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Special Issue "Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility"

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

Deadline for manuscript submissions: closed (28 February 2018).

Special Issue Editor

Guest Editor
Prof. Dr. Sergio Saponara

Department of Information Engineering (DII), University of Pisa, 56122 Pisa, Italy
Website | E-Mail
Interests: electric/hybrid vehicles; autonomous and connected vehicles; smart energy systems; energy storage systems; predictive diagnostics

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of Sensors entitled Sensors, Wireless Connectivity and Systems for Driver-Assisted/Autonomous Vehicles and Smart Mobility.

As witnessed by the latest editions of Consumer Electronics Show in Las Vegas and Mobile World Congress in Barcelona, consumer electronics is changing the way of designing, producing and driving cars, including the human–vehicle interface (HVI), sensor systems and vehicle-to-everything (V2X) communications. Recent studies on the future of the automotive industry predict that the borders with ICT and the consumer industry will blur, and that vehicles will become consumer-centric. The huge market of 90-million vehicles sold worldwide per year is suited for integrated electronics and MEMS/MOEMS (micro electro/opto-electro mechanical systems) technologies. Indeed, around 80% of all innovations in new vehicles are driven by electronics and sensor technology to implement green and safe vehicles, for sustainable and smart mobility. Value in vehicles is shifting from chassis and powertrain to electronics and sensors, which will cover one-third of a car’s cost in 2025. Lots of sensing and communication components, including wireless devices at radio frequency (RF) or mm-waves, can be used on-board vehicles. However, vehicular electronics require high performance components, operating in harsh environments, and ensuring fault robustness and functional safety. Most devices have been originally developed for consumer applications, and their use for active safety or autonomous driving is not straightforward. The issue for such components is not only their cost, but rather their performance and reliability. Although, for some sensing technologies, e.g., 3D LIDAR for context-aware autonomous/assisted driving, the cost is still a bottleneck.

The particular topics of interest for this Special Issue include, but are not limited to:

- Wireless transceivers based on 4G and future 5G technology for cellular-V2X connectivity
- Wireless transceivers exploiting local area networks (e.g., IEEE 802.11p) for V2X connectivity
- Latency-constrained and robust V2X networking data-link and MAC (medium access control) layer
- Inertial sensor systems (accelerometers and gyro and acquisition/processing electronics) to estimate vehicle dynamics and stability, and to improve navigation satellite systems
- Head-up display projectors and systems
- Advanced HVI with voice-, haptic- or visual-based technologies
- Detection/ranging technologies based on Radar, Lidar and/or array of cameras for context-aware autonomous/assisted driving
- Biometric sensors to monitor the driver’s attention, fatigue or his/her health status
- Algorithms and computing architecture for fusion of sensor and communication data to increase performance and robustness in harsh environments
- Algorithms and architecture for predictive diagnostic on-board vehicles

Most of the above topics are key enabling technologies also within the industry 4.0 scenario. Therefore, synergies can be found between smart vehicles and industry 4.0 application domains.

Prof. Dr. Sergio Saponara
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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

  • Inertial sensor systems
  • Radar, Lidar and imaging sensors
  • Biometric sensors
  • Human–vehicle interface (voice-, visual-, haptic-based)
  • V2X and cellular-V2X wireless transceivers and networks
  • Fault-robustness and functional safety
  • Predictive diagnostic
  • Autonomous vehicles and industry 4.0 applications

Published Papers (13 papers)

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Editorial

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Open AccessEditorial
Sensing and Connection Systems for Assisted and Autonomous Driving and Unmanned Vehicles
Sensors 2018, 18(7), 1999; https://doi.org/10.3390/s18071999
Received: 14 June 2018 / Accepted: 20 June 2018 / Published: 22 June 2018
Cited by 1 | PDF Full-text (181 KB) | HTML Full-text | XML Full-text
Abstract
The special issue, “Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility” on MDPI Sensors presents 12 accepted papers, with authors from North America, Asia, Europe and Australia, related to the emerging trends in sensing and navigation systems (i.e., sensors plus [...] Read more.
The special issue, “Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility” on MDPI Sensors presents 12 accepted papers, with authors from North America, Asia, Europe and Australia, related to the emerging trends in sensing and navigation systems (i.e., sensors plus related signal processing and understanding techniques in multi-agent and cooperating scenarios) for autonomous vehicles, including also unmanned aerial and underwater ones. Full article

Research

Jump to: Editorial

Open AccessArticle
A Cooperative Search and Coverage Algorithm with Controllable Revisit and Connectivity Maintenance for Multiple Unmanned Aerial Vehicles
Sensors 2018, 18(5), 1472; https://doi.org/10.3390/s18051472
Received: 24 March 2018 / Revised: 29 April 2018 / Accepted: 5 May 2018 / Published: 8 May 2018
Cited by 4 | PDF Full-text (9559 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we mainly study a cooperative search and coverage algorithm for a given bounded rectangle region, which contains several unknown stationary targets, by a team of unmanned aerial vehicles (UAVs) with non-ideal sensors and limited communication ranges. Our goal is to [...] Read more.
In this paper, we mainly study a cooperative search and coverage algorithm for a given bounded rectangle region, which contains several unknown stationary targets, by a team of unmanned aerial vehicles (UAVs) with non-ideal sensors and limited communication ranges. Our goal is to minimize the search time, while gathering more information about the environment and finding more targets. For this purpose, a novel cooperative search and coverage algorithm with controllable revisit mechanism is presented. Firstly, as the representation of the environment, the cognitive maps that included the target probability map (TPM), the uncertain map (UM), and the digital pheromone map (DPM) are constituted. We also design a distributed update and fusion scheme for the cognitive map. This update and fusion scheme can guarantee that each one of the cognitive maps converges to the same one, which reflects the targets’ true existence or absence in each cell of the search region. Secondly, we develop a controllable revisit mechanism based on the DPM. This mechanism can concentrate the UAVs to revisit sub-areas that have a large target probability or high uncertainty. Thirdly, in the frame of distributed receding horizon optimizing, a path planning algorithm for the multi-UAVs cooperative search and coverage is designed. In the path planning algorithm, the movement of the UAVs is restricted by the potential fields to meet the requirements of avoiding collision and maintaining connectivity constraints. Moreover, using the minimum spanning tree (MST) topology optimization strategy, we can obtain a tradeoff between the search coverage enhancement and the connectivity maintenance. The feasibility of the proposed algorithm is demonstrated by comparison simulations by way of analyzing the effects of the controllable revisit mechanism and the connectivity maintenance scheme. The Monte Carlo method is employed to validate the influence of the number of UAVs, the sensing radius, the detection and false alarm probabilities, and the communication range on the proposed algorithm. Full article
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Open AccessArticle
Non-Invasive Detection of Respiration and Heart Rate with a Vehicle Seat Sensor
Sensors 2018, 18(5), 1463; https://doi.org/10.3390/s18051463
Received: 20 March 2018 / Revised: 4 May 2018 / Accepted: 5 May 2018 / Published: 8 May 2018
Cited by 5 | PDF Full-text (1696 KB) | HTML Full-text | XML Full-text
Abstract
This study demonstrates the feasibility of using a seat sensor designed for occupant classification from a production passenger vehicle to measure an occupant’s respiration rate (RR) and heart rate (HR) in a laboratory setting. Relaying occupant vital signs after a crash could improve [...] Read more.
This study demonstrates the feasibility of using a seat sensor designed for occupant classification from a production passenger vehicle to measure an occupant’s respiration rate (RR) and heart rate (HR) in a laboratory setting. Relaying occupant vital signs after a crash could improve emergency response by adding a direct measure of the occupant state to an Advanced Automatic Collision Notification (AACN) system. Data was collected from eleven participants with body weights ranging from 42 to 91 kg using a Ford Mustang passenger seat and seat sensor. Using a ballistocardiography (BCG) approach, the data was processed by time domain filtering and frequency domain analysis using the fast Fourier transform to yield RR and HR in a 1-min sliding window. Resting rates over the 30-min data collection and continuous RR and HR signals were compared to laboratory physiological instruments using the Bland-Altman approach. Differences between the seat sensor and reference sensor were within 5 breaths per minute for resting RR and within 15 beats per minute for resting HR. The time series comparisons for RR and HR were promising with the frequency analysis technique outperforming the peak detection technique. However, future work is necessary for more accurate and reliable real-time monitoring of RR and HR outside the laboratory setting. Full article
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Open AccessArticle
Verifying Safety Messages Using Relative-Time and Zone Priority in Vehicular Ad Hoc Networks
Sensors 2018, 18(4), 1195; https://doi.org/10.3390/s18041195
Received: 28 February 2018 / Revised: 2 April 2018 / Accepted: 10 April 2018 / Published: 13 April 2018
Cited by 6 | PDF Full-text (6174 KB) | HTML Full-text | XML Full-text
Abstract
In high-density road networks, with each vehicle broadcasting multiple messages per second, the arrival rate of safety messages can easily exceed the rate at which digital signatures can be verified. Since not all messages can be verified, algorithms for selecting which messages to [...] Read more.
In high-density road networks, with each vehicle broadcasting multiple messages per second, the arrival rate of safety messages can easily exceed the rate at which digital signatures can be verified. Since not all messages can be verified, algorithms for selecting which messages to verify are required to ensure that each vehicle receives appropriate awareness about neighbouring vehicles. This paper presents a novel scheme to select important safety messages for verification in vehicular ad hoc networks (VANETs). The proposed scheme uses location and direction of the sender, as well as proximity and relative-time between vehicles, to reduce the number of irrelevant messages verified (i.e., messages from vehicles that are unlikely to cause an accident). Compared with other existing schemes, the analysis results show that the proposed scheme can verify messages from nearby vehicles with lower inter-message delay and reduced packet loss and thus provides high level of awareness of the nearby vehicles. Full article
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Open AccessArticle
Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays
Sensors 2018, 18(4), 1044; https://doi.org/10.3390/s18041044
Received: 31 January 2018 / Revised: 25 March 2018 / Accepted: 27 March 2018 / Published: 30 March 2018
Cited by 4 | PDF Full-text (22999 KB) | HTML Full-text | XML Full-text
Abstract
To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For [...] Read more.
To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region. Full article
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Open AccessArticle
Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication
Sensors 2018, 18(2), 662; https://doi.org/10.3390/s18020662
Received: 22 January 2018 / Revised: 16 February 2018 / Accepted: 20 February 2018 / Published: 23 February 2018
Cited by 9 | PDF Full-text (5120 KB) | HTML Full-text | XML Full-text
Abstract
Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV [...] Read more.
Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV sensor networks. Distributed leader-follower formation controllers are designed based on a state feedback and consensus algorithm. Considering that each vehicle is subject to model uncertainties and current disturbances, a second-order integral UUV model with a nonlinear function is established using the state feedback linearized method under current disturbances. For unstable communication among UUVs, communication failure and acoustic link noise interference are considered. Two-layer random switching communication topologies are proposed to solve the problem of communication failure. For acoustic link noise interference, accurate representation of valid communication information and noise stripping when designing controllers is necessary. Effective communication topology weights are designed to represent the validity of communication information interfered by noise. Utilizing state feedback and noise stripping, sufficient conditions for design formation controllers are proposed to ensure UUV formation achieves consensus under model uncertainties, current disturbances, and unstable communication. The stability of formation controllers is proven by the Lyapunov-Razumikhin theorem, and the validity is verified by simulation results. Full article
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Open AccessArticle
VEHIOT: Design and Evaluation of an IoT Architecture Based on Low-Cost Devices to Be Embedded in Production Vehicles
Sensors 2018, 18(2), 486; https://doi.org/10.3390/s18020486
Received: 24 December 2017 / Revised: 29 January 2018 / Accepted: 30 January 2018 / Published: 6 February 2018
Cited by 6 | PDF Full-text (12206 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from [...] Read more.
Nowadays, the current vehicles are incorporating control systems in order to improve their stability and handling. These control systems need to know the vehicle dynamics through the variables (lateral acceleration, roll rate, roll angle, sideslip angle, etc.) that are obtained or estimated from sensors. For this goal, it is necessary to mount on vehicles not only low-cost sensors, but also low-cost embedded systems, which allow acquiring data from sensors and executing the developed algorithms to estimate and to control with novel higher speed computing. All these devices have to be integrated in an adequate architecture with enough performance in terms of accuracy, reliability and processing time. In this article, an architecture to carry out the estimation and control of vehicle dynamics has been developed. This architecture was designed considering the basic principles of IoT and integrates low-cost sensors and embedded hardware for orchestrating the experiments. A comparison of two different low-cost systems in terms of accuracy, acquisition time and reliability has been done. Both devices have been compared with the VBOX device from Racelogic, which has been used as the ground truth. The comparison has been made from tests carried out in a real vehicle. The lateral acceleration and roll rate have been analyzed in order to quantify the error of these devices. Full article
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Open AccessArticle
Autonomous Shepherding Behaviors of Multiple Target Steering Robots
Sensors 2017, 17(12), 2729; https://doi.org/10.3390/s17122729
Received: 14 August 2017 / Revised: 20 November 2017 / Accepted: 21 November 2017 / Published: 25 November 2017
Cited by 7 | PDF Full-text (710 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another [...] Read more.
This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach. Full article
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Open AccessArticle
A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles
Sensors 2017, 17(12), 2709; https://doi.org/10.3390/s17122709
Received: 10 October 2017 / Revised: 20 November 2017 / Accepted: 20 November 2017 / Published: 23 November 2017
Cited by 3 | PDF Full-text (3005 KB) | HTML Full-text | XML Full-text
Abstract
Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS [...] Read more.
Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately. Full article
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Open AccessArticle
Visual Localization across Seasons Using Sequence Matching Based on Multi-Feature Combination
Sensors 2017, 17(11), 2442; https://doi.org/10.3390/s17112442
Received: 29 August 2017 / Revised: 18 October 2017 / Accepted: 19 October 2017 / Published: 25 October 2017
Cited by 5 | PDF Full-text (10709 KB) | HTML Full-text | XML Full-text
Abstract
Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS). However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is [...] Read more.
Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS). However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period). In this method, in order to improve matching accuracy, multi-feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center-symmetric local binary patterns) to represent image sequence. Then, similarity measurement according to Chi-square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision–recall performance against the state-of-the-art SeqSLAM algorithm. Full article
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Open AccessArticle
Event-Based Sensing and Control for Remote Robot Guidance: An Experimental Case
Sensors 2017, 17(9), 2034; https://doi.org/10.3390/s17092034
Received: 31 July 2017 / Revised: 24 August 2017 / Accepted: 4 September 2017 / Published: 6 September 2017
Cited by 11 | PDF Full-text (2013 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient [...] Read more.
This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient use of communications and reduce sensor activity. Measurement requests are dictated by an event-based state estimator by setting an upper bound to the estimation error covariance matrix. The rest of the time, state prediction is carried out with the Unscented transformation. This prediction method makes it possible to select the appropriate instants at which to perform actuations on the robot so that guidance performance does not degrade below a certain threshold. Ultimately, we obtained a combined event-based control and estimation solution that drastically reduces communication accesses. The magnitude of this reduction is set according to the tracking error margin of a P3-DX robot following a nonlinear trajectory, remotely controlled with a mini PC and whose pose is detected by a camera sensor. Full article
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Open AccessArticle
Basic Simulation Environment for Highly Customized Connected and Autonomous Vehicle Kinematic Scenarios
Sensors 2017, 17(9), 1938; https://doi.org/10.3390/s17091938
Received: 20 July 2017 / Revised: 19 August 2017 / Accepted: 20 August 2017 / Published: 23 August 2017
Cited by 4 | PDF Full-text (7341 KB) | HTML Full-text | XML Full-text
Abstract
To enhance the reality of Connected and Autonomous Vehicles (CAVs) kinematic simulation scenarios and to guarantee the accuracy and reliability of the verification, a four-layer CAVs kinematic simulation framework, which is composed with road network layer, vehicle operating layer, uncertainties modelling layer and [...] Read more.
To enhance the reality of Connected and Autonomous Vehicles (CAVs) kinematic simulation scenarios and to guarantee the accuracy and reliability of the verification, a four-layer CAVs kinematic simulation framework, which is composed with road network layer, vehicle operating layer, uncertainties modelling layer and demonstrating layer, is proposed in this paper. Properties of the intersections are defined to describe the road network. A target position based vehicle position updating method is designed to simulate such vehicle behaviors as lane changing and turning. Vehicle kinematic models are implemented to maintain the status of the vehicles when they are moving towards the target position. Priorities for individual vehicle control are authorized for different layers. Operation mechanisms of CAVs uncertainties, which are defined as position error and communication delay in this paper, are implemented in the simulation to enhance the reality of the simulation. A simulation platform is developed based on the proposed methodology. A comparison of simulated and theoretical vehicle delay has been analyzed to prove the validity and the creditability of the platform. The scenario of rear-end collision avoidance is conducted to verify the uncertainties operating mechanisms, and a slot-based intersections (SIs) control strategy is realized and verified in the simulation platform to show the supports of the platform to CAVs kinematic simulation and verification. Full article
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Open AccessArticle
Graph-Based Cooperative Localization Using Symmetric Measurement Equations
Sensors 2017, 17(6), 1422; https://doi.org/10.3390/s17061422
Received: 28 April 2017 / Revised: 13 June 2017 / Accepted: 13 June 2017 / Published: 17 June 2017
Cited by 5 | PDF Full-text (1501 KB) | HTML Full-text | XML Full-text
Abstract
Precise localization is a key requirement for the success of highly assisted or autonomous vehicles. The diminishing cost of hardware has resulted in a proliferation of the number of sensors in the environment. Cooperative localization (CL) presents itself as a feasible and effective [...] Read more.
Precise localization is a key requirement for the success of highly assisted or autonomous vehicles. The diminishing cost of hardware has resulted in a proliferation of the number of sensors in the environment. Cooperative localization (CL) presents itself as a feasible and effective solution for localizing the ego-vehicle and its neighboring vehicles. However, one of the major challenges to fully realize the effective use of infrastructure sensors for jointly estimating the state of a vehicle in cooperative vehicle-infrastructure localization is an effective data association. In this paper, we propose a method which implements symmetric measurement equations within factor graphs in order to overcome the data association challenge with a reduced bandwidth overhead. Simulated results demonstrate the benefits of the proposed approach in comparison with our previously proposed approach of topology factors. Full article
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