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Sensor Fusion and Advanced Controller for Connected and Automated Vehicles

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 19747

Special Issue Editors

Zhejiang Lab, Kechuang Avenue, Hangzhou 311121, China
Interests: state estimation; vehicle dynamics and control; path planning and path tracking control
Special Issues, Collections and Topics in MDPI journals
Intelligent Vehicles & Cognitive Robotics, Technische Universiteit Delft, Mekelweg 5, 2628 CD Delft, The Netherlands
Interests: motion comfort; chassis design and optimisation; vehicle dynamics and control; tyre dynamics and tyre wear
Special Issues, Collections and Topics in MDPI journals
Faulty of Engineering and Information Science, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: vehicle dynamics and control systems; robust control theory and engineering applications; robotics and automation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For conventional on-road vehicles, due to a lack of adequate sensor information, vehicle dynamics controllers can only rely on the dedicated state estimators, such as the sideslip angle estimator and the velocity estimator. Sometimes the estimation results are not reliable due to the single estimator source. However, autonomous electric vehicles are equipped with a number of advanced sensors such as radar and cameras. The measurements of these additional sensors can be fused into the vehicle state estimators to build a sensor fusion system, which can lead to a large number of highly reliable estimated vehicle states. This enriched vehicle state information can be greatly beneficial to the complex integrated advanced controller design (such as path planning, a path-tracking controller, or integrated chassis control) for automated vehicles or automated vehicles in a connected vehicle platoon.

We welcome the submission of both review articles and original research papers relating the sensor fusion strategy design or vehicle dynamics controller design for connected and automated vehicles. There is a particular interest in papers focusing on how advanced controllers for autonomous vehicles can fully utilize the states estimated from sensor fusion systems to maximise the control performance of automated passenger vehicles or heavy vehicles.

Dr. Boyuan Li
Prof. Dr. Yafei Wang
Dr. Georgios Papaioannou
Dr. Haiping Du
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • state estimator
  • sensor fusion
  • automated vehicles
  • connected vehicles
  • integrated controller
  • path planning control
  • path tracking control

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Published Papers (13 papers)

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Editorial

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5 pages, 200 KiB  
Editorial
Sensor Fusion and Advanced Controller for Connected and Automated Vehicles
by Boyuan Li, Yafei Wang, Georgios Papaioannou and Haiping Du
Sensors 2023, 23(16), 7015; https://0-doi-org.brum.beds.ac.uk/10.3390/s23167015 - 08 Aug 2023
Viewed by 760
Abstract
Nowadays, intelligent vehicles are equipped with a number of advanced sensors, such as radar and cameras [...] Full article

Research

Jump to: Editorial, Other

16 pages, 4598 KiB  
Article
A Study on Dynamic Motion Planning for Autonomous Vehicles Based on Nonlinear Vehicle Model
by Xin Tang, Boyuan Li and Haiping Du
Sensors 2023, 23(1), 443; https://0-doi-org.brum.beds.ac.uk/10.3390/s23010443 - 31 Dec 2022
Cited by 3 | Viewed by 1245
Abstract
Autonomous driving technology, especially motion planning and the trajectory tracking method, is the foundation of an intelligent interconnected vehicle, which needs to be improved urgently. Currently, research on path planning methods has improved, but few of the current studies consider the vehicle’s nonlinear [...] Read more.
Autonomous driving technology, especially motion planning and the trajectory tracking method, is the foundation of an intelligent interconnected vehicle, which needs to be improved urgently. Currently, research on path planning methods has improved, but few of the current studies consider the vehicle’s nonlinear characteristics in the reference model, due to the heavy computational effort. At present, most of the algorithms are designed by a linear vehicle model in order to achieve the real-time performance at the cost of lost accuracy. To achieve a better performance, the dynamics and kinematics characteristics of the vehicle must be simulated, and real-time computing ensured at the same time. In this article, a Takagi–Sugeno fuzzy-model-based closed-loop rapidly exploring random tree algorithm with on-line re-planning process is applied to build the motion planner, which effectively improves the vehicle performance of dynamic obstacle avoidance, and plans the local obstacle avoidance path in line with the dynamic characteristics of the vehicle. A nonlinear vehicle model is integrated into the motion planner design directly. For fast local path planning mission, the Takagi–Sugeno fuzzy modelling method is applied to the modeling process in the planner design, so that the vehicle state can be directly utilized into the path planner to create a feasible path in real-time. The performance of the planner was evaluated by numerical simulation. The results demonstrate that the proposed motion planner can effectively generate a reference trajectory that guarantees driving efficiency with a lower re-planning rate. Full article
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17 pages, 10223 KiB  
Article
A Driving-Adapt Strategy for the Electric Vehicle with Magneto-Rheological Fluid Transmission Considering the Powertrain Characteristics
by Peng Liao, Donghong Ning, Tao Wang and Haiping Du
Sensors 2022, 22(24), 9619; https://0-doi-org.brum.beds.ac.uk/10.3390/s22249619 - 08 Dec 2022
Cited by 1 | Viewed by 896
Abstract
The additional energy consumption caused by the incompatibility between existing electric vehicle (EV) powertrain characteristics and driving conditions inevitably curbs the promotion and development of EVs. Hence, there is an urgent demand for the driving-adapt strategy, which aims to minimize EV energy consumption [...] Read more.
The additional energy consumption caused by the incompatibility between existing electric vehicle (EV) powertrain characteristics and driving conditions inevitably curbs the promotion and development of EVs. Hence, there is an urgent demand for the driving-adapt strategy, which aims to minimize EV energy consumption due to both powertrain characteristics and driving conditions. In order to fully explore the EV driving-adapt potential, this paper equips the EV with a magneto-rheological fluid transmission (MRFT). First, an EV dynamics analysis of the driving conditions, the powertrain model considering the energy transmission process, and the driving-adapt transmission model considering magneto-rheological fluid (MRF) is conducted to clarify the quantitative relation between the driving conditions and the powertrain. Second, a driving-adapt optimization strategy in the specific driving condition is proposed. Finally, the results and discussions are executed to study (i) the determination of the MRFT fixed speed ratio and variable speed ratio range, (ii) the application potential analysis of the proposed strategy, and (iii) the feasibility analysis of the proposed strategy. The results indicate that (i) the urban driving condition has higher requirements for the MRFT, (ii) EVs equipped with MRFT achieve the expected driving performance at the most states of charge (SOCs) and environmental temperatures, except for the SOC lower than 10%, and (iii) the driving time with efficiency greater than 80% can be increased by the MRFT from 10.1% to 58.7% and from 66.8% to 88.8% in the urban and suburban driving conditions, respectively. Thus, the proposed driving-adapt strategy for the EV equipped with the MRFT has the potential to alleviate or eliminate the traffic problems caused by the incompatibility of the EV powertrain characteristics and the driving conditions. Full article
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15 pages, 5209 KiB  
Article
Traffic Sign Recognition Based on the YOLOv3 Algorithm
by Chunpeng Gong, Aijuan Li, Yumin Song, Ning Xu and Weikai He
Sensors 2022, 22(23), 9345; https://0-doi-org.brum.beds.ac.uk/10.3390/s22239345 - 01 Dec 2022
Cited by 11 | Viewed by 2427
Abstract
Traffic sign detection is an essential component of an intelligent transportation system, since it provides critical road traffic data for vehicle decision-making and control. To solve the challenges of small traffic signs, inconspicuous characteristics, and low detection accuracy, a traffic sign recognition method [...] Read more.
Traffic sign detection is an essential component of an intelligent transportation system, since it provides critical road traffic data for vehicle decision-making and control. To solve the challenges of small traffic signs, inconspicuous characteristics, and low detection accuracy, a traffic sign recognition method based on improved (You Only Look Once v3) YOLOv3 is proposed. The spatial pyramid pooling structure is fused into the YOLOv3 network structure to achieve the fusion of local features and global features, and the fourth feature prediction scale of 152 × 152 size is introduced to make full use of the shallow features in the network to predict small targets. Furthermore, the bounding box regression is more stable when the distance-IoU (DIoU) loss is used, which takes into account the distance between the target and anchor, the overlap rate, and the scale. The Tsinghua–Tencent 100K (TT100K) traffic sign dataset’s 12 anchors are recalculated using the K-means clustering algorithm, while the dataset is balanced and expanded to address the problem of an uneven number of target classes in the TT100K dataset. The algorithm is compared to YOLOv3 and other commonly used target detection algorithms, and the results show that the improved YOLOv3 algorithm achieves a mean average precision (mAP) of 77.3%, which is 8.4% higher than YOLOv3, especially in small target detection, where the mAP is improved by 10.5%, greatly improving the accuracy of the detection network while keeping the real-time performance as high as possible. The detection network’s accuracy is substantially enhanced while keeping the network’s real-time performance as high as possible. Full article
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16 pages, 4522 KiB  
Article
Research on Forward Problem of Rail Detection Based on Magnetoacoustic Coupling
by Xin Huang, Aijuan Li, Zhen Huang, Yi Sun, Yumin Song and Ning Xu
Sensors 2022, 22(15), 5539; https://0-doi-org.brum.beds.ac.uk/10.3390/s22155539 - 25 Jul 2022
Cited by 1 | Viewed by 1045
Abstract
According to the characteristics of rail defects, a rail microcrack detection method based on magnetoacoustic coupling effect is proposed in this paper. Firstly, the basic principle of a rail microcrack detection method based on magnetoacoustic coupling effect is described, and then the model [...] Read more.
According to the characteristics of rail defects, a rail microcrack detection method based on magnetoacoustic coupling effect is proposed in this paper. Firstly, the basic principle of a rail microcrack detection method based on magnetoacoustic coupling effect is described, and then the model is analyzed theoretically. Through simulation calculation, the current density distribution and Lorentz force distribution generated by electromagnetic excitation, the motion characteristics of particles under Lorentz force and the sound field distribution characteristics of magnetoacoustic signals generated by Lorentz force are obtained. Finally, an experimental platform was set up and the steel ring model was preliminarily tested. The magnetic and acoustic signals of the two steel ring boundaries excited by an electromagnetic field were collected. These signals correspond to the position distribution of the steel ring. The state change of rail microstructure will cause a change in the conductivity characteristics of rail materials, and will affect the characteristics and distribution of sound pressure in the detection. Therefore, the detection method based on the magnetoacoustic coupling effect can detect the surface microcracks of high-speed rail. This method has great feasibility and development potential in the field of rail flaw detection. Full article
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15 pages, 1371 KiB  
Article
Multi-Criteria Evaluation for Sorting Motion Planner Alternatives
by Georgios Papaioannou, Zaw Htike, Chenhui Lin, Efstathios Siampis, Stefano Longo and Efstathios Velenis
Sensors 2022, 22(14), 5177; https://0-doi-org.brum.beds.ac.uk/10.3390/s22145177 - 11 Jul 2022
Cited by 2 | Viewed by 1312
Abstract
Automated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put [...] Read more.
Automated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put their wide impact at risk, as well as their acceptance by the public. In this direction, this paper presents the application of motion planning in order to minimise motion sickness in automated vehicles. Thus, an optimal control problem is formulated through which we seek the optimum velocity profile for a predefined road path for multiple fixed journey time (JT) solutions. In this way, a Pareto Front will be generated for the conflicting objectives of MS and JT. Despite the importance of optimising both of these, the optimum velocity profile should be selected after taking into consideration additional objectives. Therefore, as the optimal control is focused on the MS minimisation, a sorting algorithm is applied to seek the optimum solution among the pareto alternatives of the fixed time solutions. The aim is that this solution will correspond to the best velocity profile that also ensures the optimum compromise between motion comfort, safety and driving behaviour, energy efficiency, journey time and riding confidence. Full article
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26 pages, 12941 KiB  
Article
Conceptual Modeling of Extended Collision Warning System from the Perspective of Smart Product-Service System
by Chunlong Wu, Hanyu Lv, Tianming Zhu, Yunhe Liu and Marcus Vinicius Pereira Pessôa
Sensors 2022, 22(12), 4654; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124654 - 20 Jun 2022
Cited by 3 | Viewed by 1532
Abstract
While Product-Service Systems (PSS) have a potential sustainability impact by increasing a product’s life and reducing resource consumption, the lack of ownership might lead to less responsible user behavior. Smart PSS can overcome this obstacle and guarantee correct and safe PSS use. In [...] Read more.
While Product-Service Systems (PSS) have a potential sustainability impact by increasing a product’s life and reducing resource consumption, the lack of ownership might lead to less responsible user behavior. Smart PSS can overcome this obstacle and guarantee correct and safe PSS use. In this context, intelligent connected vehicles (ICVs) with PSS can effectively reduce traffic accidents and ensure the safety of vehicles and pedestrians by guaranteeing optimal and safe vehicle operation. A core subsystem to support that is the collision-warning system (CWS). Existing CWSs are, however, limited to in-car warning; users have less access to the warning information, so the result of CWS for collision avoidance is insufficient. Therefore, CWS needs to be extended to include more elements and stakeholders in the collision scenario. This paper aims to provide a novel understanding of extended CWS (ECWS), outline the conceptual framework of ECWS, and contribute a conceptual modeling approach of ECWS from the smart PSS perspective at the functional level. It defines an integrated solution of intelligent products and warning services. The function is modeled based on the Theory of Inventive Problem Solving (TRIZ). Functions of an ECWS from the perspective of smart PSS can be comprehensively expressed to form an overall solution of integrated intelligent products, electronic services, and stakeholders. Based on the case illustration, the proposed method can effectively help function modeling and development of the ECWS at a conceptual level. This can effectively avoid delays due to traffic accidents and ensure the safety of vehicles and pedestrians. Full article
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20 pages, 3489 KiB  
Article
Analysis of a Measurement Method and Test System for Pressure Change Rates in Commercial Vehicle Brake Chambers
by Gangyan Li, Rui Shen, Yudong Liu, Fan Yang and Jian Hu
Sensors 2022, 22(9), 3427; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093427 - 30 Apr 2022
Cited by 1 | Viewed by 1211
Abstract
The pressure change rate (PCR) of the brake chamber is the key control parameter and evaluation index in the pneumatic braking system for intelligent braking. The PCR threshold value of commercial vehicle brake chambers for braking comfort is analyzed. The PCR measurement method [...] Read more.
The pressure change rate (PCR) of the brake chamber is the key control parameter and evaluation index in the pneumatic braking system for intelligent braking. The PCR threshold value of commercial vehicle brake chambers for braking comfort is analyzed. The PCR measurement method based on a laminar flow resistance tube is proposed, and the PCR test system is designed. The simulation model of a PCR test system for commercial vehicle brake chambers is presented. By analyzing the simulation and experimental results, it is validated that the PCR test system of commercial vehicle brake chambers has the function of measuring PCR in real time. Finally, according to the MSA (Measurement System Analysis) evaluation method, the performance of the PCR test system for commercial vehicle brake chambers is analyzed, and the correctness and applicability of the test system are verified. Full article
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25 pages, 33558 KiB  
Article
Estimation of Longitudinal Force, Sideslip Angle and Yaw Rate for Four-Wheel Independent Actuated Autonomous Vehicles Based on PWA Tire Model
by Xiaoqiang Sun, Yulin Wang and Weiwei Hu
Sensors 2022, 22(9), 3403; https://0-doi-org.brum.beds.ac.uk/10.3390/s22093403 - 29 Apr 2022
Cited by 2 | Viewed by 1866
Abstract
This article introduces an efficient and high-precision estimation framework for four-wheel independently actuated (FWIA) autonomous vehicles based on a novel tire model and adaptive square-root cubature Kalman filter (SCKF) estimation strategy. Firstly, a reliable and concise tire model that considers the tire’s nonlinear [...] Read more.
This article introduces an efficient and high-precision estimation framework for four-wheel independently actuated (FWIA) autonomous vehicles based on a novel tire model and adaptive square-root cubature Kalman filter (SCKF) estimation strategy. Firstly, a reliable and concise tire model that considers the tire’s nonlinear mechanics characteristics under combined conditions through the piecewise affine (PWA) identification method is established to improve the accuracy of the lateral dynamics model of FWIA autonomous vehicles. On this basis, the longitudinal relaxation length of each tire is integrated into the lateral dynamics modeling of FWIA autonomous vehicle. A novel nonlinear state function, including the PWA tire model, is proposed in this paper. To reduce the impact of the uncertainty of noise statistics on the estimation accuracy, an adaptive SCKF estimation algorithm based on the maximum a posteriori (MAP) criterion is proposed in the estimation framework. Finally, the estimation accuracy and stability of the adaptive SCKF algorithm are verified by the co-simulation of CarSim and Simulink. The simulation results show that when the statistical characteristics of noise are unknown and the target state changes suddenly under critical maneuvers, the estimation framework proposed in this paper still maintains high accuracy and stability. Full article
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19 pages, 4874 KiB  
Article
Research on Measurement Principle and Key Measuring Devices of Pressure Change Rate for Electronically Controlled Pneumatic Brake of Commercial Vehicle Based on Poiseuille’s Law
by Jian Hu, Min Yan, Rui Yang, Fan Yang and Gangyan Li
Sensors 2022, 22(8), 3023; https://0-doi-org.brum.beds.ac.uk/10.3390/s22083023 - 14 Apr 2022
Cited by 2 | Viewed by 1570
Abstract
For intelligence brakes in the electronic pneumatic brake system of commercial vehicles, the pressure change rate is used as the key control parameter and evaluation index. This can improve the brake safety, stability, and ride comfort of the vehicle. The real-time detection of [...] Read more.
For intelligence brakes in the electronic pneumatic brake system of commercial vehicles, the pressure change rate is used as the key control parameter and evaluation index. This can improve the brake safety, stability, and ride comfort of the vehicle. The real-time detection of the brake pressure change rate for commercial vehicles is the premise for realizing the accurate control of brake pressure change rate. Based on Poiseuille’s law, an efficient measurement method of brake pressure change rate is proposed for commercial vehicles, and a new measuring device with an isothermal container and laminar flow resistance tube as the core components is designed. Through thermal insulation performance tests, flow resistance tests and measurement accuracy tests, combined with simulations, the effects of structural parameters and copper wire filling density on the performance of the isothermal container are analyzed, and these key parameters are optimized to improve the thermal insulation performance. A tubular laminar flow resistance tube composed of 304 stainless steel capillaries in parallel is designed. The influence mechanism of core parameters such as the number, radius, and length of laminar flow channels on its performance is studied, and the optimal parameter array is selected to optimize its performance. The experimental platform for measuring brake pressure change rate is constructed. By comparing the measurement curve of brake pressure change rate under simulation and experiment, the correctness and effectiveness of the pressure change rate measurement principle and the key components for electronically controlled pneumatic brakes of commercial vehicles are verified to meet engineering requirements. Full article
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27 pages, 10093 KiB  
Article
Robust Speed Tracking Control for Future Electric Vehicles under Network-Induced Delay and Road Slope Variation
by Jie Zhang, Qianrong Fan, Ming Wang, Bangji Zhang and Yuanchang Chen
Sensors 2022, 22(5), 1787; https://0-doi-org.brum.beds.ac.uk/10.3390/s22051787 - 24 Feb 2022
Cited by 5 | Viewed by 1342
Abstract
Integrated motor-transmission (IMT) powertrain systems are widely used in future electric vehicles due to the advantages of their simple structure configuration and high controllability. In electric vehicles, precise speed tracking control is critical to ensure good gear shifting quality of an IMT powertrain [...] Read more.
Integrated motor-transmission (IMT) powertrain systems are widely used in future electric vehicles due to the advantages of their simple structure configuration and high controllability. In electric vehicles, precise speed tracking control is critical to ensure good gear shifting quality of an IMT powertrain system. However, the speed tracking control design becomes challenging due to the inevitable time delay of signal transmission introduced by the in-vehicle network and unknown road slope variation. Moreover, the system parameter uncertainties and signal measurement noise also increase the difficulty for the control algorithm. To address these issues, in this paper a robust speed tracking control strategy for electric vehicles with an IMT powertrain system is proposed. A disturbance observer and low-pass filter are developed to decrease the side effect from the unknown road slope variation and measurement noise and reduce the estimation error of the external load torque. Then, the network-induced delay speed tracking model is developed and is upgraded considering the damping coefficient uncertainties of the IMT powertrain system, which can be described through the norm-bounded uncertainty reduction method. To handle the network-induced delay and parameter uncertainties, a novel and less-conservative Lyapunov function is proposed to design the robust speed tracking controller by the linear matrix inequality (LMI) algorithm. Meanwhile, the estimation error and measurement noise are considered as the external disturbances in the controller design to promote robustness. Finally, the results demonstrate that the proposed controller has the advantages of strong robustness, excellent speed tracking performance, and ride comfort over the current existing controllers. Full article
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17 pages, 3912 KiB  
Article
A Collision Relationship-Based Driving Behavior Decision-Making Method for an Intelligent Land Vehicle at a Disorderly Intersection via DRQN
by Lingli Yu, Shuxin Huo, Keyi Li and Yadong Wei
Sensors 2022, 22(2), 636; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020636 - 14 Jan 2022
Cited by 1 | Viewed by 1446
Abstract
An intelligent land vehicle utilizes onboard sensors to acquire observed states at a disorderly intersection. However, partial observation of the environment occurs due to sensor noise. This causes decision failure easily. A collision relationship-based driving behavior decision-making method via deep recurrent Q network [...] Read more.
An intelligent land vehicle utilizes onboard sensors to acquire observed states at a disorderly intersection. However, partial observation of the environment occurs due to sensor noise. This causes decision failure easily. A collision relationship-based driving behavior decision-making method via deep recurrent Q network (CR-DRQN) is proposed for intelligent land vehicles. First, the collision relationship between the intelligent land vehicle and surrounding vehicles is designed as the input. The collision relationship is extracted from the observed states with the sensor noise. This avoids a CR-DRQN dimension explosion and speeds up the network training. Then, DRQN is utilized to attenuate the impact of the input noise and achieve driving behavior decision-making. Finally, some comparative experiments are conducted to verify the effectiveness of the proposed method. CR-DRQN maintains a high decision success rate at a disorderly intersection with partially observable states. In addition, the proposed method is outstanding in the aspects of safety, the ability of collision risk prediction, and comfort. Full article
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Other

Jump to: Editorial, Research

23 pages, 7885 KiB  
Technical Note
Design and Implementation of HD Mapping, Vehicle Control, and V2I Communication for Robo-Taxi Services
by Jun Yong Yoon, Jinseop Jeong and Woosuk Sung
Sensors 2022, 22(18), 7049; https://0-doi-org.brum.beds.ac.uk/10.3390/s22187049 - 17 Sep 2022
Cited by 4 | Viewed by 1623
Abstract
This paper presents our autonomous driving (AD) software stack, developed to complete the main mission of the contest we entered. The main mission can be simply described as a robo-taxi service on public roads, to transport passengers to their destination autonomously. Among the [...] Read more.
This paper presents our autonomous driving (AD) software stack, developed to complete the main mission of the contest we entered. The main mission can be simply described as a robo-taxi service on public roads, to transport passengers to their destination autonomously. Among the key competencies required for the main mission, this paper focused on high-definition mapping, vehicle control, and vehicle-to-infrastructure (V2I) communication. V2I communication refers to the task of wireless data exchange between a roadside unit and vehicles. With the data being captured and shared, rich, timely, and non-line-of-sight-aware traffic information can be utilized for a wide range of AD applications. In the contest, V2I communication was applied for a robo-taxi service, and also for traffic light recognition. A V2I communication-enabled traffic light recognizer was developed, to achieve a nearly perfect recognition rate, and a robo-taxi service handler was developed, to perform the main mission of the contest. Full article
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