计量经济分析 = Econometric analysis

Technological advances are bringing connected and autonomous vehicles (CAVs) to the ever- evolving transportation system. Anticipating the public acceptance and adoption of these technologies is important. A recent internet-based survey was conducted polling 347 Austinites to understand their opinions on smart-car technologies and strategies. Ordered-probit and other model results indicate that respondents perceive fewer crashes to be the primary benefit of autonomous vehicles (AVs), with equipment failure being their top concern. Their average willingness to pay (WTP) for adding full (Level 4) automation ($7,253) appears to be much higher than that for adding partial (Level 3) automation ($3,300) to their current vehicles. This study estimates the impact of demographics, built-environment variables, and travel characteristics on Austinites’ WTP for adding such automations and connectivity to their current and coming vehicles. It also estimates adoption rates of shared autonomous vehicles (SAVs) under different pricing scenarios ($1, $2, and $3 per mile), choice dependence on friends’ and neighbors’ adoption rates, and home-location decisions after AVs and SAVs become a common mode of transport. Higher-income, technology-savvy males, living in urban areas, and those who have experienced more crashes have a greater interest in and higher WTP for the new technologies, with less dependence on others’ adoption rates. Such behavioral models are useful to simulate long-term adoption of CAV technologies under different vehicle pricing and demographic scenarios. These results can be used to develop smarter transportation systems for more efficient and sustainable travel.

Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective

In October 2016, the US National Science and Technology Council published a report on Artificial Intelligence (AI) (United States 2016) that summarised evidence from a wide variety of sources on how they expect AI to develop, what impact it would have and what actions it recommended the US Government to take. It built on several previous US Government reports, e.g. United States (2014, 2016), and consulted widely among AI experts in the USA, e.g. Horvitz and Selman (2009) and five workshops. A companion document has also been published: ‘‘The National Artificial Intelligence Research and Development Strategic Plan’’, which lays out a strategic plan for federally funded research and development in AI. Overall, this is a comprehensive report, which I recommend to anyone wanting a balanced review of the state of the AI art, its potential impact and what ethical, economic and societal issues it presents. It does, of course, duck some of the more difficult issues—or rather recommend that someone else considers them in detail. This concern about AI is, of course, triggered by the phenomenal recent successes of mainly statistical machine learning in games (Chess, Go and Jeopardy), self-driving cars, automated assistants (Apple Siri, Amazon Alexa, Google Now and Microsoft Cortana). The other main driver is the worry that Artificial General Intelligence (AGI) will exceed human intelligence and supplant us as the dominant species on the Earth—the, so-called, Singularity. The report wisely ignores concerns about the Singularity, claiming that, if it occurs at all, it’s a long way in the future, and that the immediate actions should be the same whether or not it occurs. It points out that the AI successes have been in, what it calls, narrow AI, i.e. often superhuman performance in a very narrow task, e.g. playing Go. I call such systems idiot savants. In contrast, progress in AGI has been disappointing, with no sign that this will improve in the foreseeable future. So the report focuses on the prospects for narrow AI. It claims that it has already brought ‘‘major benefits to the public in fields as diverse as health care, transportation, the environment, criminal justice and economic inclusion’’. The report then explores its potential in autonomous vehicles, governance, education, cyber-security and weapons. This exploration uncovers a number of important issues and concludes with 23 recommendations. These issues and recommendations include the following:

/pdf/preparing-for-the-future-of-artificial-intelligence-4c0v961umv.pdf

Preparing for the future of Artificial Intelligence

Connected and automated vehicles (CAVs) are poised to reshape transportation and mobility by replacing humans as the driver and service provider While the primary stated motivation for vehicle automation is to improve safety and convenience of road mobility, this transformation also provides a valuable opportunity to improve vehicle energy efficiency and reduce emissions in the transportation sector Progress in vehicle efficiency and functionality, however, does not necessarily translate to net positive environmental outcomes Here, we examine the interactions between CAV technology and the environment at four levels of increasing complexity: vehicle, transportation system, urban system, and society We find that environmental impacts come from CAV-facilitated transformations at all four levels, rather than from CAV technology directly We anticipate net positive environmental impacts at the vehicle, transportation system, and urban system levels, but expect greater vehicle utilization and shifts in tra

A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehicles

The rise of research into shared mobility systems reflects emerging challenges, such as rising traffic congestion, rising oil prices and rising environmental concern. The operations research community has turned towards more sharable and sustainable systems of transportation. Shared mobility systems can be collapsed into two main streams: Those where people share rides and those where parcel transportation and people transportation are combined. This survey sets out to review recent research in this area, including different optimization approaches, and to provide guidelines and promising directions for future research. It makes a distinction between prearranged and real-time problem settings and their methods of solution, and also gives an overview of real-case applications relevant to the research area.

https://hal.archives-ouvertes.fr/hal-02014342/document

A survey of models and algorithms for optimizing shared mobility

This report analyzes a variety of cost components caused by flight delays, including cost to airlines, cost to passengers, cost of lost demand, as well as the indirect impact of delay on the US economy. This study offers a broader consideration of relevant costs than conventional cost-of-delay estimates, and employs several innovative methodologies for assessing the magnitudes of these costs. Of particular note are the passenger delay cost estimates, which recognize that flight cancellations and missed connections can lead to substantial passenger delays not revealed in traditional flight delay statistics. The team estimates that the total cost of all US air transportation delays in 2007 was $32.9 billion including an $8.3 billion airline component, a $16.7 billion passenger component, a $3.9 billion cost from lost demand, and a $4 billion reduction in US GDP.

Total Delay Impact Study: A Comprehensive Assessment of the Costs and Impacts of Flight Delay in the United States

This paper proposes a crowdsource-enabled system for urban parcel relay and delivery. We consider cyclists and pedestrians as crowdsources who are close to customers and interested in relaying parcels with a truck carrier and undertaking jobs for the last-leg parcel delivery and the first-leg parcel pickup. The crowdsources express their interests in doing so by submitting bids to the truck carrier. The truck carrier then selects bids and coordinates crowdsources’ last-leg delivery (first-leg pickup) with its truck operations. The truck carrier's problem is formulated as a mixed integer non-linear program which simultaneously i) selects crowdsources to complete the last-leg delivery (first-leg pickup) between customers and selected points for crowdsource-truck relay; and ii) determines the relay points and truck routes and schedule. To solve the truck carrier problem, we first decompose the problem into a winner determination problem and a simultaneous pickup and delivery problem with soft time windows, and propose a Tabu Search based algorithm to iteratively solve the two subproblems. Numerical results show that this solution approach is able to yield close-to-optimum solutions with much less time than using off-the-shelf solvers. By adopting this new system, truck vehicle miles traveled (VMT) and total cost can be reduced compared to pure-truck delivery. The advantage of the system over pure-truck delivery is sensitive to factors such as penalty for servicing outside customers’ desired time windows, truck unit operating cost, time value of crowdsources, and the crowdsource mode.

Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery

Flight delay presents a widespread phenomenon in the air transportation system, costing billions of dollars every year. Some delay originating from an upstream flight spreads to downstream flights. This phenomenon is defined as delay propagation. To understand the delay propagation patterns and associated mitigation measures, this study proposes a novel analytical-econometric approach. Considering that airlines deliberately insert buffer into flight schedules and ground turnaround operations, an analytical model is developed to quantify propagated and newly formed delays that occur to each sequence of flights that an aircraft flies in a day, from three perspectives on the ways that delays are absorbed by the buffer. With delays computed from the analytical model, we further develop a joint discrete-continuous econometric model and use the Heckman's two-step procedure to reveal the effects of various influencing factors on the initiation and progression of propagated delays. Results from the econometric analysis provide estimates on how much propagated delay will be generated out of each minute of newly formed delay, for the US domestic aviation system as well as for individual major airports and airlines. The impacts of various factors on the initiation and progression of propagated delay are quantified. These results may help aviation system planners gain additional insights into flight delay propagation patterns and consequently prioritize resource allocation while improving system overall performance. Airlines can also be better informed to assign buffer to their flight schedules to mitigate delay propagation.

Modeling flight delay propagation: A new analytical-econometric approach.

This paper proposes a mechanism design based approach for public parking slot assignment in an environment empowered by recent advances in parking sensing, infrastructure-to-vehicle, and vehicle-to-infrastructure communications. An important part of the parking slot assignment deals with eliciting truthful private information from drivers while maximizing social welfare. We consider both static and dynamic mechanisms and provide theoretic proofs that, by using coupled slot allocation and payment rules, drivers will be incentivized to participate in the assignment process and truthfully report their private information. The parking manager will benefit by generating non-negative revenue from each assigned driver. Our numerical analysis provides further insights into the implementation of the dynamic mechanisms.

/pdf/a-mechanism-design-based-approach-to-solving-parking-slot-2xdk7hyawo.pdf

A mechanism design based approach to solving parking slot assignment in the information era

This paper analyzes the welfare effects of slot controls on major US airports. We consider the fundamental tradeoff between benefits from queuing delay reduction and costs due to simultaneous schedule delay increase to passengers while imposing slot limits at airports. A set of quantitative models and simulation procedures are developed to explore the possible airline scheduling responses through reallocating and trimming flights. We find that, of the 35 major US airports, a more widespread use of slot controls would improve travelers’ welfare. The results from our analyses suggest that slot caps at the four airports that currently have slot controls (Washington Reagan, Newark, New York LaGuardia, New York John F. Kennedy) are set too high. Further slot reduction by removing some of the flights at these airports could generate additional benefits to passengers. Slot controls can potentially reduce two thirds of the total system delays caused by congestion. A number of implementation and design issues related to the use of slot controls are also discussed in the paper.

Bo Zou

Papers

Total Delay Impact Study: A Comprehensive Assessment of the Costs and Impacts of Flight Delay in the United States

Design and modeling of a crowdsource-enabled system for urban parcel relay and delivery

Modeling flight delay propagation: A new analytical-econometric approach.

A mechanism design based approach to solving parking slot assignment in the information era

Do more US airports need slot controls? A welfare based approach to determine slot levels