Science topic
Autonomous Vehicles - Science topic
Explore the latest questions and answers in Autonomous Vehicles, and find Autonomous Vehicles experts.
Questions related to Autonomous Vehicles
This question seeks to determine the best practices for collecting and analyzing data to assess the effectiveness of programmable headlights, ensuring that they meet safety and efficiency standards in real-world scenarios
Is it already highly safe to drive a car in driverless mode, i.e. driven, guided by an artificial intelligence system?
More and more car companies are conducting tests and some have already started to mass-produce autonomous cars guided by artificial intelligence. Some models are being produced in dual versions, i.e. allowing the vehicle to be driven classically by the driver and with the option of enabling automatic steering by an AI computer. In the future, the scale of production equipped with this type of solution is said to increase. The key arguments for the development of this type of solution include, on the one hand, convenience and the possibility, already used in some countries, to transport goods by truck on intercity routes without a driver. On the other hand, when driverless autonomous vehicles are allowed in urban areas, there are concerns about the safety of vehicle traffic, which may be due to the malfunctioning of AI-controlled vehicle movement systems. In addition, there are also considerations regarding the qualification of liability for road traffic accidents involving autonomously driven vehicles by artificial intelligence.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Would you trust an artificial intelligence to steer your autonomous car while driving that vehicle in a driverless option?
Is it already highly safe to drive a car in driverless mode, i.e. driven, guided by an artificial intelligence system?
What is your opinion on this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz

This question aims to explore the intersection of artificial intelligence and autonomous vehicle technology. It seeks to identify the key challenges faced in implementing AI for recognition systems, such as processing and managing real-time data, and making accurate decisions in dynamic and complex driving environments. Additionally, it invites discussion on the future advancements and potential solutions that could enhance the reliability and efficiency of AI-driven recognition systems in self-driving cars. This topic is crucial for advancing the development of autonomous vehicles and ensuring their safe and effective operation.
I am currently working on a research paper focused on the control of Connected and Autonomous Vehicles (CAVs) utilizing multi-agent reinforcement learning methods. At this stage, I am seeking a reputable journal that offers a relatively swift publication process. I would greatly appreciate any recommendations you could provide.
SENET: Semantic Communication-aided Wireless Networks for Emerging Technologies
Co-located with IEEE MASS 2024
25 September, 2024
Objectives
The objective of the workshop is to familiarize participants with semantic communication and its importance in the context of wireless networking for emerging technologies. It aims to delve into how semantic technologies can be seamlessly integrated with wireless communication protocols to improve efficiency, co-existence among protocols, interoperability across devices, reliability of communication, and scalability of networks. Discussions will focus on understanding how semantics contribute to context-awareness within networks, facilitate intelligent decision-making processes, and enable adaptive resource management in dynamic wireless environments. Real-world applications and case studies showcasing the benefits of semantic communication in various domains will be explored to provide practical insights.
We invite workshop papers that align with the theme and objectives outlined above. This workshop seeks to catalyze innovation, promote collaboration, and facilitate knowledge sharing among experts, researchers, practitioners, and industry professionals across the wireless networking and semantic technologies domains.
Scope
Semantic communication-aided wireless networks represent a paradigm shift in wireless communications, enabling intelligent and context-aware interactions between heterogeneous devices, systems, and protocols. This workshop aims to explore the intersection of semantic technologies and wireless networking, focusing on their applications in emerging technologies such as AR/VR/XR, machine-type applications, V2V, V2X, edge intelligence, etc., and fostering the co-existence and interoperability among fundamentally diverse protocols including WiFi, 5G/6G, satellite networks. Through theoretical discussions, practical demonstrations, and collaborative activities, participants will gain insights into the design principles, implementation challenges, and potential opportunities of semantic communication-aided wireless networks.
Potential Topics
- Foundations of Semantic Communication:
- Ontology modeling and reasoning in wireless communication
- Semantic interoperability in wireless networks
- Semantic Techniques in Wireless Networking:
- Semantic routing and network management
- Semantic-based spectrum management and allocation
- Semantic-aware resource allocation in edge computing environments
- Co-existence and interoperability between wireless protocols
- Efficient spectrum utilization through semantic-aware networking
- Context-Awareness and Situation Awareness:
- Semantic context modeling and representation
- Context inference and reasoning in wireless networks
- Situation-awareness applications in IoT and 5G/6G networks
- Intelligent Decision-Making and Adaptation:
- Semantic-driven decision support systems
- Adaptive protocols and algorithms based on semantic information
- AI/ML techniques for semantic-enabled wireless networks
- Semantic communication for Edge Intelligence and Federated Learning
- Applications and Use Cases:
- Smart cities, urban mobility, autonomous vehicles & transportation
- AR/VR/XR
- Healthcare and assistive technologies
- Industrial IoT and Industry 4.0 applications
- Smart Agriculture
- Environmental Monitoring
- Challenges and Future Directions:
- Scalability and efficiency of semantic communication in large-scale networks
- Semantic-native next-generation wireless protocols and technologies
- Security and privacy in semantic-enabled wireless networks
- Standardization efforts and interoperability challenges
Specific Promotions
BTS Labs. (https://btslabs.ai/) will sponsor the workshop featuring a Best Paper Award (BPA) with a cash prize of 800 Euros.
Submission Guidelines:
All submissions should be original and unpublished research papers up to six (6) printed pages in length, formatted in two-column, single-spaced with 10-point font on US Letter paper.
EDAS Link: https://edas.info/N32418
Important Dates
Paper Submission Deadline: Friday, June 21, 2024 (11:59pm AoE)
Notification of Acceptance: Friday, July 26, 2024
Camera-Ready Submission: Friday, August 9, 2024
Workshop Date: Wednesday, September 25, 2024
Best regards,
safety of autonomous self-driving vehicles.
In the not-too-distant future, most cars and trucks will be electric and autonomous. They will be connected to the road and infrastructure. This means they can be controlled remotely if necessary.
One application of this type of control would be for the police to catch a thief or in the case of a hit-and-run. Do you think or know that car manufacturers have already implemented this function?
I am writing to seek your assistance in resolving an issue related to the car-to-vehicle distance in VISSIM when there are multiple lanes. I have encountered a phenomenon where autonomous vehicles (AV) deviate from the spacing when driving alongside human-driving vehicles (HDV) in the side lane.
To provide some context, I have set the car-to-vehicle distance between AV and HDV by configuring the parameters CC0 and CC1 in the Car-following tab of VISSIM. All vehicles have been assigned a speed of 100 km/h, and there is no variability in the speed distribution.
In my experiments, I have observed that when there is only one lane on a highway without a traffic signal, all vehicles maintain the set interval and drive at the same interval (Input demand is far greater than the capacity of the highway. Furthermore, when AV and HDV are mixed, the distance between cars remains consistent with the spacing. The passing traffic volume, as measured by the detector, aligns with the capacity calculated based on the theoretically set car-to-vehicle distance. Thus, the results match the expected behavior as per the theory.
However, the issue arises when there are two lanes. In this scenario, some of the AV drive with wider spacing than the set spacing, specifically when HDV drives alongside them in the side lane.
I am seeking guidance on how to address this issue. I have already configured CC0 and CC1 in the Car-following settings. Therefore, I think the Car-following settings have nothing to do with the problem. If there are any additional parameters or settings that I should consider adjusting to resolve this problem, I would greatly appreciate your advice.
Please provide me with more details and insights on how to address this issue effectively. Your expertise and guidance would be of immense help in resolving this matter.
Thank you for your attention to this inquiry. I look forward to your prompt response and assistance.

What role does AI play in developing autonomous vehicles for agricultural purposes, such as driverless tractors?
AI-based research software has been in use recently, spanning a wide range of applications across various fields, including Drug Discovery and Development, Precision Medicine, Healthcare Diagnostics and Imaging, Environmental Monitoring and Conservation, Autonomous Vehicles and Robotics, Language Processing and Translation, Financial Analysis and Trading, Cybersecurity, Manufacturing and Supply Chain Optimization, Agricultural Optimization etc. The innovation has also been applied in the fields of Education and Learning, Content Creation and Entertainment.
Recently, I came across AnswerThis to facilitate my research work. What is your opinion regarding use of this software? Available at https://answerthis.io/signup
How can artificial intelligence technology improve the process of organizational management of modern urban agglomerations developed operating according to the green smart city model?
Industry 4.0/5.0 technologies are increasingly being used to manage the organization of modern urban agglomerations developed operating according to the green smart city model. Since artificial intelligence technology has been developing particularly rapidly recently, and numerous new applications of this technology are emerging in various sectors of the economy, so also the opportunities for applying AI technologies to improve the systems of automated management of the organization of modern urban agglomerations are increasing. Besides, the combination of Big Data Analytics, Data Science, Internet of Things, multi-criteria simulation models, digital twins, cloud computing with artificial intelligence technology and other ICT technologies makes it possible to significantly increase the efficiency of operation and improvement of systems of automated management of the organization of modern urban agglomerations.
Smart home technologies and smart city technologies are developing on the basis of new ICT information technologies and Industry 4.0/Industry 5.0. Developed commercial applications of smart home technologies allow remote management and automation of the use processes of certain devices controlling power and generating energy for home use, energy storage and conservation, etc. Such applications are perfectly in line with the development of renewable and zero-carbon energy applications, which are installed in the home to increase the scope of energy self-sufficiency. In such a situation, it is necessary to develop systemic solutions and infrastructure for the collection of surplus energy produced by prosumer citizens. In this regard, a computerized system for managing individual household appliances based on smart home technology can fit perfectly into the current trend of pro-environmental transformation of the economy. Smart technologies based on artificial intelligence or machine learning technology, using cloud computing and the Internet of Things, allow the integration of various household appliances, including household electronics and appliances equipped with microprocessors and smart software. In this way, individual household appliances can be integrated into a central, integrated management system based on smart home technology. This kind of central integrated management system based on smart home technology can be controlled from, for example, a smartphone, a smart tv remote control, a smart watch equipped with the necessary software. With this kind of central integrated management system based on smart home technology, further devices such as home robots can be "modularly" connected, which can be very helpful for the elderly. On the other hand, the development of computerized management systems for individual household appliances based on smart home technology is also determined by the issue of improving cyber security systems and cyber security risk management. This issue is particularly relevant when a central, integrated system for remote management of individual household appliances is connected to the Internet.
In a smart city, on the one hand, many of the city's functions are carried out through automated and centrally managed information systems using new Industry 4.0/Industry 5.0 technologies. On the other hand, citizens of a smart city have the opportunity to use many of the city's information services currently offered mainly through websites and smartphone apps. Where defined certain categories of information appear on the smartphone according to the citizen's location and are automatically added to the calendar, etc. Particularly relevant information applications include systems that alert citizens to unusual weather phenomena, climatic disasters, locally growing pandemic threats, etc. Smart urban information systems can also cooperate with autonomous vehicle systems.
The issues of energy efficiency in buildings, eco-technology and eco-innovative building materials providing high levels of energy efficiency, sustainable construction, green smart city, etc. are some of the important elements for carrying out a pro-environmental transformation of the economy to build a sustainable, green, zero-carbon zero-growth and closed-loop economy. I am conducting research in the problematic of the key determinants of smoothly carrying out the pro-environmental transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero growth economy and closed loop economy. In view of the above, the issue of green, sustainable construction is one of the key elements for carrying out the pro-environmental transformation of the economy and the development of urban agglomeration developed in the green smart city model. More and more research institutes are working to develop new green technologies and eco-innovations that will make it more efficient and faster to carry out the green transformation of the economy, including the green transformation of the economy. For example, laboratories at research institutes are working on new innovative types of photovoltaic panels. For example, new types of photovoltaic panels are being developed that look like window glass but are also photovoltaic panels. In a situation where these kinds of photovoltaic panels that look like windowpanes are properly refined technologically and come on the market then they could revolutionize the building of energy self-sufficient green smart cities. Such innovative solutions of photovoltaic panel technology could be very useful in buildings that are built or planned to be built in modern sustainable green smart cities.
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can artificial intelligence technology improve the organizational management process of modern urban agglomerations developed operating according to the green smart city model?
How can artificial intelligence improve the operation of green smart city management systems?
What do you think on this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

I am working on lane line detection using lidar point clouds and using sliding window to detect lane lines. As lane lines have higher intensity values compared to asphalt, we can use the intensity values to differentiate lane lines from the low intensity non-lane-line points. However my lane detection suffers from noisy points i.e. high intensity non-lane line points. I've tried intensity thresholding, and statistical outlier removal based on intensity, but they don't seem to work as I am dealing with some pretty noisy point clouds. Please suggest some non-AI based methods which i can use to get rid of the noisy points.
Has the rivalry among leading technology companies in perfecting generative artificial intelligence technology already entered a path of no return and could inevitably lead to the creation of a super general artificial intelligence that will achieve the ability to self-improve, develop and may escape human control in this development? And if so, what risks could be associated with such a scenario of AI technology development?
The rivalry between IT giants, leading technology companies in perfecting generative artificial intelligence technology may have already entered a path of no return. On the other hand, there are increasing comments in the media about where this rivalry may lead, and whether this rivalry has already entered a path of no return. Even these aforementioned IT giants made attempts in the spring of 2023 to slow down this not-quite-tame development, but unfortunately failed. As a result, regulators are now expected to step in with the goal of sanctioning this development with regulations concerning, for example, the issue of including copyright in creative processes during which artificial intelligence takes on the role of creator. In the growing number of considerations regarding the use of artificial intelligence technology in various applications, in more and more spheres of human functioning, professional work and so on. there are questions about the dangers of this and attempts to powder the subject by suggesting that, after all, the development of AI technology and its applications cannot escape human control, that AI is unlikely to replace humans only assist in many jobs, that the vision of disaster known from the "Terminator" saga of science fiction films will not materialize, that human-like intelligent androids will never become fully autonomous, and so on. Or perhaps in this way, man is subconsciously trying to escape from other kinds of considerations, in which, for example, it could soon turn out that the technological advances taking place under Industry 5.0 driven by the entry of leading technology companies into a path of competition, which first will create a highly advanced super general artificial intelligence, which could turn out to be smarter than man, will be able to self-improve without man and develop in a direction that man will not even be able to imagine let alone predict beforehand. Perhaps the greatest fear of the consequences of the unbridled development of AI applications stems from the fact that the result of this development could be something that will intellectually surpass humans. Sometimes this kind of situation has already been referred to as an attempt to create one's own God (not an idol, just God). In these considerations, we repeatedly come to the conclusion that what is most fascinating can also generate the greatest dangers.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Has the competition among leading technology companies to perfect generative artificial intelligence technology already entered a path of no return and may inevitably lead to the creation of a super general artificial intelligence that will reach the capacity of self-improvement, development and may escape human control in this development? And if so, what risks could be associated with such a scenario of AI technology development?
Has the competition among leading technology companies to perfect generative artificial intelligence technology already entered a path of no return?
And what is your opinion about it?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

Hello,
I'm analyzing a point cloud dataset captured by a lidar sensor and have a question regarding its Vertical Field Of View (VFOV) channel configuration. The dataset documentation suggests the VFOV configuration shown in the attached image (lidar_beam.png), but my analysis (Screenshot.png) of the data implies a different setup. Specifically, the data near the origin (where the lidar is located) was captured by channel/lidar_beam 63, and as the distance from the origin increases, the channel number decreases sequentially down to channel 0. This pattern suggests that the channels are arranged vertically from bottom to top in the order of 63 to 0 rather than the even/odd pattern suggest by the lidar_beam.png. Can you provide insights or confirm if my understanding of the channel configuration being 63 (lowest) to 0 (highest) along the z-axis is correct?


Hello,
Concerning my PhD project, I'm curious about the placement of electronic toll stations within a city, particularly in Europe. I'm interested in whether they are typically situated sequentially along one or more routes, arranged in a grid network, or perhaps organized in a circular pattern.
I am also wondering if all electronic toll stations in a city are typically connected to each other through the available links among them, or is there any possibility that two or more toll stations are not connected (in a city)?
Thank you in advance for your help.
How can advanced fuzzy logic and machine learning techniques be integrated to enhance decision-making and control systems in complex, uncertain, and dynamic environments, such as autonomous vehicles navigating real-world urban traffic scenarios?
Vehicle-to-Everything (V2X) communication refers to the exchange of information between vehicles (V2V), vehicles and infrastructure (V2I), vehicles and pedestrians (V2P), and vehicles and network/cloud (V2N) using wireless communication technologies. The implementation of V2X in autonomous vehicles can significantly improve their safety and efficiency in a connected and intelligent transportation ecosystem in the following ways:
- Enhanced Situational Awareness: V2X enables vehicles to communicate with each other and share real-time information, such as position, speed, acceleration, and intentions. This enhances the vehicle's situational awareness and allows it to anticipate and react to potential hazards or critical events proactively.
- Intersection Safety: V2X can improve intersection safety by allowing vehicles to exchange data with traffic signals and infrastructure. This enables vehicles to receive traffic light phase information, optimizing speed, and facilitating cooperative maneuvers, such as platooning and intersection priority management.
- Pedestrian Safety: V2P communication enables vehicles to detect and communicate with pedestrians carrying V2X-enabled devices, such as smartphones or wearable sensors. This can alert both the vehicle and pedestrians to potential collisions, reducing accidents involving vulnerable road users.
- Cooperative Adaptive Cruise Control (CACC): V2V communication facilitates CACC, enabling vehicles to form platoons and maintain safe and coordinated spacing at high speeds. CACC can enhance traffic flow, reduce congestion, and improve fuel efficiency.
- Hazard and Road Condition Warnings: V2X enables vehicles to share data about road conditions, weather, and hazardous events with others on the network. This information can be used to warn nearby vehicles and drivers, helping them adjust their driving behavior and avoid potential dangers.
- Preemptive Emergency Braking: V2X allows vehicles to receive emergency braking warnings from other connected vehicles or infrastructure, allowing for preemptive actions and reducing the severity of collisions.
- Data Sharing for Traffic Management: V2X communication can provide real-time traffic data to traffic management centers, helping optimize traffic flow, reduce congestion, and improve overall transportation efficiency.
- Reducing Carbon Emissions: V2X-enabled vehicles can optimize their routes and speeds based on real-time traffic and road conditions, leading to reduced fuel consumption and greenhouse gas emissions.
Overall, the implementation of V2X communication systems in autonomous vehicles plays a critical role in creating a safer, more efficient, and sustainable transportation ecosystem by promoting cooperative, intelligent, and data-driven interactions between vehicles and the surrounding environment.
Automotive manufacturers are increasingly integrating augmented reality (AR) and virtual reality (VR) technologies to revolutionize various aspects of vehicle design, prototyping, manufacturing processes, and customer experiences. These immersive technologies offer significant benefits in the era of advanced automotive engineering and smart mobility solutions. Here's how AR and VR are being utilized in the automotive industry:
- Vehicle Design and Styling: Designers and engineers use VR to visualize and interact with 3D models of vehicles, enabling them to explore different design iterations and assess aesthetics, ergonomics, and functionality. VR design reviews facilitate efficient collaboration and decision-making among cross-functional teams.
- Virtual Prototyping and Simulation: VR allows automotive manufacturers to create virtual prototypes of vehicles and conduct realistic simulations of various scenarios, such as crash testing, aerodynamics, and thermal analysis. This streamlines the development process, reduces physical prototyping costs, and enhances safety assessments.
- Manufacturing and Assembly Processes: AR is applied on the factory floor to guide assembly line workers with real-time instructions and visual overlays. AR-assisted assembly and maintenance improves productivity, reduces errors, and enhances worker training and skill development.
- Quality Control and Inspection: AR and VR enable technicians to perform detailed quality control inspections using digital overlays, highlighting potential defects or deviations during manufacturing processes. This enhances product quality and reduces defects.
- Customer Experience and Marketing: Automotive manufacturers leverage AR and VR in showrooms and marketing campaigns to offer immersive and interactive experiences to customers. VR-based test drives and AR-enabled product presentations allow customers to explore vehicle features and configurations.
- Virtual Showrooms and Configurators: AR and VR technologies power virtual showrooms and vehicle configurators, enabling customers to customize vehicles, explore different options, and visualize the final product before purchase.
- Service and Maintenance: AR is utilized to provide service technicians with real-time diagnostic information, step-by-step repair instructions, and overlay information on the vehicle, simplifying maintenance tasks and reducing service time.
- Training and Skill Development: AR and VR-based training programs are used to educate service technicians, assembly line workers, and sales personnel. These interactive training modules enhance skills and knowledge retention.
- Design Validation and Customer Feedback: VR allows automotive manufacturers to conduct virtual focus groups and user studies to gather customer feedback on vehicle designs, features, and usability.
- Autonomous Vehicle Development: AR and VR technologies are utilized to simulate real-world driving scenarios for testing and validation of autonomous vehicle systems, reducing the reliance on costly physical road testing.
The integration of AR and VR technologies in the automotive industry is transforming the entire product lifecycle, from design and manufacturing to sales and customer support. These immersive technologies not only improve efficiency and reduce costs but also enhance the overall customer experience and drive innovation in advanced automotive engineering and smart mobility solutions.
Hello,
I am a young researcher and preparing myself for master's related to image processing, computer vision and ai for autonomous vehicle.
I have worked on various projects but confused with their publication that which one will be better in conference paper, journal or the book chapter. It will be very supportive if anyone suggest the best one?
I am studying at the minimum number of shared autonomous vehicles would need to meet all traffic demand of motor vehicles needs for a city, and considering the impact of joining rail transit to further optimize fleet size. I plan to cite the paper titled "Addressing the minimum fleet problem in on-demand urban mobility" in my paper, and compare the method of solving the minimum fleet size in this paper with my research method, so as to prove whether my research is effective. Therefore, I would like to ask if you have the source code for this article. If so, please contact me at Chengminghui@zjnu.edu.cn. Thank you very much!
Hey everyone, me and my team want to write a review article on the current state of autonomous vehicles and the future technology that will be used in Autonomous Vehicles, I'm not able to find the proper review article format, Can anyone please provide me the proper format for a review article, preferably in a PDF form?
Hello,
I am trying to design a nonlinear observer to estimate states for adaptive cruise control purpose. The first problem I have faced was to find an appropriate model of the vehicle( longitudinal or lateral ) with tyre forces being unknown(to be estimated). Where can I find a useful model that describe the vehicle dynamics including adaptive cruise control equations.
Thank you.
Having a global 3D map (generated using slam stereo vision) of a given space, what approach would be appropriate to use this map to localize a vehicle - using stereo vision as an input?
When will we have autonomous vehicles in use at Level 4: High Driving Automation or Level 5: Full Driving Automation?
What are the main problems? What are the road conditions? How will they adjust to different weather conditions? How will they share information with the road or with other vehicles? What technologies, algorithms, and processing detect and prevent the occurrence of accidents?
I want to perform a comparison which can be statistical to get the understanding of the severity of the accidents. What approach should I prefer to proceed with.
Hello
I am a PhD student looking to read some recent good papers that can help me identify a research topic in RL for controls applications . I have been reading through quite a few papers/topics discussing model free vs model based RL etc . Not been able to find something , may be I don't understand it yet to the extent :) .
Just for the background : My experience is with Diesel , SI engines , vehicles and controls .
One of the topics/areas that seems interesting to me is learning using RL in uncertain scenarios, this might seem to broad for most of the people .
Another possible area would be RL for connected vehicles, self driving etc .
Any help/suggestion is welcome .
Hi there,
I am working on the development of sensors for Autonomous vehicles that can assess road conditions, particularly traffic situations. The primary area is Optics based sensors such as LiDAR or Photonic Radar. I am looking for tools to develop the sensor and asking for recommendation on which software is helpful.
Regards
Photonic-based or microwave photonic-based Sensors are being used in combination with Ultrasonic, and Camera-based sensors for the smooth operation of Autonomous Vehicles. Many articles have been presented using FMCW techniques along with LiDAR tech to enhance the sensing capabilities of AVs.
What do you think is the future direction in this area of sensor development in a simulative environment?
We are planning to learn Apollo open source tool to simulate various scenario for autonomous vehicles. Could you please provide good learning resources for the same. Thank you.
Suppose I have and HD map, which have many segments (line, arc, spiral, …), that describe the road of the vehicle.
Now, How can I plot or get the coordinates along the spiral given the all following data:
- start coordinate of the spiral,
- the heading (orientation) of the spiral,
- the start and end of the curvature for the spiral, and
- the length of the spiral.
Sensors have played a significant role in intelligent robots and autonomous driving. While lidars and cameras have become dominant in the field, the advancements of other sensors have also promoted its developments.
MMWR is becoming promising. Its 4D imaging technology is becoming more and more mature. Even though I am not familiar with this kind of sensor and have no experience with it, as a person working in robotic and autonomous systems, I am interested in it. I hope this message can reach someone who knows about it.
Questions are:
1. How about the role of 4D MMWR in robots and autonomous vehicles, especially compared with lidar and cameras? or even replace them as primary sensors?
2. Is 4D MMWR robust enough for L3 or above-level autonomous driving?
3. Are there any other fields that 4D MMWR will be applied more often or promising?
Are there any available datasets of autonomous vehicles trajectories with GPS and date times specifications? if not, how would one adapt existing datasets, which are obtained from normal vehicles, to autonomous ones if possible?
A number of proprietary (and often expensive) softwares for modelling both vehicle dynamic behaviour, and the sensors for autonomous vehicles exist.
We have experience using open source solutions including Gazebo, AirSim, LG SVL (which sadly appears to no longer be supported by LG), CARLA, and a number of custom solutions bridging software like MATLAB to games engines like Unity.
Does anyone have any additional suggestions, or anyone experienced in this area have any insights / resources etc into what the future directions for coupled vehicle dynamic and autonomous vehicle simulation may be?
Hello,
I have been working on computer vision. I used datasets from Kaggle or other sites for my projects. But now I want to do lane departure warning, and real-time lane detection with real-time conditions(illuminations, road conditions, traffic, etc.). Then the idea to use simulators comes to my mind but there are lots of simulators on online but I'm confused about which one would be suitable for my work!
It would be very supportive if anyone guide me through picking up the best simulator for my works.
[Information] Special Issue - Intelligent Control and Robotics
Hi,
I am looking for clock time synchronization for autonomous vehicles network, can anyone please suggest simulation software and some good publication to start with.
Thanks
SA
For most drivers who manually control a vehicle, obeying traffic regulations like speed limits looks like a huge task for them as some overlook the importance of these strategically placed limits. Our quest is to devise ways to use AI-based technology in both autonomous and manually controlled cars to detect these speed limits on the road and for the AI technology to proceed to act on it in bringing the vehicle to a lower speed when the vehicle is travelling at a speed out of range. Issuing warning about a speed out of range is another thing and it all falls on the driver to heed to the warnings or not.
Considering the use of facial recognition cameras on autonomous vehicles, the storage of data collected, the security of the data and access, do UK data privacy laws go far enough to protect peoples rights?
Hi friends! Who knows taxi drivers? (traditional cab drivers, not Uber of Lyft). Our team is recruiting taxi drivers to participate in focus groups about technological changes in driving jobs and the future impact of autonomous vehicles on workforce. Whoever successfully particpated in the focus group can receive a $50 gift card. More information can be found at: <iframe src="https://www.facebook.com/plugins/post.php?href=https%3A%2F%2Fwww.facebook.com%2FWEAVENSF%2Fposts%2F180149620718317&show_text=true&width=500" width="500" height="737" style="border:none;overflow:hidden" scrolling="no" frameborder="0" allowfullscreen="true" allow="autoplay; clipboard-write; encrypted-media; picture-in-picture; web-share"></iframe>
Hello,
I am writing my thesis regarding building trust in autonomous vehicles (AVs). I have developed 4 hypothesis from literature review and my research model contains 4 different independent variables (Reliability, Usability, Familiarity, Regulations) and a single dependent variable (trust in AVs). I am using 5 point Likert scale based on previous studies to collect data through an online survey questionnaire. Each variable has 4 items.
With limited knowledge, I am not sure which tests would be necessary and enough to see which of my IVs really impact DV i.e. Trust?
Thank You
Shahid
Since I am working on autonomous vehicle, I am interested in developing a path planning/navigation system for guiding in row crops. Please tell me about the type of algorithm/programme that needs to be developed for same. Also, inform me what type of camera and GPS system (Make; Model) for real time application will be the best that can identify the crop rows.
Is there any firm in India which can provide the necessary equipment/components.
Will the development of autonomous cars be correlated with the development of electric cars?
Will these technologies be developed in parallel?
In the future, will a significant part of autonomous cars also be electric cars?
Please reply
I invite you to the discussion
Thank you very much
Best wishes

I conduct the lane changing decision-making model based on stackelberg game for autonomou vehicles. However, the stackelberg game is bi-level optimal problem show as below appedix file and how to attain the stackelberg equilibrium solution that distorb me for a long time. I use SQP methond in MATLAB to get the stackelberg game optimal, but the results is terribled. Can I use SQP methon to get the soluton? And could you please indict the thinking for solve for me to solve. Thank you very much.
I have been looking into self-supervised methods in computer vision. For example which looks at three consecutive frames of video, tasks a network with predicting the third frame, and uses the original as the ground truth / supervisory signal.
This type of pretext task for self supervision is a cross between context-based and semantic label based pretext tasks
Lane line detection in many ways is approached as a subset of the semantic segmentation task.
I am wondering if there is any way to come up with a pretext task that is specific to lane line detection?
I have seen where self supervision is used in the lane fitting task
But this is used after the lane segments have been identified.
I am working on an autonomous driving domain and my field poses multiple autonomous vehicle collision avoidances. I want to try to solve it using RL. In this case, the following statements regarding the RL method are correct or any thins complicated with the fundamentals of RL. Please explain to me.
"Through Learning Control, control knowledge of a control function can be created through
the training by Reinforcement Learning. However, the conventional Reinforcement Learning
method does not provide the application of more than one control function within a Learning
Control System. Execution of more control functions within a Learning Control System
would require the application of multiple learning processes within a control system. Methods concerning the application of learning processes in Learning Control vary depending on
the application of the control device and the purpose of the system."
With the Trolley Problem being a hot disucssion with lots of phylosophical and technical papers discussed on it. It is eventually very hard to get to a final idea whether to incorporate this problem into AVs driving ethics? do they really create the dilemma ?
in 2017, the German ethics commission for automated and connected driving released 20 ethical guidelines for autonomous vehicles.
and Yet one more question : Why this comission paper, have so few references? does it mean they have cared less about other phylosophers ideas? or they have tried to found some ideas?
There are lots of relevant papers. bring them in this post to discuss it.
Autonomous vehicle, robots and rovers are finding applications in space exploration. Which tasks can Autonomous rovers and robots can take over from human (In other planets like mars, or moon or titan etc). How can an army of robots create all the infrastructure that humans needs for settlement?
Hello
I want to find accurate locations of some static objects to be used as landmarks for localizing other mobile object. As the landmarks will be used to localize other object, their own location must be accurate. Kindly suggest some practical methods for accurate positioning of static objects(landmark).
Best regards
I have attached two papers, which discuss the trolley problem differently. one trying to follow the question and picture possible cases, the other, "Avoids" the unfairness of the Trolley problem, but its discussion is not long enough and gets to a conclusion fast. Which doctorine of thought do you prefer?
Anyone can suggest a dataset of scenarios/test cases that could be used to test and validate autonomous vehicles? I am interested in scenarios that are described in english or in any scenario description language that could be used for virtual closed loop testing?
Hi All
I'm looking for some papers on Self driving cars that discuss the current capability and work, on how much Data processing these cars do, and what are the steps and techniques applied to improve them
Hello
I need to know about the ways to represent a path mathematically and technically in the vehicle industry based on a map which contains lanes. An initial search shows that path generally defined sometimes using some way-points, others use curvilinear coordinates and others define a network of connected segments. Which are the relevant and common ways to represent a path on map with lanes ? Any citations about the matter ?!
Cordially
Hi there, im currently writing my dissertation on how autonomous vehicles will influence real estate valuation.
To define real estate value factors (factors that residents of city X find influential in determining residential valuation) I am conducting a qualitative survey to exhibit what people are most attracted to.
How can I justify my survey size, of say 100 people?
Colleagues and I are about to begin a project investigating the role of town planners and local authorities in establishing the introduction of connected and autonomous vehicles (CAVs).
What views do you have on the needs of users of CAVs, particularly members of the disabled community; the usefulness of planners creating infrastructure to accommodate CAVs and join these with existing conventional forms of travel; and how these can combine to establish a 'whole of journey' approach to future transport systems?
Dear Researchers,
I am pursuing my masters in Mechatronics (Germany) and currently working as a system validation intern. I am looking for some advice/guidance on possible topics in the field of autonomous driving. I am open to any sub-field but my current experience is in system validation of ADAS/ Autonomous Driving mostly in a Software-in-Loop environment. There is currently not a industry accepted standard for validation of ADAS/AD features so something along these lines would be greatly appreciated
Thanks in advance!
hi, now I am researching about these things, this is my first time to ask question at this site. I need various opinions who is expert about this topic. Please help me !!
How do you think the social environment will change in the near future when full-autonomous driving becomes the norm?
1. Future trends in the automobile market
2. Trends in technology announcements including automobiles
3.Changes in the living environment of general consumers
*English, Chinese OK:)
In my opinion, the development of the necessary infrastructure and security stabilities is of key importance for the development of autonomous cars technology, so that the development of autonomous cars technology and the increase in the number of autonomous cars does not increase statistics on the number of road accidents.
In addition, the development of autonomous cars technology can be paralleled to the development of electromobility. For the development of electromobility and the number of used electric cars, it is also necessary to build the necessary infrastructure installed on roads, urban streets and interurban arteries of communication charging points for batteries into electricity.
In some countries there are active policies for the development of electromobility, under which the state from public finance funds pays extra to purchase an electric car and invests in projects to develop the necessary infrastructure for charging points in electricity. Other power plants are also being built as part of the development of renewable energy sources, because the development of electromobility is causing a significant increase in electricity demand. Unfortunately, this pro-ecological, active policy for the development of electromobility is carried out only in some countries.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What are the main determinants of the development of electromobility and autonomous cars technology?
Please reply
I invite you to the discussion
Thank you very much
Best wishes

Hi,
I am designing a model for detecting attacks launched against connected vehicles (autonomous vehicles). Where can I find a dataset having connected vehicle or connected vehicle network related attacks?
A monocular camera is to be calibrated, which is located in the area of the vehicle and looks in front of the direction of travel. During the calibration, the extrinsic parameters (position and rotation between the camera coordinate system and the origin of the vehicle coordinate system: Center of the rear axle of the vehicle) should be calculated. The camera parameters are calculated online, i.e. while the camera is taking pictures. The algorithm should automatically calculate the extrinsic parameters from driving scene images while driving.
I am looking forward to your feedback !
Do you think that artificial intelligence will be implemented in the control systems of driving and orientation in the field in autonomous cars?
What are the effects of artificial intelligence implemented in the field of driving control systems and orientation in the field of autonomous cars?
Will autonomous cars be safe?
Will autonomous cars be mostly electric cars at the same time?
Please, answer, comments.
I invite you to the discussion.
Best wishes

Hi,
Kindly can anyone suggest a multiagent based traffic simulator for selecting of best possible routes?
Regards.
Dear researchers,
if you are you interested in research on efficient autonomous vehicles, I have something new for you.
We have just launched our new open source reinforcement learning environment. Here you can find it: https://github.com/dynamik1703/gym_longicontrol
Our new environment is in the field of autonomous driving. It offers the possibility to test and further develop algorithms for the efficient longitudinal control.
The longitudinal control problem has various challenges. One example is the trade-off between conflicting goals of travel time minimization and energy consumption. They contradict each other because a fast driving vehicle leads to high-energy consumption and vice versa.
Through the proposed RL environment, which is adapted to the OpenAi Gym standardization, we show that it is easy to prototype and implement state-of-art RL algorithms. Besides, the LongiControl environment is suitable for various examinations. In addition to the comparison of RL algorithms and the evaluation of safety algorithms, investigations in the area of Multi-Objective Reinforcement Learning are also possible. Further possible research objectives are the comparison with planning algorithms for known routes, investigation of the influence of model uncertainties and the consideration of very long-term objectives like arriving at a specific time.
LongiControl is designed to enable the community to leverage the latest strategies of reinforcement learning to address a real-world and high-impact problem in the field of autonomous driving.
Have fun trying it out! If you have any questions, feel free to write.
Hi,
I built a Simulink vehicle model with Dugoff's tire model that requires two parameters to calculate Fx and Fy; namely, the longitudinal stiffness and the cornering stiffness. Now I would like to verify my Simulink model by comparing the results with MSC ADAMS. ADAMS does not have Dugoff's tire model. How can I get these two parameters from ADAMS ?
Please share the link or the file. I have tried in NCAC but the website is not accessible. Thank you in advance.
I was told by a person without any reference,
Co-60 source mus be replaced after the dose rate reached 50 cGy/minute..please anyone may guide me to provide the correct reference??
I some papers, the mean square error is considered. In some other, the mse is normalized by dividing the error by the (total sampling instants x the total length of the reference trajectory).
Which solution does represent the factual error?
The challenge faced by the autonomous vehicle industry is to keep pace with the exploration of autonomous vehicles. The industrial research centers are limited and prevent them from sharing their thoughts. This in turn prevents their researchers from gaining access to other knowledge pools.
It is important for industries to come together and maintain an open relationship with various research universities in order to find the best solution for the development and evaluation of autonomous vehicles so that autonomous vehicles meet the basic safety and protection criteria.
Do we have a specific model and strategy for industry-university collaboration on autonomous vehicle products and services?
I am working on Application - Specific Radio Resource Allocation in 5G and I need to know the size of packets used for every application or use-case of 5G if possible. Applications like; Video conferencing, AR/VR, Web browsing, Wireless E-health, Industry automation, Autonomous vehicles, Smart Energy, Smart City and so on.