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Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (20 April 2019) | Viewed by 55243

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Special Issue Editors

Prof. Dr. Stratis Kanarachos

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Guest Editor

1. School of Mechanical, Aerospace and Automotive Engineering, Faculty of Engineering, Environment and Computing, Coventry University, Coventry CV1 5FB, UK
2. Head of School of Engineering, Coventry University Egypt branch
Interests: motion control; active dynamics and self-learning systems; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Dr. Valentin Ivanov

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Guest Editor

Automotive Engineering Group, Technische Universität Ilmenau, 98693 Ilmenau, Germany
Interests: vehicle dynamics; automotive control systems; electric vehicles; automated vehicles; chassis design; alternative powertrains; vehicle testing; motion control
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Alessandro Corrêa Victorino

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Departamento de Engenharia Mecânica Escola de Engenharia - bloco 1 - sala 3644 Universidade Federal de Minas Gerais, Av Antonio Carlos 6627, Brazil
Interests: Gerais (UFMG). intelligent and robotic vehicles; autonomous navigation and driver assistance systems; integrating advanced control techniques; fusion of sensor data; observers of dynamic states; embedded perception of the environment

Dr. David Ward

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Guest Editor

Head of Functional Safety, HORIBA MIRA Ltd., Watling Street, Nuneaton, Warwickshire CV10 0TU, UK
Interests: vehicle functional safety

Special Issue Information

Dear Colleagues,

This Special Issue seeks articles related to recent advances and future challenges in “Multi-Actuated Ground Vehicles”. Its scope will include the following topics:

X by wire systems (vehicle electrification)
Integrated vehicle controllers
Active safety
Functional Safety
Energy efficiency and energy recuperation
Shared vehicle control
Highly Automated and Fully Automated Driving
Testing, validation and Verification
Simulation In the Loop and Hardware In the Loop

Dr. Stratis Kanarachos
Prof. Dr. Valentin Ivanov
Prof. Dr. Alessandro Corrêa Victorino
Dr. David Ward
Guest Editors

Manuscript Submission Information

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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. Applied Sciences 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 2400 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

multi-actuated
ground vehicles
electrification
integrated control
functional safety

Published Papers (13 papers)

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Research

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18 pages, 8711 KiB

Open AccessArticle

A New Path Tracking Method Based on Multilayer Model Predictive Control

by Guoxing Bai, Yu Meng, Li Liu, Weidong Luo, Qing Gu and Kailun Li

Appl. Sci. 2019, 9(13), 2649; https://doi.org/10.3390/app9132649 - 29 Jun 2019

Cited by 37 | Viewed by 3034

Abstract

At present, many path tracking controllers are unable to actively adjust the longitudinal velocity according to path information, such as the radius of the curve, to further improve tracking accuracy. For this problem, we propose a new path tracking framework based on model predictive control (MPC). This is a multilayer control system that includes three path tracking controllers with fixed velocities and a velocity decision controller. This new control method is named multilayer MPC. This new control method is compared to other control methods through simulation. In this paper, the maximum values of the displacement error and the heading error of multilayer MPC are 92.92% and 77.02%, respectively, smaller than those of nonlinear MPC. The real-time performance of multilayer MPC is very good, and parallel computation can further improve the real-time performance of this control method. In simulation results, the calculation time of multilayer MPC in each control period does not exceed 0.0130 s, which is much smaller than the control period. In addition, when the error of positioning systems is at the centimeter level, the performance of multilayer MPC is still good. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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22 pages, 18689 KiB

Open AccessArticle

A Novel Emergency Braking Control Strategy for Dual-Motor Electric Drive Tracked Vehicles Based on Regenerative Braking

by Zhaomeng Chen, Xiaojun Zhou, Zhe Wang, Yaoheng Li and Bo Hu

Appl. Sci. 2019, 9(12), 2480; https://doi.org/10.3390/app9122480 - 18 Jun 2019

Cited by 11 | Viewed by 3847

Abstract

Dual-motor electric drive tracked vehicles (DDTVs) have drawn much attention in the trends of hybridization and electrification for tracked vehicles. Their transmission chains differ significantly from the traditional ones. Due to the complication and slug of a traditional tracked vehicle braking system, as well as the difference of track-ground with tire-road, research of antilock braking control of tracked vehicles is rather lacking. With the application of permanent magnet synchronous motors (PMSMs), applying an advanced braking control strategy becomes practical. This paper develops a novel emergency braking control strategy using a sliding mode slip ratio controller and a rule-based braking torque allocating method. Simulations are conducted under various track-ground conditions for comparing the control performance of the proposed strategy with three other strategies including the full braking strategy, traditional antilock braking strategy, as well as sliding mode slip ratio strategy without the use of motors. For an initial speed of 80 km/h, simulation results show that the proposed control strategy performs the best among all strategies mentioned above. Several hardware-in-the-loop (HIL) experiments are conducted under the same track-ground conditions as the ones in the simulations. The experiment results verified the validity of the proposed emergency braking control strategy. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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15 pages, 5548 KiB

Open AccessArticle

Real-Time Control Strategy for CVT-Based Hybrid Electric Vehicles Considering Drivability Constraints

by Hangyang Li, Yunshan Zhou, Huanjian Xiong, Bing Fu and Zhiliang Huang

Appl. Sci. 2019, 9(10), 2074; https://doi.org/10.3390/app9102074 - 20 May 2019

Cited by 18 | Viewed by 2484

Abstract

The energy management strategy has a great influence on the fuel economy of hybrid electric vehicles, and the equivalent consumption minimization strategy (ECMS) has proved to be a useful tool for the real-time optimal control of Hybrid Electric Vehicles (HEVs). However, the adaptation of the equivalent factor poses a major challenge in order to obtain optimal fuel consumption as well as robustness to varying driving cycles. In this paper, an adaptive-ECMS based on driving pattern recognition (DPR) is established for hybrid electric vehicles with continuously variable transmission. The learning vector quantization (LVQ) neural network model was adopted for the on-line DPR algorithm. The influence of the battery state of charge (SOC) on the optimal equivalent factor was studied under different driving patterns. On this basis, a method of adaptation of the equivalent factor was proposed by considering the type of driving pattern and the battery SOC. Besides that, in order to enhance drivability, penalty terms were introduced to constrain frequent engine on/off events and large variations of the continuously variable transmission (CVT) speed ratio. Simulation results showed that the proposed method efficiently improved the equivalent fuel consumption with charge-sustaining operations and also took into account driving comfort. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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15 pages, 2903 KiB

Open AccessArticle

Path Tracking of Mining Vehicles Based on Nonlinear Model Predictive Control

by Guoxing Bai, Li Liu, Yu Meng, Weidong Luo, Qing Gu and Baoquan Ma

Appl. Sci. 2019, 9(7), 1372; https://doi.org/10.3390/app9071372 - 01 Apr 2019

Cited by 47 | Viewed by 4463

Abstract

Path tracking of mining vehicles plays a significant role in reducing the working time of operators in the underground environment. Because the existing path tracking control of mining vehicles, based on model predictive control, is not very effective when the longitudinal velocity of the vehicle is above 2 m/s, we have devised a new controller based on nonlinear model predictive control. Then, we compare this new controller with the existing model predictive controller. In the results of our simulation, the tracking accuracy of our controller at the longitudinal velocity of 4 m/s is close to that of the existing model predictive controller, at the longitudinal velocity of 2 m/s. When longitudinal velocity is 4 m/s, the existing model predictive controller cannot drive the mining vehicle to track the given path, but our nonlinear model predictive controller can, and the maximum displacement error and heading error are 0.1382 m and 0.0589 rad, respectively. According to these results, we believe that this nonlinear model predictive controller can be used to improve the performance of the path tracking of mining vehicles. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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27 pages, 10388 KiB

Open AccessArticle

Direct Yaw Moment Control for Enhancing Handling Quality of Lightweight Electric Vehicles with Large Load-To-Curb Weight Ratio

by Pongsathorn Raksincharoensak, Sato Daisuke and Mathias Lidberg

Appl. Sci. 2019, 9(6), 1151; https://doi.org/10.3390/app9061151 - 19 Mar 2019

Cited by 12 | Viewed by 6288

Abstract

In this paper a vehicle dynamics control system is designed to compensate the change in vehicle handling dynamics of lightweight vehicles due to variation in loading conditions and the effectiveness of the proposed design is verified by simulations and an experimental study using a fixed-base driving simulator. Considering the electrification of future mobility, the target vehicle of this research is a lightweight vehicle equipped with in-wheel motors that can generate an additional direct yaw moment by transverse distribution of traction forces to control vehicle yawing as well as side slip motions. Previously, the change in vehicle handling dynamics for various loading conditions have been analyzed by using a linear two-wheel vehicle model in planar motion and a control law of the DYC system based on feed-forward of front steering angular velocity and feedback of vehicle yaw rate. The feed-forward controller is derived based on the model following control with approximation of the vehicle dynamics to 1st-order transfer function. To make the determination of the yaw rate feedback gain model-based and adaptable to various vehicle velocity conditions, this paper selects a method where the yaw rate feedback gain in the DYC system is determined in a way that the steady-state yaw rate gain of the controlled loaded vehicle matches the gain of the unloaded vehicle. The DYC system is simulated in a single lane change maneuver to confirm the improved responsiveness of the vehicle while simulations of a double-lane change maneuver with a driver steering model confirms the effectiveness of the DYC system to support tracking control. Finally, the effectiveness of the proposed DYC system is also verified in an experimental study with ten human drivers using a fix-based driving simulator. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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18 pages, 6971 KiB

Open AccessArticle

Approach of Coordinated Control Method for Over-Actuated Vehicle Platoon based on Reference Vector Field

by Yang Liu, Dong Zhang, Timothy Gordon, Guiyuan Li and Changfu Zong

Appl. Sci. 2019, 9(2), 297; https://doi.org/10.3390/app9020297 - 15 Jan 2019

Cited by 5 | Viewed by 2514

Abstract

Collaborative vehicle platoon control with full drive-by-wire vehicles with four-wheel independent driving and steering (FWIDSV) has attracted broader research interests. However, the problem of cooperative vehicle platoon control in two-dimensional driving scenes remains to be solved. This paper proposes a coupling control method for path tracking and spacing-maintaining based on the reference vector field (RVF). An integrated hierarchical control structure, including the following control layer, tire force allocator layer, and an actuator controlling layer for FWIDSV is presented. Inside, the next control layer was designed according to the spacing control strategy and RVF within the limitation of the friction circle. For verifying the effectiveness of this control method, sufficient conditions for error convergence are analyzed when considering the influence of the critical parameters on the particle dynamics model. The tire force allocator layer is designed based on linear quadratic programming (LQP), which is used to distribute the total forces and yaw moment. The sliding mode control (SMC) is employed to track the desired tire forces in the actuator controlling layer. The proposed control methods are validated through simulation in intelligent cruise control (ICC) and platoon merging scenarios. The results demonstrate an effective FWIDSV platoon control approach that is based on the RVF in the 2-D driving scenes. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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16 pages, 2915 KiB

Open AccessArticle

Active Fault-Tolerant Control Based on Multiple Input Multiple Output-Model Free Adaptive Control for Four Wheel Independently Driven Electric Vehicle Drive System

by Yugong Luo, Yun Hu, Fachao Jiang, Rui Chen and Yongsheng Wang

Appl. Sci. 2019, 9(2), 276; https://doi.org/10.3390/app9020276 - 14 Jan 2019

Cited by 10 | Viewed by 3273

Abstract

To solve the problems with the existing active fault-tolerant control system, which does not consider the cooperative control of the drive system and steering system or accurately relies on the vehicle model when one or more motors fail, a multi-input and multi-output model-free adaptive active fault-tolerant control method for four-wheel independently driven electric vehicles is proposed. The method, which only uses the input/output data of the vehicle in the control system design, is based on a new dynamic linearization technique with a pseudo-partial derivative, aimed at solving the complex and nonlinear issues of the vehicle model. The desired control objectives can be achieved by the coordinated adaptive fault-tolerant control of the drive and steering systems under different failure conditions of the drive system. The error convergence and input-output boundedness of the control system are proven by means of stability analysis. Finally, simulations and further experiments are carried out to validate the effectiveness and real-time response of the fault-tolerant system in different driving scenarios. The results demonstrate that our proposed approach can maintain the longitudinal speed error (within 3%) and lateral stability, thereby improving the safety of the vehicles. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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13 pages, 760 KiB

Open AccessArticle

Deep Learning Applied to Scenario Classification for Lane-Keep-Assist Systems

by Halil Beglerovic, Thomas Schloemicher, Steffen Metzner and Martin Horn

Appl. Sci. 2018, 8(12), 2590; https://doi.org/10.3390/app8122590 - 12 Dec 2018

Cited by 17 | Viewed by 4566

Abstract

Test, verification, and development activities of vehicles with ADAS (Advanced Driver Assistance Systems) and ADF (Automated Driving Functions) generate large amounts of measurement data. To efficiently evaluate and use this data, a generic understanding and classification of the relevant driving scenarios is necessary. Currently, such understanding is obtained by using heuristic algorithms or even by manual inspection of sensor signals. In this paper, we apply deep learning on sensor time series data to automatically extract relevant features for classification of driving scenarios relevant for a Lane-Keep-Assist System. We compare the performance of convolutional and recurrent neural networks and propose two classification models. The first one is an online model for scenario classification during driving. The second one is an offline model for post-processing, providing higher accuracy. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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13 pages, 6621 KiB

Open AccessArticle

Effect of Seat Condition on Abdominal Injuries to Vehicle Occupants in Frontal Impact Accidents

by Yasuhiro Matsui and Shoko Oikawa

Appl. Sci. 2018, 8(11), 2047; https://doi.org/10.3390/app8112047 - 25 Oct 2018

Cited by 2 | Viewed by 2607

Abstract

Vehicle occupants were killed in 33% of all traffic accidents in Japan in 2017. Of the vehicles in vehicle-to-vehicle accidents, 54% were impacted from the front. In frontal impact accidents, when the lap belt moves away from the iliac crests of the pelvis of a vehicle occupant, the belt moves directly into the abdomen. Here, we investigated causes of abdominal injuries to vehicle occupants, because the abdomen is associated with the highest rates of severe injury and fatality. The purpose of this study was to clarify the correlation between downward movement of the seat and of the lap belt away from the iliac crests of a human occupant of a car, in the event of a frontal impact. We investigated this phenomenon by conducting simulations using an anthropomorphic 50th percentile male (AM50) human model wearing a three-point seatbelt. We set two deformable seat conditions: Vertical movement and lean forward movement. Our results revealed that the lap belt came off from both of the iliac crests during lean forward movement but only from one of the iliac crests during vertical movement. We concluded that abdominal injuries can be caused by downward movement together with forward rotation in the seat during vehicle-to-vehicle frontal impacts. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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29 pages, 13918 KiB

Open AccessArticle

Service-Oriented Cooperation Policies for Intelligent Ground Vehicles Approaching Intersections

by Kailong Zhang, Ce Xie, Yujia Wang, Min Wang, Arnaud De La Fortelle, Weibin Zhang and Zongtao Duan

Appl. Sci. 2018, 8(9), 1647; https://doi.org/10.3390/app8091647 - 13 Sep 2018

Cited by 6 | Viewed by 3038

Abstract

With the coming of intelligent vehicles and vehicular communication, Intelligent Transportation Systems (ITS) of connected vehicles are emerging and now evolving to Cooperative-ITS (C-ITS), as service platforms for smart cities. Considering new service properties, the autonomous cooperation of such vehicles has exhibited novel QoS features that imply new requirements: guaranteeing the traffic efficiency of any emergent vehicle while trying to promote the throughput at an intersection. So, after analyzing the classic reservation-based cooperation mechanisms, new QoS-oriented cooperation methods and policies are studied in this work. Concretely, several models of related traffic objects we have proposed are firstly introduced briefly. Then, the scheduling policies of vehicles approaching an intersection have been presented, including three existing policies (FAFP-SV, FAFP-SQ, and HQEP-SV) and five new polices (FAFP-SQ-SV, FAFP-MQ, HWFP-SQ, HWFP-SQ-SV, HWFP-MQ). These policies combine two major factors: vehicular priority for scheduling and concurrency in traffics. The first one includes the vehicular arrival-time, priority mapped to QoS, and the weight of reserved vehicles on a lane etc. In addition, the second refers to schedule a platoon rather than single vehicle each time, or platoons on different lanes instead of one platoon on only one lane. All these policies have been implemented, and further, verified within the parameter-configurable traffic simulator QoS-CITS (v2.1) we designed and developed with C#. Abundant experiments have been conducted with configured typical traffic scenes, and experimental results show that HWFP-SQ-SV and HWFP-MQ can guarantee both the QoS of emergent vehicles and traffic throughput better than other six policies. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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21 pages, 3872 KiB

Open AccessArticle

Design and Experimental Validation of a Cooperative Adaptive Cruise Control System Based on Supervised Reinforcement Learning

by Shouyang Wei, Yuan Zou, Tao Zhang, Xudong Zhang and Wenwei Wang

Appl. Sci. 2018, 8(7), 1014; https://doi.org/10.3390/app8071014 - 21 Jun 2018

Cited by 28 | Viewed by 4955

Abstract

This paper presents a supervised reinforcement learning (SRL)-based framework for longitudinal vehicle dynamics control of cooperative adaptive cruise control (CACC) system. A supervisor network trained by real driving data is incorporated into the actor-critic reinforcement learning approach. In the SRL training process, the actor and critic network are updated under the guidance of the supervisor and the gain scheduler. As a result, the training success rate is improved, and the driver characteristics can be learned by the actor to achieve a human-like CACC controller. The SRL-based control policy is compared with a linear controller in typical driving situations through simulation, and the control policies trained by drivers with different driving styles are compared using a real driving cycle. Furthermore, the proposed control strategy is demonstrated by a real vehicle-following experiment with different time headways. The simulation and experimental results not only validate the effectiveness and adaptability of the SRL-based CACC system, but also show that it can provide natural following performance like human driving. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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16 pages, 2196 KiB

Open AccessArticle

Model Predictive Stabilization Control of High-Speed Autonomous Ground Vehicles Considering the Effect of Road Topography

by Kai Liu, Jianwei Gong, Shuping Chen, Yu Zhang and Huiyan Chen

Appl. Sci. 2018, 8(5), 822; https://doi.org/10.3390/app8050822 - 19 May 2018

Cited by 36 | Viewed by 4676

Abstract

This paper presents a model predictive control (MPC) scheme for the stabilization of high-speed autonomous ground vehicles (AGVs) considering the effect of road topography. Accounting for the road curvature and bank angle, a single-track dynamic model with roll dynamics is derived. Variable time steps are utilized for vehicle model discretization, enabling collision avoidance in the long-term without compromising the prediction accuracy in the near-term. Accordingly, safe driving constraints including the sideslip envelope, zero-moment-point and lateral safety corridor are developed to handle stability and obstacle avoidance. Taking these constraints into account, an MPC problem is formulated and solved at each step to determine the optimal steering control commands. Moreover, feedback corrections are integrated into the MPC to compensate the unmodeled dynamics and parameter uncertainties. Comparative simulations validate the capability and real-time ability of the proposed control scheme. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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Review

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38 pages, 4851 KiB

Open AccessFeature PaperReview

Pedestrian and Cyclist Detection and Intent Estimation for Autonomous Vehicles: A Survey

by Sarfraz Ahmed, M. Nazmul Huda, Sujan Rajbhandari, Chitta Saha, Mark Elshaw and Stratis Kanarachos

Appl. Sci. 2019, 9(11), 2335; https://doi.org/10.3390/app9112335 - 06 Jun 2019

Cited by 52 | Viewed by 8681

Abstract

As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection and intent estimation to increase the safety of autonomous vehicles, for both the driver and other road users. Understanding the intentions of the pedestrian/cyclist enables the self-driving vehicle to take actions to avoid incidents. To make this possible, development of methods/techniques, such as deep learning (DL), for the autonomous vehicle will be explored. For example, the development of pedestrian detection has been significantly advanced using DL approaches, such as; Fast Region-Convolutional Neural Network (R-CNN) , Faster R-CNN and Single Shot Detector (SSD). Although DL has been around for several decades, the hardware to realise the techniques have only recently become viable. Using these DL methods for pedestrian and cyclist detection and applying it for the tracking, motion modelling and pose estimation can allow for a successful and accurate method of intent estimation for the vulnerable road users. Although there has been a growth in research surrounding the study of pedestrian detection using vision-based approaches, further attention should include focus on cyclist detection. To further improve safety for these vulnerable road users (VRUs), approaches such as sensor fusion and intent estimation should be investigated. Full article

(This article belongs to the Special Issue Multi-Actuated Ground Vehicles: Recent Advances and Future Challenges)

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