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A-1  Deployment Pattern Forecasting the timeline for penetration of automated driving system (ADS) technologies is significantly complicated by the rapidly emerging nature of ADS development, as well as the flood of information and hype created by individual automakers/developers, each contending with market and shareholder pressures to accelerate their timeline to market. Based on the lit- erature review, technology innovations generally follow a predictable S-curve deployment pattern, as illustrated in Figure A-1. As the figure shows, the deployment pattern follows the following phases: development, testing, approval, commercial release, product improvement, market expan- sion, differentiation, maturation, and eventually saturation and decline (Litman, 2019). ADS tech- nology will probably follow this pattern. Cost According to previous studies on ADS cost and market penetration, about 24% of consumers would be willing to pay an additional $4,000 for an ADS feature, while 17% would be willing to pay more than $5,000 for a fully automated vehicle (AV) (Mosquet et al., 2015). The surveyed consumers indicated a lack of clear preference toward a specific feature. However, the con- sumers expressed a more intense level of interest in ADSs compared to electric vehicles (EVs) prior to their deployment, providing an indication of a more rapid and prevalent ADS deployment compared to the slow EV deployment. Depending on the ADS feature, the price after launch is expected to decrease by a compound annual rate of about 4% to 10% due to original equipment manufacturers (OEMs) benefiting from the economies of scale of the ADS market. Public Acceptance Public acceptance of ADSs is an essential factor to consider in conjunction with the willing- ness to pay and could be a barrier for expanding the market of ADS features. While many studies (AAA, 2019; Hewitt et al., 2019) documented a lower intention for drivers to use ADS features, the majority of these studies confirmed that this attitude was specific toward full and higher levels of automation (Level 4/Level 5). Additionally, a recent study (Penmetsa et al., 2019) reported that as the public interacts with ADSs, their acceptance and perception toward the technology are more likely to be positive. In this study, respondents interacting directly with ADSs reported significantly higher expectations of the benefits of ADSs than those not interacting with ADSs. In fact, the study recommended that policymakers should provide opportunities for the public to have interaction experience with ADSs. A P P E N D I X A Factors Considered for Estimating ADS Market Penetration
A-2 Framework for Assessing Potential Safety Impacts of Automated Driving Systems Fleet Turnover Rates Studies have shown that consumers who are willing to pay more than $5,000 will be the primary customers for ADS features and will move the ADS market forward in the early stages of ADS features deployment (Mosquet et al., 2015). Since OEMs will later benefit from the ADS market economies of scale and based on the consumer willingness to pay survey, it is expected that the ADS market (partially and fully AV) will blossom until it reaches a penetration rate of around 29% over the next 10 to 15 years. The number of cars and light trucks expected to be on U.S. roads in 2030 and 2035 is about 290 million and 300 million vehicles (https://news. nationalgeographic.com/2017/09/electric-cars-replace-gasoline-engines-2040/), respectively, and the projected annual sales of the U.S. car market would be about 17 million vehicles. Extrapolating from these figures, this could take anywhere from 58 to 60 years during the period from 2030 to 2035 for the entire fleet to turn over to become automated. Another study anticipates that ADS technologies would normally require 3 to 5 decades to penetrate 90% of vehicle fleets (https:// www.vtpi.org/avip.pdf). Policy and Regulation The timeframe for AV deployment will depend not only on technology readiness, but on regulatory activities at various levels of government and in countless jurisdictions around the nation; the response of the insurance industry in terms of shifting liability; initial cost of the technology; and, of course, infrastructure dependencies. Some ADS features are commercially available and deployed in vehicles that are certified to operate on the road by customers (such as autopilot); policy barriers should be minimal for these ADS features. Other features, however, are not yet commercially available (such as conditional automated highway drive) or have been deployed only as a proof of concept (such as platooning). Some of these features might face policy or regulation barriers on either the federal or state levels before being made available for commercial use. It is worth noting that a major influence on the deployment rates is the pace of modernizing existing federal regulations and standards to be more flexible, responsive, and technology-neutral for accommodating the rapid pace of innovations in ADS. Specifically, major changes are needed for safety standards at the federal Figure A-1. Innovative technology deployment trend (Source: Adapted from Litman, 2019).
Factors Considered for Estimating ADS Market Penetration A-3  level to accommodate the development, testing, and sale of certain ADS features within specific Level 4 and Level 5 vehicle design. The different paces at which these regulatory challenges will be addressed would result in different deployment timelines and rates. Proportion of Shared HAVs in the Fleet According to several articles documenting automaker announcements regarding the timeline for introducing highly automated vehicles (HAVs; Levels 4 and 5) (http://www.businessinsider. com/google-apple-tesla-race-todevelop-self-driving-cars-by-2020-2016-4/; https://www.cbinsights. com/research/autonomous-driverless-vehicles-corporations-list/), the first phase of deploying these vehicles will probably occur from 2020 to 2021. During the early deployment stages of HAVs, the car manufacturers will primarily target transportation network companies (TNCs) with large fleets. Large-fleet companies will be able to afford the HAV at early deployment and will be the key players for expanding the HAV market. In an early response to these facts, auto- makers and TNCs have been forging corporate coalitions to reserve a decent share of what is expected to be a multibillion-dollar market by 2030. For instance, in 2017, Volvo announced a 3-year deal to supply up to 24,000 robo-taxis to Uber, with the vehicle shipment expected to start during 2019. On the other hand, Lyft began partnering with General Motors earlier in 2016 to develop HAVs. Lyft pursued further collaboration by making two separate pacts in 2017 with Ford and Waymo, respectively, for collaboration on HAVs. Accordingly, the market of TNCs and shared mobility is expected to grow rapidly, with the introduction of HAVs reaching $173.15 billion by 2030 with shared mobility services contrib- uting to 65.31% (Frost and Sullivan, 2018). These cascade trends and partnerships are expected to reshape the transportation sector and trigger a disruptive change to the transportation industry, probably the largest ever in transportation history. For instance, by 2030 the traditional process for buying or renting a car could be replaced by a subscription system operated by TNCs and fleet managers. These systems would offer a variety of ride-hailing plans covering the different types of subscriber trips (e.g., work, errands, recreational). Discount would be offered for sub- scribers affiliated with the TNC on long-term agreements to a level that makes the cost per mile traveled using these services much cheaper and convenient than the cost and satisfaction per mile traveling using private cars. Assuming these scenarios, parking lots are expected to shrink across the United States and gradually be replaced with electric charging stations. Proportion of Total VMT Many studies suggest that automating the dynamic driving task would make traveling more convenient and travelers would be capable of making better use of their time, which will eventually increase the vehicle miles traveled (VMT). ADS-equipped vehicles are likely to increase total VMT. Some researchers estimate that the VMT will increase between 15% and 59% (Soteropoulos et al., 2019). Also, annual mileage tends to decline as the vehicles age. For example, 2001 vehicles averaged approximately 15,000 miles their first year, 10,000 miles their 10th year, and 5,000 miles their 15th year, so vehicles older than 10 years represent about 50% of the vehicle fleet, but only about 20% of vehicle mileage (Oak Ridge National Laboratory, 2012; Litman, 2015). There- fore, from a planning perspective, it is also imperative to have an estimate for the anticipated contribution of ADS to the total VMT in addition to estimating the envisioned ADS market penetration.
