Robust localization for autonomous vehicles in dense urban areas

2021 ◽  
Author(s):  
Kerman Viana ◽  
Asier Zubizarreta ◽  
Mikel Diez
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Robust Localization

scholarly journals Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature

2021 ◽  
Vol 13 (8) ◽  
pp. 4448
Author(s):  
Alberto Dianin ◽  
Elisa Ravazzoli ◽  
Georg Hauger
Keyword(s):  
Conceptual Model ◽  
Transport System ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Scientific Literature ◽  
Social Groups ◽  
Future Studies ◽  
Social Accessibility ◽  
The Relationship

Increasing accessibility and balancing its distribution across space and social groups are two fundamental goals to make transport more sustainable and equitable. In the next decades, autonomous vehicles (AVs) could significantly transform the transport system, influencing accessibility and transport equity. In particular, depending on the assumed features of AVs (e.g., private or collective) and the considered spatial, social, and regulative context (e.g., rural or urban areas), impacts may be very different. Nevertheless, research in this field is still limited, and the relationship between AV assumptions and accessibility impacts is still partially unclear. This paper aims to provide a framework of the key and emerging aspects related to the implications of AVs for accessibility and transport equity. To set this framework, we perform an analysis of the scientific literature based on a conceptual model describing the implications of AVs for the distribution of accessibility across space and social groups. We recognize four main expected impacts of AVs on accessibility: (1) accessibility polarization, (2) accessibility sprawl, (3) exacerbation of social accessibility inequities, and (4) alleviation of social accessibility inequities. These impacts are described and analyzed in relation to the main AV assumptions expected to trigger them through different mechanisms. Based on the results, some recommendations for future studies intending to focus on the relation between AVs, accessibility, and transport equity are provided.

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

scholarly journals How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

2020 ◽  
Vol 10 (18) ◽  
pp. 6306 ◽  
Author(s):  
Luke Butler ◽  
Tan Yigitcanlar ◽  
Alexander Paz
Keyword(s):  
Conceptual Framework ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Technological Innovations ◽  
Potential Solution ◽  
Wide Range ◽  
Smart Mobility

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

scholarly journals Factors That Influence Older Canadians’ Preferences for using Autonomous Vehicle Technology: A Structural Equation Analysis

2019 ◽  
Vol 2673 (1) ◽  
pp. 469-480 ◽  
Author(s):  
Hany M. Hassan ◽  
Mark R. Ferguson ◽  
Saiedeh Razavi ◽  
Brenda Vrkljan
Keyword(s):  
Quality Of Life ◽  
Older Adults ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Structural Equation ◽  
Well Being ◽  
Transportation Systems ◽  
Equation Modeling ◽  
Willingness To Use

Accessible and safe mobility is critical for those aged 65 years and older to maintain their health, quality of life, and well-being. Being able to move beyond one’s home and participate in activities in older adulthood requires consideration of both transportation needs and preferences. This paper aims to address a gap in evidence with respect to understanding factors that can affect older adults’ perceptions and willingness to use autonomous vehicles. In addition, it examines how these factors compare with those of younger adults to better understand the potential implications of this technology on mobility and quality of life. Using responses of those aged 65+ to a national survey of Canadians, structural equation modeling (SEM) was used to identify and quantify factors significantly associated with older adults’ willingness to use autonomous vehicles. The SEM results suggest that factors such as using other modes of transit (e.g., sharing rides as passenger, bicycle, public transit, commuter rail, ride and car sharing) as well as distance traveled by automobile, income, gender (being male), and living in urban areas, were all positively associated with older adults’ perceptions of using autonomous driving features. The findings also suggest that older Canadians are more concerned about autonomous vehicles than younger Canadians. This study provides valuable insights into factors that can affect the preferences of Canadians when it comes to autonomous technology in their automobiles. Such results can inform the way in which transportation systems are designed to ensure the needs of users are considered across both age and ability.

scholarly journals A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

2019 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Umair Hasan ◽  
Andrew Whyte ◽  
Hamad Al Jassmi
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Critical Evaluation ◽  
Value Added ◽  
Pollutant Emissions ◽  
Transport Systems ◽  
Privacy And Security ◽  
Pilot Studies ◽  
Empirical Modelling

Mobility is experiencing a revolution, as advanced communications, computers with big data capacities, efficient networks of sensors, and signals, are developing value-added applications such as intelligent spaces and autonomous vehicles. Another new technology that is both promising and might even be pervasive for faster, safer and more environmentally-friendly public transport (PT) is the development of autonomous vehicles (AVs). This study aims to understand the state of the current research on the artificially intelligent transportation system (ITS) and AVs through a critical evaluation of peer-reviewed literature. This study’s findings revealed that the majority of existing research (around 82% of studies) focused on AVs. Results show that AVs can potentially reduce more than 80% of pollutant emissions per mile if powered by alternate energy resources (e.g., natural gas, biofuel, electricity, hydrogen cells, etc.). Not only can private vehicle ownership be cut down by bringing in ridesharing but the average vehicle miles travelled (VMT) should also be reduced through improved PT. The main benefits of AV adoption were reported in the literature to be travel time, traffic congestion, cost and environmental factors. Findings revealed barriers such as technological uncertainties, lack of regulation, unawareness among stakeholders and privacy and security concerns, along with the fact that lack of simulation and empirical modelling data from pilot studies limit the application. AV–PT was also found to be the most sustainable strategy in dense urban areas to shift the heavy trip load from private vehicles.

scholarly journals Road Trauma in Regional and Remote Australia and New Zealand in Preparedness for ADAS Technologies and Autonomous Vehicles

2020 ◽  
Vol 12 (11) ◽  
pp. 4347 ◽  
Author(s):  
Sujanie Peiris ◽  
Janneke Berecki-Gisolf ◽  
Bernard Chen ◽  
Brian Fildes
Keyword(s):  
New Zealand ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Tracking System ◽  
National Level ◽  
Vehicle Ownership ◽  
Remote Areas ◽  
Global Challenge ◽  
Geographical Variations ◽  
Vehicle Technologies

Achieving remote and rural road safety is a global challenge, exacerbated in Australia and New Zealand by expansive geographical variations and inconsistent population density. Consequently, there exists a rural-urban differential in road crash involvement in Australasia. New vehicle technologies are expected to minimise road trauma globally by performing optimally on high quality roads with predictable infrastructure. Anecdotally, however, Australasia’s regional and remote areas do not fit this profile. The aim of this study was to determine if new vehicle technologies are likely to reduce road trauma, particularly in regional and remote Australia and New Zealand. An extensive review was performed using publicly available data. Road trauma in regional and remote Australasia was found to be double that of urban regions, despite the population being approximately one third of that in urban areas. Fatalities in 100 km/h + speed zones were overrepresented, suggestive of poor speed limit settings. Despite new vehicle ownership in regional and remote Australasia being comparable to major cities, road infrastructure supportive of new vehicle technologies appear lacking, with only 1.3–42% of all Australian roads, and 67% of all New Zealand roads being fully sealed. With road quality in regional and remote areas being poorly mapped, the benefits of Advanced Driver-Assistance Systems (ADAS) technologies cannot be realised despite the fact new vehicles with these technologies are penetrating the fleet. Investments should be made into sealing and separating roads but more importantly, for mapping the road network to create a unified tracking system which quantifies readiness at a national level.

scholarly journals Continuum Dynamic Traffic Assignment Model for Autonomous Vehicles in a Polycentric Urban City with Environmental Consideration

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Bosheng Rong ◽  
Hui Zhao ◽  
Shaohua Cui ◽  
Cuiping Zhang
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Travel Cost ◽  
Solution Algorithm ◽  
Dynamic Traffic ◽  
Environment Impact ◽  
Urban City ◽  
Assignment Model

This paper proposed a continuum dynamic model for autonomous vehicles in a polycentric urban city by considering the environment impact of traffic emission. The model assumes that homogeneous autonomous vehicles are continuously distributed over the urban areas which tend to choose a path to minimize their total travel cost from origin to destination. To describe the path choice behavior of travelers, we presented the continuum dynamic traffic assignment model which consists of a two-dimensional hyperbolic system of nonlinear conservation laws with source terms and an Eikonal-type equation. The elastic demand is considered using a function which associating each copy of flow with its total instantaneous travel cost. For the environmental impacts, here we consider the influence of CO emission and include the cost of emission into the actual transportation cost. A solution algorithm for the model is designed as a cell-centered finite volume method for conservation law equations and a fast sweeping method for Eikonal-type equations on unstructured grids. Numerical examples are given to demonstrate the model and the proposed solution algorithm. Further, the results of the travel cost considering CO emissions and not considering CO emissions are compared.

scholarly journals Multi-Task End-to-End Self-Driving Architecture for CAV Platoons

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1039 ◽  
Author(s):  
Sebastian Huch ◽  
Aybike Ongel ◽  
Johannes Betz ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Ride Comfort ◽  
Urban Environments ◽  
Training Environment ◽  
Improve Energy Efficiency ◽  
V2v Communication ◽  
End To End ◽  
Reduce Emissions ◽  
Point To Point

Connected and autonomous vehicles (CAVs) could reduce emissions, increase road safety, and enhance ride comfort. Multiple CAVs can form a CAV platoon with a close inter-vehicle distance, which can further improve energy efficiency, save space, and reduce travel time. To date, there have been few detailed studies of self-driving algorithms for CAV platoons in urban areas. In this paper, we therefore propose a self-driving architecture combining the sensing, planning, and control for CAV platoons in an end-to-end fashion. Our multi-task model can switch between two tasks to drive either the leading or following vehicle in the platoon. The architecture is based on an end-to-end deep learning approach and predicts the control commands, i.e., steering and throttle/brake, with a single neural network. The inputs for this network are images from a front-facing camera, enhanced by information transmitted via vehicle-to-vehicle (V2V) communication. The model is trained with data captured in a simulated urban environment with dynamic traffic. We compare our approach with different concepts used in the state-of-the-art end-to-end self-driving research, such as the implementation of recurrent neural networks or transfer learning. Experiments in the simulation were conducted to test the model in different urban environments. A CAV platoon consisting of two vehicles, each controlled by an instance of the network, completed on average 67% of the predefined point-to-point routes in the training environment and 40% in a never-seen-before environment. Using V2V communication, our approach eliminates casual confusion for the following vehicle, which is a known limitation of end-to-end self-driving.

scholarly journals Encouraging the Sustainable Adoption of Autonomous Vehicles for Public Transport in Belgium: Citizen Acceptance, Business Models, and Policy Aspects

2022 ◽  
Vol 14 (2) ◽  
pp. 921
Author(s):  
Pol Camps-Aragó ◽  
Laura Temmerman ◽  
Wim Vanobberghen ◽  
Simon Delaere
Keyword(s):  
Public Transport ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Business Models ◽  
Environmental Safety ◽  
Economic Benefits ◽  
Factors Affecting ◽  
Policy Goals ◽  
Last Mile ◽  
Socio Demographic Factors

Several mobility-related issues persist in and around urban areas. Autonomous vehicles promise substantial environmental, safety, and economic benefits but may also cause unintended adverse effects that stem from single-passenger mobility becoming more affordable and accessible. While using them for public transport (i.e., autonomous shuttles) can help avoid such downsides, there are many challenges to their adoption, particularly ones that are related to citizen acceptance and economic aspects. Based on a novel survey of Brussels’ citizens, we provide insights from user opinions on last-mile autonomous shuttle services and analyze the effect of various attitudinal and socio-demographic factors affecting such acceptance. Our respondents exhibit an overall positive acceptance albeit with a limited willingness to pay for it. In addition, based on expert interviews, we provide a discussion on appropriate business models and policy recommendations to help ensure the timely adoption of AVs in Belgium that adapts to mobility needs and policy goals.

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