Unsettled Issues On Hd Mapping Technology For Autonomous Driving And Adas
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| Author | : Felix Leach |
| Publisher | : |
| Total Pages | : |
| Release | : 2021 |
| Genre | : Automated vehicles |
| ISBN | : 9781468604405 |
Current advanced driver-assistance systems (ADAS) and automated driving systems (ADS) rely on high-definition (HD) maps to enable a range of features and functions. These maps can be viewed as an additional sensor from an ADAS or ADS perspective as they impact overall system confidence, reduce system computational resource needs, help improve comfort and convenience, and ultimately contribute to system safety. However, HD mapping technology presents multiple challenges to the automotive industry. Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS identifies the current unsettled issues that need to be addressed to reach the full potential of HD maps for ADAS and ADS technology and suggests some possible solutions for initial map creation, map change detection and updates, and map safety levels.
| Author | : Thomas Bock |
| Publisher | : SAE International |
| Total Pages | : 24 |
| Release | : 2021-06-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1468604406 |
Current advanced driver-assistance systems (ADAS) and automated driving systems (ADS) rely on high-definition (HD) maps to enable a range of features and functions. These maps can be viewed as an additional sensor from an ADAS or ADS perspective as they impact overall system confidence, reduce system computational resource needs, help improve comfort and convenience, and ultimately contribute to system safety. However, HD mapping technology presents multiple challenges to the automotive industry. Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS identifies the current unsettled issues that need to be addressed to reach the full potential of HD maps for ADAS and ADS technology and suggests some possible solutions for initial map creation, map change detection and updates, and map safety levels. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2021013
| Author | : Seth Chalmers |
| Publisher | : SAE International |
| Total Pages | : 48 |
| Release | : 2023-07-18 |
| Genre | : Technology & Engineering |
| ISBN | : 1468606271 |
Thousands die or are injured each year in automobile crashes. Reducing the number of these tragedies requires reframing our approach to vehicle- and human-based transportation mobility and depends on whether the mobility industry and individual human drivers take a more aggressive approach to saving lives and preventing injuries. Bringing automated driving systems technologies into the advanced driver assist systems (ADAS) and connected vehicle space will help humans drive more safely and better prepare us for automated vehicles (AVs). Reducing Human Driver Error and Setting Realistic Expectations with Advanced Driver Assistance Systems discusses the recent Partnership for Analytics Research in Traffic Safety report which shows that ADAS can indeed work. The path forward requires combining ADAS and ADS implementation with infrastructure engineering, law enforcement, education, emergency response, and public policy, with the goal of reaching zero deaths and serious injuries. It also requires fully embracing the US Department of Transportation Federal Highway Administration’s Safe System approach, backed by the addition of public policies that incorporate and expand ADAS’s role in achieving that safe system. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2023016
| Author | : Jeffrey Nickerson |
| Publisher | : SAE International |
| Total Pages | : 18 |
| Release | : 2022-04-27 |
| Genre | : Technology & Engineering |
| ISBN | : 1468604597 |
Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2022009
| Author | : Serge Lambermont |
| Publisher | : SAE International |
| Total Pages | : 30 |
| Release | : 2021-12-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1468604201 |
Information and communication technology is fundamentally changing the way we live and operate in cities, such as instant access to events, transportation, bookings, payments, and other services. At the same time, three “megatrends” in the automotive industry—self-driving, electrification, and advanced manufacturing technology—are enabling the design of innovative, application-specific vehicles that capitalize on city connectivity. Applications could countless; however, they also need to be safe and securely integrated into a city’s physical and digital infrastructure, and into the overall urban ecosystem. Unsettled Issues Concerning Automated Driving Services in the Smart City Infrastructure examines the current state of the industry, the developments in automated driving and robotics, and how these new urban, self-driving city applications are different. It also analyzes higher level challenges for urban applications. Ultimately, this report includes several options for sharing lessons learned among different cities and their stakeholders. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2021030
| Author | : Sven Beiker |
| Publisher | : SAE International |
| Total Pages | : 20 |
| Release | : 2019-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1468601172 |
This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the challenges of achieving optimal model fidelity for developing, validating, and verifying vehicles capable of automated driving. Three main issues are outlined that merit immediate interest: First, assuring that simulation models represent their real-world counterparts, how to quantify simulation model fidelity, and how to assess system risk. Second, developing a universal simulation model interface and language for verifying, simulating, and calibrating automated driving sensors. Third, characterizing and determining the different requirements for sensor, vehicle, environment, and human driver models. SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report need to be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed; second, prioritizing the issues requiring resolution; and, third, creating a plan to generate the necessary frameworks, practices, and protocols. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019007
| Author | : Tsung-Ming Hsu |
| Publisher | : SAE International |
| Total Pages | : 26 |
| Release | : 2024-08-26 |
| Genre | : Technology & Engineering |
| ISBN | : 1468608479 |
The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication and coordination technology to maintain stability and reliability in high-traffic scenarios. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2024019
| Author | : James M. Anderson |
| Publisher | : Rand Corporation |
| Total Pages | : 215 |
| Release | : 2014-01-10 |
| Genre | : Transportation |
| ISBN | : 0833084372 |
The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
| Author | : Rahul Razdan |
| Publisher | : SAE International |
| Total Pages | : 33 |
| Release | : 2019-06-12 |
| Genre | : Technology & Engineering |
| ISBN | : 1468600982 |
Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more. Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized. This paper explores the ADS validation challenge by reviewing existing approaches and examining the effectiveness of those approaches, presenting critical techniques required to bring safe and effective solutions to market, discussing unsettled topics, and suggesting next steps for industry stakeholders to consider as they work to advance the ADS ecosystem. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019001
| Author | : Mohsen Khalkhali |
| Publisher | : SAE International |
| Total Pages | : 22 |
| Release | : 2020-06-03 |
| Genre | : Technology & Engineering |
| ISBN | : 1468601679 |
Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes discusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future “self-driving” vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers. Yet, data-sharing can be developed – as a technology, culture, and business – and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS – resulting in lower research and development costs to the industry. Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance – and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2020007
