Towards Automated Bicycles: Achieving Self-Balance Using Steering Control

2018 ◽  
Author(s):  
Wenhao Deng ◽  
Skyler Moore ◽  
Jonathan Bush ◽  
Miles Mabey ◽  
Wenlong Zhang
Keyword(s):  
Autonomous Vehicles ◽  
Controller Design ◽  
Smart Cities ◽  
Autonomous Driving ◽  
Human Robot Interaction ◽  
Steering Control ◽  
Control Moment Gyroscope ◽  
Control Moment ◽  
Potential Applications ◽  
Electric Bicycle

In recent years, researchers from both academia and industry have worked on connected and automated vehicles and they have made great progress toward bringing them into reality. Compared to automated cars, bicycles are more affordable to daily commuters, as well as more environmentally friendly. When comparing the risk posed by autonomous vehicles to pedestrians and motorists, automated bicycles are much safer than autonomous cars, which also allows potential applications in smart cities, rehabilitation, and exercise. The biggest challenge in automating bicycles is the inherent problem of staying balanced. This paper presents a modified electric bicycle to allow real-time monitoring of the roll angles and motor-assisted steering. Stable and robust steering controllers for bicycle are designed and implemented to achieve self-balance at different forward speeds. Tests at different speeds have been conducted to verify the effectiveness of hardware development and controller design. The preliminary design using a control moment gyroscope (CMG) to achieve self-balancing at lower speeds are also presented in this work. This work can serve as a solid foundation for future study of human-robot interaction and autonomous driving.

scholarly journals Simulation of AEBS Applicability by Changing Radar Detection Angle

2021 ◽  
Vol 11 (5) ◽  
pp. 2305
Author(s):  
Yongsoon Choi ◽  
Seryong Baek ◽  
Cheonho Kim ◽  
Junkyu Yoon ◽  
Seongkwan Mark Lee
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Smart Cities ◽  
Autonomous Driving ◽  
Radar Detection ◽  
Safe Driving ◽  
Euro Ncap ◽  
Test Standards ◽  
Emergency Braking ◽  
Crash Avoidance

As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

scholarly journals Project ARES: Driverless Transportation System. Challenges and Approaches in an Unstructured Road

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1753
Author(s):  
Pablo Marin-Plaza ◽  
David Yagüe ◽  
Francisco Royo ◽  
Miguel Ángel de Miguel ◽  
Francisco Miguel Moreno ◽  
...  
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Smart Cities ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Vehicle Localization ◽  
Transport Efficiency ◽  
The Road ◽  
Operational Design ◽  
Low Coverage

The expansion of electric vehicles in urban areas has paved the way toward the era of autonomous vehicles, improving the performance in smart cities and upgrading related driving problems. This field of research opens immediate applications in the tourism areas, airports or business centres by greatly improving transport efficiency and reducing repetitive human tasks. This project shows the problems derived from autonomous driving such as vehicle localization, low coverage of 4G/5G and GPS, detection of the road and navigable zones including intersections, detection of static and dynamic obstacles, longitudinal and lateral control and cybersecurity aspects. The approaches proposed in this article are sufficient to solve the operational design of the problems related to autonomous vehicle application in the special locations such as rough environment, high slopes and unstructured terrain without traffic rules.

Development of a Predictive Collision Risk Estimation Scheme for Mixed Traffic

2014 ◽  
Author(s):  
Je Hong Yoo ◽  
Reza Langari
Keyword(s):  
Autonomous Vehicles ◽  
Controller Design ◽  
Risk Estimation ◽  
Autonomous Driving ◽  
Collision Probability ◽  
Subjective Perception ◽  
Subsequent Work ◽  
Prediction Ability ◽  
Collision Model ◽  
Estimation Scheme

Driven by the emergence of autonomous/semi-autonomous driving technologies, the mixed situation of autonomous vehicles and human drivers is of considerable significance. Toward this end, it is necessary to better understand human driving characteristics so as to predict the actions of the other cars. In this regard, we develop a basic framework for modeling driver behaviors in view of human prediction ability. Through the game theoretic estimation of the counterpart’s behaviors and the corresponding time-evolution of unsafe collision areas, we compute an objective collision model. In turn, we design a human-like predictive perception model on collision with an adjacent vehicle based on the objective collision model and the driver’s subjective level of safety assurance. Since drivers have different safety requirements, the subjective estimate on the collision was designed as a region in which has less safety than the driver’s own safety requirement in the objective probabilistic collision prediction. The region that is subjectively perceived based on the driver’s own safety standard is regarded as a deterministic unsafe region for the driver. That is to say, the subjective perception acts as a collision area with the collision probability of 1 so that the driver should avoid while driving. In our subsequent work, we will address the issue of controller design to avoid the subjective collision estimation.

scholarly journals Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2143
Author(s):  
Sara Paiva ◽  
Mohd Abdul Ahad ◽  
Gautami Tripathi ◽  
Noushaba Feroz ◽  
Gabriella Casalino
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
City Planning ◽  
Smart Cities ◽  
The Sustainable Development ◽  
Current Trends ◽  
Enabling Technologies ◽  
Entry Points ◽  
Development Goals ◽  
Smart Mobility

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

Female Voice Agents in Fully Autonomous Vehicles Are Not Only More Likeable and Comfortable, But Also More Competent

2020 ◽  
Vol 64 (1) ◽  
pp. 1033-1037
Author(s):  
Jiayuan Dong ◽  
Emily Lawson ◽  
Jack Olsen ◽  
Myounghoon Jeon
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Driving ◽  
Preference Ranking ◽  
Uncanny Valley ◽  
Tracking Data ◽  
Effective Solution ◽  
User Perception ◽  
Future Studies ◽  
Underlying Mechanisms ◽  
The Voice

Driving agents can provide an effective solution to improve drivers’ trust in and to manage interactions with autonomous vehicles. Research has focused on voice-agents, while few have explored robot-agents or the comparison between the two. The present study tested two variables - voice gender and agent embodiment, using conversational scripts. Twenty participants experienced autonomous driving using the simulator for four agent conditions and filled out subjective questionnaires for their perception of each agent. Results showed that the participants perceived the voice only female agent as more likeable, more comfortable, and more competent than other conditions. Their final preference ranking also favored this agent over the others. Interestingly, eye-tracking data showed that embodied agents did not add more visual distractions than the voice only agents. The results are discussed with the traditional gender stereotype, uncanny valley, and participants’ gender. This study can contribute to the design of in-vehicle agents in the autonomous vehicles and future studies are planned to further identify the underlying mechanisms of user perception on different agents.

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

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