scholarly journals Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2659
Author(s):  
Ryuichi Fukatsu ◽  
Kei Sakaguchi
Keyword(s):  
Millimeter Wave ◽  
Data Rate ◽  
Sensor Data ◽  
Automated Driving ◽  
V2v Communication ◽  
Additional Information ◽  
Safety And Reliability ◽  
V2v Communications ◽  
Vehicle Movement ◽  
Blind Spots

The combination of onboard sensors on vehicles with wireless communication has great advantages over the conventional driving systems in terms of safety and reliability. This technique is often called cooperative perception. Cooperative perception is expected to compensate for blind spots in dynamic maps, which are caused by obstacles. Few blind spots in dynamic maps can improve the safety and reliability of driving thanks to the additional information beyond the sensing of the onboard sensors. In this paper, we analyzed the required sensor data rate to be exchanged for the cooperative perception in order to enable a new level of safe and reliable automated driving in overtaking scenario. The required sensor data rate was calculated by the combination of recognition and vehicle movement to adopt realistic assumptions. In the end of the paper, we compared the required sensor data rate with the outage data rate realized by the conventional V2V communication and millimeter-wave communication. The results showed the indispensability of millimeter-wave communications in automated driving systems.

scholarly journals Automated Driving with Cooperative Perception Based on CVFH and Millimeter-Wave V2I Communications for Safe and Efficient Passing through Intersections

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5854
Author(s):  
Ryuichi Fukatsu ◽  
Kei Sakaguchi
Keyword(s):  
Wireless Communications ◽  
Millimeter Wave ◽  
Traffic Congestion ◽  
Data Rate ◽  
Sensor Data ◽  
Connected Vehicles ◽  
Automated Driving ◽  
Connected Cars ◽  
Millimeter Wave Communications ◽  
Blind Spots

The development of automated driving is actively progressing, and connected cars are also under development. Connected cars are the technology of connecting vehicles to networks so that connected vehicles can enhance their services. Safety services are among the main services expected in connected car society. Cooperative perception belongs to safety services and improves safety by visualizing blind spots. This visualization is achieved by sharing sensor data via wireless communications. Therefore, the number of visualized blind spots highly depends upon the performance of wireless communications. In this paper, we analyzed the required sensor data rate to be shared for the cooperative perception in order to realize safe and reliable automated driving in an intersection scenario. The required sensor data rate was calculated by the combination of recognition and crossing decisions of an automated driving vehicle to adopt realistic assumptions. In this calculation, CVFH was used to derive tight requirements, and the minimum required braking aims to alleviate the traffic congestion around the intersection. At the end of the paper, we compare the required sensor data rate with the outage data rate realized by conventional and millimeter-wave communications, and show that millimeter-wave communications can support safe crossing at a realistic velocity.

scholarly journals Distributed and Scalable Radio Resource Management for mmWave V2V Relays towards Safe Automated Driving

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 93
Author(s):  
Yue Yin ◽  
Tao Yu ◽  
Kazuki Maruta ◽  
Kei Sakaguchi
Keyword(s):  
Resource Management ◽  
Interference Mitigation ◽  
Radio Resource Management ◽  
Decisive Role ◽  
Data Rate ◽  
Radio Resource ◽  
Automated Driving ◽  
V2v Communication ◽  
High Data ◽  
V2v Communications

The millimeter-wave (mmWave) Vehicle-to-Vehicle (V2V) communication system has drawn attention as a critical technology to extend the restricted perception of onboard sensors and upgrade the level of vehicular safety that requires a high data rate. However, co-channel inter-link interference presents significant challenges for scalable V2V communications. To overcome such limitations, this paper firstly analyzes the required data rate ensuring maneuver safety via mmWave V2V relays in an overtaking traffic scenario. Based on these preparations, we propose a distributed radio resource management scheme that integrates spatial, frequency, and power domains for two transmission ranges (short/long). In the spatial domain, ZigZag antenna configuration is utilized to mitigate the interference, which plays a decisive role in the short inter-vehicle distance. In frequency and power domains, two resource blocks are allocated alternately, and transmit power is controlled to suppress the interference, which has a decisive impact on interference mitigation in the long inter-vehicle distance. Simulation results reveal that the achievable End-to-End (E2E) throughput maintains consistently higher than the required data rate for all vehicles. Most importantly, it works effectively in scalable mmWave V2V topology.

scholarly journals Simultaneous Target Classification and Moving Direction Estimation in Millimeter-Wave Radar System

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5228
Author(s):  
Jin-Cheol Kim ◽  
Hwi-Gu Jeong ◽  
Seongwook Lee
Keyword(s):  
Millimeter Wave ◽  
Radar System ◽  
Sensor Data ◽  
Test Field ◽  
Target Classification ◽  
Radar Sensor ◽  
Millimeter Wave Radar ◽  
Direction Estimation ◽  
Wave Radar ◽  
Moving Direction

In this study, we propose a method to identify the type of target and simultaneously determine its moving direction in a millimeter-wave radar system. First, using a frequency-modulated continuous wave (FMCW) radar sensor with the center frequency of 62 GHz, radar sensor data for a pedestrian, a cyclist, and a car are obtained in the test field. Then, a You Only Look Once (YOLO)-based network is trained with the sensor data to perform simultaneous target classification and moving direction estimation. To generate input data suitable for the deep learning-based classifier, a method of converting the radar detection result into an image form is also proposed. With the proposed method, we can identify the type of each target and its direction of movement with an accuracy of over 95%. Moreover, the pre-trained classifier shows an identification accuracy of 85% even for newly acquired data that have not been used for training.

scholarly journals Investigating and Modeling of Cooperative Vehicle-to-Vehicle Safety Stopping Distance

2021 ◽  
Vol 13 (3) ◽  
pp. 68
Author(s):  
Steven Knowles Flanagan ◽  
Zuoyin Tang ◽  
Jianhua He ◽  
Irfan Yusoff
Keyword(s):  
High Reliability ◽  
Base Station ◽  
Ieee 802.11P ◽  
Packet Losses ◽  
The Road ◽  
V2v Communication ◽  
Stopping Distance ◽  
Vehicle To Vehicle ◽  
V2v Communications ◽  
On The Road

Dedicated Short-Range Communication (DSRC) or IEEE 802.11p/OCB (Out of the Context of a Base-station) is widely considered to be a primary technology for Vehicle-to-Vehicle (V2V) communication, and it is aimed toward increasing the safety of users on the road by sharing information between one another. The requirements of DSRC are to maintain real-time communication with low latency and high reliability. In this paper, we investigate how communication can be used to improve stopping distance performance based on fieldwork results. In addition, we assess the impacts of reduced reliability, in terms of distance independent, distance dependent and density-based consecutive packet losses. A model is developed based on empirical measurements results depending on distance, data rate, and traveling speed. With this model, it is shown that cooperative V2V communications can effectively reduce reaction time and increase safety stop distance, and highlight the importance of high reliability. The obtained results can be further used for the design of cooperative V2V-based driving and safety applications.

Bulk Sensor Data Sharing Using Millimeter Wave V2X for Enhanced Safety and Comfort in Mobility

2018 ◽  
Author(s):  
Masataka Irie ◽  
Gaius Wee Yao Huang ◽  
Michael Sim Hong Cheng ◽  
Kazuaki Takahashi
Keyword(s):  
Data Sharing ◽  
Millimeter Wave ◽  
Sensor Data

Data Collection and Analysis for the Creation of a Digital Shadow During the Production of Thermoplastic Composite Layers in Unbonded Flexible Pipes

2018 ◽  
Author(s):  
Martin Schäkel ◽  
John McNab ◽  
Neville Dodds ◽  
Tido Peters ◽  
Henning Janssen ◽  
...  
Keyword(s):  
External Pressure ◽  
Thermoplastic Composite ◽  
Sensor Data ◽  
Consolidation Process ◽  
Specific Strength ◽  
Additional Information ◽  
Flexible Pipes ◽  
Potential Part ◽  
Path Dependent ◽  
Unbonded Flexible Pipes

Unbonded flexible pipes present a mature technology for the efficient recovery and transport of hydrocarbons offshore. The substitution of metallic reinforcement layers in the multi-layered structure by thermoplastic fiber-reinforced polymer (FRP) presents a solution for self-weight issues of especially long pipes, as FRP materials display high specific strength and modulus while being resistant to external pressure and corrosion. The production of these layers is automated by the laser-assisted tape winding process without the need of additional curing steps. During the manufacturing process, several data like process temperature and consolidation pressure are continuously monitored by non-contact sensors to ensure process stability without interfering in the consolidation process. To gain additional information about the temperature distribution within the multi-layered laminate, contact temperature sensors were introduced in the tape winding process. By this method the temperature of subjacent tapes can be assessed during the continued winding process. Additionally, this paper features a new approach of utilizing winding path data for relating the time-dependent sensor data to the exact position on the produced part. The visualization of path-dependent sensor data opens up possibilities of linking quality monitoring results to manufacturing insufficiencies and potential part defects.

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