Implications of automated vehicles for physical road environment: A comprehensive review

Tengilimoglu, Oguz; Carsten, Oliver; Wadud, Zia

doi:10.1016/j.tre.2022.102989

Cited by 58 publications

(16 citation statements)

References 90 publications

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“…multiple‐choice and scaling) and open‐ended questions. The questionnaire was developed based on an extensive literature review [38]. The methodology adopted in this study is briefly illustrated in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

Infrastructure‐related challenges in implementing connected and automated vehicles on urban roads: Insights from experts and stakeholders

Tengilimoglu

Carsten

Wadud

2023

IET Intelligent Trans Sys

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The introduction of connected and automated vehicles (CAVs) has the potential to bring numerous advantages to urban mobility. However, many challenges for road infrastructure need to be overcome before those benefits can be achieved. This study addressed multiple dimensions of the implications of CAV deployment for road infrastructure through a comprehensive survey with 168 experts from different sectors and regions around the world. The issues are grouped into five categories: (1) key challenges of accommodating CAVs in existing urban transport networks; (2) infrastructure improvement required for shared CAV models; (3) maintenance aspects of infrastructure for CAVs; (4) implementation time of infrastructure support for CAVs; and (5) financing infrastructure upgrades to facilitate CAVs on the roads. The outcomes of the research show that there is still no consensus among the stakeholders on what should be considered to maximise CAV benefits for society as a whole. This indicates the necessity for cooperation between stakeholders to achieve the safe and efficient operation of CAVs. Overall, this study provides in‐depth insights for decision‐makers and transport planners to form policies, regulations, and guidelines regarding the future implementation of CAVs for roads before their commercialisation phase.

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Section: Methodsmentioning

confidence: 99%

Infrastructure‐related challenges in implementing connected and automated vehicles on urban roads: Insights from experts and stakeholders

Tengilimoglu

Carsten

Wadud

2023

IET Intelligent Trans Sys

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“…U današnje vrijeme autonomna vozila privlače puno pozornosti u znanosti i industriji diljem svijeta, a njihov sve brži razvoj najavljuje i značajnu potrebu za prilagodbom prometne infrastrukture [1]. Brojne europske zemlje financiraju istraživačke projekte te postavljaju ciljeve i strateške planove za autonomnu mobilnost [2], dok znanstvena istraživanja sugeriraju uspostavljanje standarada i smjernica za projektiranje, odnosno prilagodbu cestovne infrastrukture novim prometnim trendovima [3].…”

Section: Uvodunclassified

Designing highways for the traffic of autonomous vehicles

Čudina Ivančev,

Dragičević,

Džambas

2023

Zajednički Temelji 2023. - uniSTem : Deseti Skup Mladih Istraživača Iz Područja Građevinarstva I Srodnih Tehničkih Znanosti, Sp

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In the last few years, there has been an increasing amount of research dealing with the development of autonomous vehicles. The ability of autonomous vehicles to drive themselves, predict situations, communicate with surrounding vehicles and infrastructure, and interact with the environment in which they are located sets new requirements for designing road infrastructure. Gradual adaptation of the road infrastructure will largely depend on the level of development of autonomous vehicles and their share in the traffic flow. This paper presents the results of existing research related to the geometric design of highways adapted to the traffic of autonomous vehicles and provides guidelines for the implementation of further research. The main purpose of the research will be a detailed analysis of all project elements during the construction of new or reconstruction of existing highways, depending on the share of autonomous vehicles in traffic flow.

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“…The current SAE taxonomy, although widely adopted and recognized as the industry standard, does have certain limitations. One such limitation is that the taxonomy primarily focuses on the technical aspects of vehicle automation, such as the level of driver involvement and the extent of automation, without considering the variability in driving conditions and environments across different regions, which can have a significant impact on the performance and reliability of automated systems [21][22][23][24][25][26].…”

Section: Existing Sae Taxonomymentioning

confidence: 99%

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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Implications of automated vehicles for physical road environment: A comprehensive review

Cited by 58 publications

References 90 publications

Infrastructure‐related challenges in implementing connected and automated vehicles on urban roads: Insights from experts and stakeholders

Infrastructure‐related challenges in implementing connected and automated vehicles on urban roads: Insights from experts and stakeholders

Designing highways for the traffic of autonomous vehicles

A Taxonomy for Autonomous Vehicles Considering Ambient Road Infrastructure

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