and penetration of a new vehicle technology.. The timeline indicates a period of 12 to 20+ years between the initial market introduction of a new technology and when it reaches “saturation” in the new light-duty vehicle fleet, with the lower end of the range applying primarily to technologies that do not require extensive integration into vehicle systems or substantial post-introduction cost reductions