Planning and Policy Directions for Autonomous Vehicles in Metropolitan Planning Organizations (MPOs) in the United States

McAslan, Devon; Gabriele, Max; Miller, Thaddeus R.

doi:10.1080/10630732.2021.1944751

Cited by 15 publications

(8 citation statements)

References 41 publications

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“…Also, the American Association of State Highway and Transportation Officials indicated that keeping a safe driving environment for AVs through defining regulations and constructing smart infrastructure is a major issue [33]. Notably, McAslan et al [34] found that many regional planning agencies in the United States have implemented policies aimed at enhancing infrastructure maintenance to facilitate the testing and deployment of AVs. Thus, the importance of smart infrastructure in ensuring the safe and efficient operation of AVs cannot be overstated.…”

Section: Role Of Road Infrastructurementioning

confidence: 99%

“…Last but not least, policymakers and the public need more explicit information regarding scenarios in which a specific type of HADS can operate safely and regarding the infrastructure requirement associated with a given level of performance of the automated system [26,34,41]. Several companies have stated that they have developed vehicles with Level 4 automation [49,50].…”

Section: From the Ddt Perspectivementioning

confidence: 99%

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A Taxonomy for Autonomous Vehicles Considering Ambient Road Infrastructure

et al. 2023

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To standardize definitions and guide the design, regulation, and policy related to automated transportation, the Society of Automotive Engineers (SAE) has established a taxonomy consisting of six levels of vehicle automation. The SAE taxonomy defines each level based on the capabilities of the automated system. It does not fully consider the infrastructure support required for each level. This can be considered a critical gap in the practice because the existing taxonomy does not account for the fact that the operational design domain (ODD) of any system must describe the specific conditions, including infrastructure, under which the system can function. In this paper, we argue that the ambient road infrastructure plays a critical role in characterizing the capabilities of autonomous vehicles (AVs) including mapping, perception, and motion planning, and therefore, the current taxonomy needs enhancement. To throw more light and stimulate discussion on this issue, this paper reviews, analyzes, and proposes a supplement to the existing SAE levels of automation from a road infrastructure perspective, considering the infrastructure support required for automated driving at each level of automation. Specifically, we focus on Level 4 because it is expected to be the most likely level of automation that will be deployed soon. Through an analysis of driving scenarios and state-of-the-art infrastructure technologies, we propose five sub-levels for Level 4 automated driving systems: Level 4-A (Dedicated Guideway Level), Level 4-B (Expressway Level), Level 4-C (Well-Structured Road Level), Level 4-D (Limited-Structured road Level), and Level 4-E (Disorganized Area Level). These sublevels reflect a progression from highly structured environments with robust infrastructure support to less structured environments with limited or no infrastructure support. The proposed supplement to the SAE taxonomy is expected to benefit both potential AV consumers and manufacturers through defining clear expectations of AV performance in different environments and infrastructure settings. In addition, transportation agencies may gain insights from this research towards their planning regarding future infrastructure improvements needed to support the emerging era of driving automation.

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Section: Role Of Road Infrastructurementioning

confidence: 99%

Section: From the Ddt Perspectivementioning

confidence: 99%

A Taxonomy for Autonomous Vehicles Considering Ambient Road Infrastructure

et al. 2023

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“…Acknowledging the situation mentioned above, companies and governments are conducting pilots and studies to understand better the implementation, advantages, disadvantages and challenges (Ahangar et al, 2021;Feys et al, 2020;Gavanas, 2019;McAslan et al, 2021;Pattinson & Chen, 2020;Pereira et al, 2019). Some of these studies have focused on the intention of potential users to adopt the service (Ahmed et al, 2022;Alsalman et al, 2021;Feys et al, 2021;Hulse et al, 2018), as well as on the perceptions of vulnerable road users such as pedestrian and cyclist (Penmetsa et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Identification of older adults' needs as future users of autonomous shuttles: A serious game co-creation approach for inclusiveness

Flores¹,

Vanongeval²,

Steenberghen³

2023

ToTS

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Automated vehicles are potential disrupters of the mobility system and are expected to address inclusive mobility issues. Yet, the transition to their full implementation in cities is expected to face numerous challenges. While companies and governments interested in their future implementation have conducted pilots to understand better their implementation in cities, there is still a limited understanding of potential users' needs. This understanding becomes even more limited when considering vulnerable groups. To address this gap, we have developed a novel Serious Game named "A shuttle for everyone". We use it as a co-creation method to engage potential users, in this case, older adults in the Noordrand-Brussels region, Belgium. This study case contributes to the co-creation and transport literature as there is scarce research focused on developing new inclusive mobility public services. Three game sessions with older adults took place. The key identified needs are related to comfort, safety, ease of use, and accessibility. Our results confirm and complete previous automated vehicle studies. We can confirm that our Serious Game as a co-creation method has facilitated anticipatory needs identification. Understanding users' needs contribute to improving design and can help to create policy recommendations that aim for an inclusive implementation of automated vehicle mobility services.

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“…In the face of uncertainty about the impacts and growing skepticism about deployment timelines, many cities find it easier to not plan at this early stage. Others have recognized the need to plan and have begun to develop policies to help prepare for AVs, particularly regional planning agencies (McAslan et al, 2021). Some cities have created their own regulation and rules for testing, while others have adopted broader policy initiatives for emerging technologies (e.g., SDOT, 2017;City of Portland, 2018;City of Pittsburgh, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Analyzing regional policy and planning approaches, McAslan et al (2021) find that MPOs have begun to develop policies within their regional transportation plans for AVs. These include policies for infrastructure investment and maintenance, ensuring roadway safety for all users, data-sharing, encouraging multimodal transportation and public transit use, land use and parking, equity, and developing partnerships and collaborations as a key planning approach.…”

Section: Introductionmentioning

confidence: 99%

Pilot project purgatory? Assessing automated vehicle pilot projects in U.S. cities

McAslan

Arevalo

King

et al. 2021

Humanit Soc Sci Commun

Self Cite

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Pilot projects have emerged in cities globally as a way to experiment with the utilization of a suite of smart mobility and emerging transportation technologies. Automated vehicles (AVs) have become central tools for such projects as city governments and industry explore the use and impact of this emerging technology. This paper presents a large-scale assessment of AV pilot projects in U.S. cities to understand how pilot projects are being used to examine the risks and benefits of AVs, how cities integrate these potentially transformative technologies into conventional policy and planning, and how and what they are learning about this technology and its future opportunities and risks. Through interviews with planning practitioners and document analysis, we demonstrate that the approaches cities take for AVs differ significantly, and often lack coherent policy goals. Key findings from this research include: (1) a disconnect between the goals of the pilot projects and a city’s transportation goals; (2) cities generally lack a long-term vision for how AVs fit into future mobility systems and how they might help address transportation goals; (3) an overemphasis of non-transportation benefits of AV pilots projects; (4) AV pilot projects exhibit a lack of policy learning and iteration; and (5) cities are not leveraging pilot projects for public benefits. Overall, urban and transportation planners and decision makers show a clear interest to discover how AVs can be used to address transportation challenges in their communities, but our research shows that while AV pilot projects purport to do this, while having numerous outcomes, they have limited value for informing transportation policy and planning questions around AVs. We also find that AV pilot projects, as presently structured, may constrain planners’ ability to re-think transportation systems within the context of rapid technological change.

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Planning and Policy Directions for Autonomous Vehicles in Metropolitan Planning Organizations (MPOs) in the United States

Cited by 15 publications

References 41 publications

A Taxonomy for Autonomous Vehicles Considering Ambient Road Infrastructure

A Taxonomy for Autonomous Vehicles Considering Ambient Road Infrastructure

Identification of older adults' needs as future users of autonomous shuttles: A serious game co-creation approach for inclusiveness

Pilot project purgatory? Assessing automated vehicle pilot projects in U.S. cities

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