A Novel Dynamic Measurement System for Evaluating the Braking Coordination of Articulated Vehicles

The braking coordination between tractor and semitrailer is vital to the safety of articulated vehicles. Traditional evaluation about braking coordination is based on the pressure measurement along air braking pipeline, which needs to change original braking structure to install gauges and cannot directly reflect the final braking coordination of different wheels. To overcome these limitations, this paper proposes a novel dynamic measurement system for evaluating the braking coordination of articulated vehicles. During the brake test, all wheel velocities of the whole articulated vehicle are synchronously obtained through a specially designed distributed acquisition platform. To effectively eliminate gross errors and noises in wheel angular velocity data, a 3-order autoregressive (AR) model and an improved-thresholding wavelet filtering algorithm are developed. Further, a novel direct evaluation method about braking coordination is proposed according to the differences in angular velocity dropping time of all wheels. Finally, the overall system is assessed through real field tests. The results validate the feasibility and effectiveness of the proposed system

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact

Recent trends in vehicle engineering are testament to the great efforts that scientists and industries have made to seek solutions to enhance both the performance and safety of vehicular systems. This Special Issue aims to contribute to the study of modern vehicle dynamics, attracting recent experimental and in-simulation advances that are the basis for current technological growth and future mobility. The area involves research, studies, and projects derived from vehicle dynamics that aim to enhance vehicle performance in terms of handling, comfort, and adherence, and to examine safety optimization in the emerging contexts of smart, connected, and autonomous driving.This Special Issue focuses on new findings in the following topics:(1) Experimental and modelling activities that aim to investigate interaction phenomena from the macroscale, analyzing vehicle data, to the microscale, accounting for local contact mechanics; (2) Control strategies focused on vehicle performance enhancement, in terms of handling/grip, comfort and safety for passengers, motorsports, and future mobility scenarios; (3) Innovative technologies to improve the safety and performance of the vehicle and its subsystems; (4) Identification of vehicle and tire/wheel model parameters and status with innovative methodologies and algorithms; (5) Implementation of real-time software, logics, and models in onboard architectures and driving simulators; (6) Studies and analyses oriented toward the correlation among the factors affecting vehicle performance and safety; (7) Application use cases in road and off-road vehicles, e-bikes, motorcycles, buses, trucks, etc

Enhancing roll stability and directional performance of articulated heavy vehicles based on anti-roll control and design optimization.

This research presents an investigation to actively improve the rollover stability of articulated heavy vehicles (AHVs) during high speed manoeuvres using anti-roll control systems. A 3-dimensional (3-D) linear yaw/roll model with 5 degrees of freedom is developed. Based on this model a linear quadratic regulator (LQR) controller is designed to improve the rollover stability of a tractor/semi-trailer combination. A design optimization method for AHVs using genetic algorithms (GAs) and multibody vehicle system models is also presented. AHVs have poor manoeuvrability when travelling at low speeds on local roads and city streets. On the other hand, these vehicles exhibit unstable motion modes at high speeds, including jack-knifing, trailer sway and rollover. From the design point of view, the low-speed manoeuvrability and high-speed stability have conflicting requirements on some design variables. The design method based on a GA and a multibody vehicle dynamic package, TruckSim, is proposed to coordinate this trade-off relationship. To test the effectiveness of the design method, a tractor/semi-trailer combination is optimized using the proposed method. It is demonstrated that the proposed design method can be used for identifying desired design variables and predict performance envelopes in the early design stages of AHVs

On Robust Steering Based Lateral Control of Longer and Heavier Commercial Vehicles

Rapid growth in the transportation of goods has led to raised concerns aboutenvironmental effects, road freight traffic, and increased infrastructure usage.The increasing cost of fuel, and issues with congestions and gas emissions,make longer and heavier commercial vehicles (LHCVs) an attractive alter-native to conventional heavy vehicles. However, one major issue concerningLHCVs is their potential impact on traffic safety. A typically dangerous be-haviour happens during evasive steering maneuvers, which causes amplifiedlateral motions in the towed units. These amplified motions can lead to thetowed units’ oscillation, large offtracking and, in a worst case scenario, causerollover.The main objective of this thesis is to develop robust steering-based con-trollers for improving the lateral performance of LHCVs at high speeds bysuppressing unwanted amplified motions in the towed units. Robust controlmethods aim to achieve an adequate level of robustness against model un-certainties and disturbances, while at the same time satisfying the desiredclosed-loop system performance specifications. The proposed robust controlsyntheses are formulated based on an H ∞ static output-feedback (SOFB)in which only one easily measurable state variable is required. The controlsynthesis problems are solved by using linear matrix inequality (LMI) op-timizations. As the measurement of the driver steering input is available,a combined version of SOFB and dynamic feed-forward (DFF) is also de-veloped and several techniques for designing DFF are proposed. The theo-retical contributions of this research mainly lie in the derivation of a novelLMI conditions for integral quadratic constraints on the states and also inthe derivation of a set of new LMI conditions for the DFF design method.From a practical point of view, the proposed controllers are simple and easyto implement, despite their theoretical complexity.The effectiveness of the designed controllers is verified through numericalsimulations performed on linear vehicle models as well as high-fidelity ve-hicle models. The verification results confirm a significant reduction in yawrate rearward amplification, lateral acceleration rearward amplification andhigh-speed transient off-tracking, thereby improving the lateral stability andperformance of the studied LHCVs

Advances in Mechanical Systems Dynamics 2020

The fundamentals of mechanical system dynamics were established before the beginning of the industrial era. The 18th century was a very important time for science and was characterized by the development of classical mechanics. This development progressed in the 19th century, and new, important applications related to industrialization were found and studied. The development of computers in the 20th century revolutionized mechanical system dynamics owing to the development of numerical simulation. We are now in the presence of the fourth industrial revolution. Mechanical systems are increasingly integrated with electrical, fluidic, and electronic systems, and the industrial environment has become characterized by the cyber-physical systems of industry 4.0. Within this framework, the status-of-the-art has become represented by integrated mechanical systems and supported by accurate dynamic models able to predict their dynamic behavior. Therefore, mechanical systems dynamics will play a central role in forthcoming years. This Special Issue aims to disseminate the latest research findings and ideas in the field of mechanical systems dynamics, with particular emphasis on novel trends and applications

Investigation of integrated control of articulated heavy vehicle using scaled multi-body dynamic model

Heavy vehicle handling control systems have proven to be an efficient way of reducing road accidents and improving road traffic safety. Testing these control systems on heavy vehicles can be expensive and unsafe. Meanwhile, the scaled model has proven a secure and inexpensive way of designing and deploying vehicle dynamics control. However, the scaled model's mathematical modelling has been mainly limited to the bicycle model, reducing the scope of exploring the handling dynamics. This study presents an innovative way of modelling a scaled tractor semi-trailer using multi-body dynamics software and testing control systems through co-simulation to help develop new control systems safely and inexpensively for improving road traffic safety. In this research, modelling the scaled model of an articulated vehicle was simulated on MSC ADAMS/View, which extends the mathematical model to 168 degrees of freedom. A 1/14 physical model was used to validate the simulation model and co-simulation has been established between MSC ADAMS/View and MATLAB to investigate the control of a scaled model built on MSC ADAMS/View with a developed control system built on MATLAB/Simulink. The scaled model is a 1/14 Scania R620 articulated lorry manufactured by TAMIYA. Different parameters of the scaled model have been measured and used as inputs to the simulation model. MSC ADAMS/View was used to model the vehicle and to capture its response. The results were validated through physical tests, so a microcontroller was added to the physical model with different accelerometers to control and record the vehicle's motion instead of the existing radio control. Co-simulation has been implemented using two different control schemes, which have been built and compared against each other. The first control scheme is the electronic stability control system only. The second one is an integrated control system which combines the active front steering with the electronic stability control scheme. The main target of the developed control systems is to stabilise the vehicle through manoeuvres using the Fuzzy logic methodology. The study's main findings are that the experimental results show reasonable similarity to the simulation results, although there are minor differences. The physical validation of the simulation model indicates that it is possible to model a scaled model using multi-body dynamics software with specific considerations. Also, the results give a good understanding of the performance of heavy vehicles. Finally, using the co-simulation implemented using two different control schemes proves that the control can be developed using the scaled model. The proposed control method has been shown to be useful in developing the stability of the vehicle. It enhances the yaw rate for both tractor-trailer by around 25% and the lateral acceleration by around 20% at manoeuvres. Also, the control can be tuned easily using MATLAB. Meanwhile, the electronic stability control scheme gives better performance than the combined active front steering and electronic stability control scheme

Parameter tuning and cooperative control for automated guided vehicles

For several practical control engineering applications it is desirable that multiple systems can operate independently as well as in cooperation with each other. Especially when the transition between individual and cooperative behavior and vice versa can be carried out easily, this results in ??exible and scalable systems. A subclass is formed by systems that are physically separated during individual operation, and very tightly coupled during cooperative operation. One particular application of multiple systems that can operate independently as well as in concert with each other is the cooperative transportation of a large object by multiple Automated Guided Vehicles (AGVs). AGVs are used in industry to transport all kinds of goods, ranging from small trays of compact and video discs to pallets and 40-tonne coils of steel. Current applications typically comprise a ??eet of AGVs, and the vehicles transport products on an individual basis. Recently there has been an increasing demand to transport very large objects such as sewer pipes, rotor blades of wind turbines and pieces of scenery for theaters, which may reach lengths of over thirty meters. A realistic option is to let several AGVs operate together to handle these types of loads. This Ph.D. thesis describes the development, implementation, and testing of distributed control algorithms for transporting a load by two or more Automated Guided Vehicles in industrial environments. We focused on the situations where the load is connected to the AGVs by means of (semi-)rigid interconnections. Attention was restricted to control on the velocity level, which we regard as an intermediate step for achieving fully automatic operation. In our setup the motion setpoint is provided by an external host. The load is assumed to be already present on the vehicles. Docking and grasping procedures are not considered. The project is a collaboration between the company FROG Navigation Systems (Utrecht, The Netherlands) and the Control Systems group of the Technische Universiteit Eindhoven. FROG provided testing facilities including two omni-directional AGVs. Industrial AGVs are custom made for the transportation tasks at hand and come in a variety of forms. To reduce development times it is desirable to follow a model-based control design approach as this allows generalization to a broad class of vehicles. We have adopted rigid body modeling techniques from the ??eld of robotic manipulators to derive the equations of motion for the AGVs and load in a systematic way. These models are based on physical considerations such as Newton's second law and the positions and dimensions of the wheels, sensors, and actuators. Special emphasis is put on the modeling of the wheel-??oor interaction, for which we have adopted tire models that stem from the ??eld of vehicle dynamics. The resulting models have a clear physical interpretation and capture a large class of vehicles with arbitrary wheel con??gurations. This ensures us that the controllers, which are based on these models, are applicable to a broad class of vehicles. An important prerequisite for achieving smooth cooperative behavior is that the individual AGVs operate at the required accuracy. The performance of an individual AGV is directly related to the precision of the estimates for the odometric parameters, i.e. the effective wheel diameters and the offsets of the encoders that measure the steering angles of the wheels. Cooperative transportation applications will typically require AGVs that are highly maneuverable, which means that all the wheels of an individual AGV ahould be able to steer. Since there will be more than one steering angle encoder, the identi??cation of the odometric parameters is substantially more dif??cult for these omni-directional AGVs than for the mobile wheeled robots that are commonly seen in literature and laboratory settings. In this thesis we present a novel procedure for simultaneously estimating effective wheel diameters and steering angle encoder offsets by driving several pure circle segments. The validity of the tuning procedure is con??rmed by experiments with the two omni-directional test vehicles with varying loads. An interesting result is that the effective wheel diameters of the rubber wheels of our AGVs increase with increasing load. A crucial aspect in all control designs is the reconstruction of the to-be-controlled variables from measurement data. Our to-be-controlled variables are the planar motion of the load and the motions of the AGVs with respect to the load, which have to be reconstruct from the odometric sensor information. The odometric sensor information consists of the drive encoder and steering encoder readings. We analyzed the observability of an individual AGV and proved that it is theoretically possible to reconstruct its complete motion from the odometric measurements. Due to practical considerations, we pursued a more pragmatic least-squares based observer design. We show that the least-squares based motion estimate is independent of the coordinate system that is being used. The motion estimator was subsequently analyzed in a stochastic setting. The relation between the motion estimator and the estimated velocity of an arbitrary point on the vehicle was explored. We derived how the covariance of the velocity estimate of an arbitrary point on the vehicle is related to the covariance of the motion estimate. We proved that there is one unique point on the vehicle for which the covariance of the estimated velocity is minimal. Next, we investigated how the local motion estimates of the individual AGVs can be combined to yield one global estimate. When the load and AGVs are rigidly interconnected, it suf??ces that each AGVs broadcasts its local motion estimate and receives the estimates of the other AGVs. When the load is semi-rigidly interconnected to the AGVs, e.g. by means of revolute or prismatic joints, then generally each AGV needs to broadcasts the corresponding information matrix as well. We showed that the information matrix remains constant when the load is connected to the AGV with a revolute joint that is mounted at the aforementioned unique point with the smallest velocity estimate covariance. This means that the corresponding AGV does not have to broadcast its information matrix for this special situation. The key issue in the control design for cooperative transportation tasks is that the various AGVs must not counteract each others' actions. The decentralized controller that we derived makes the AGVs track an externally provided planar motion setpoint while minimizing the interconnection forces between the load and the vehicles. Although the control design is applicable to cooperative transportation by multiple AGVs with arbitrary semi-rigid AGV-load interconnections, it is noteworthy that a particularly elegant solution arises when all interconnections are completely rigid. Then the derived local controllers have the same structure as the controllers that are normally used for individual operation. As a result, changing a few parameter settings and providing the AGVs with identical setpoints is all that is required to achieve cooperative behavior on the velocity level for this situation. The observer and controller designs for the case that the AGVs are completely rigidly interconnected to the load were successfully implemented on the two test vehicles. Experi ments were carried out with and without a load that consisted of a pallet with 300 kg pave stones. The results were reproducible and illustrated the practical validity of the observer and controller designs. There were no substantial drawbacks when the local observers used only their local sensor information, which means that our setup can also operate satisfactory when the velocity estimates are not shared with the other vehicles

Transportation Systems Analysis and Assessment

The transportation system is the backbone of any social and economic system, and is also a very complex system in which users, transport means, technologies, services, and infrastructures have to cooperate with each other to achieve common and unique goals.The aim of this book is to present a general overview on some of the main challenges that transportation planners and decision makers are faced with. The book addresses different topics that range from user's behavior to travel demand simulation, from supply chain to the railway infrastructure capacity, from traffic safety issues to Life Cycle Assessment, and to strategies to make the transportation system more sustainable

Enhancing service quality and reliability in intelligent traffic system

Intelligent Traffic Systems (ITS) can manage on-road traffic efficiently based on real-time traffic conditions, reduce delay at the intersections, and maintain the safety of the road users. However, emergency vehicles still struggle to meet their targeted response time, and an ITS is vulnerable to various types of attacks, including cyberattacks. To address these issues, in this dissertation, we introduce three techniques that enhance the service quality and reliability of an ITS. First, an innovative Emergency Vehicle Priority System (EVPS) is presented to assist an Emergency Vehicle (EV) in attending the incident place faster. Our proposed EVPS determines the proper priority codes of EV based on the type of incidents. After priority code generation, EVPS selects the number of traffic signals needed to be turned green considering the impact on other vehicles gathered in the relevant adjacent cells. Second, for improving reliability, an Intrusion Detection System for traffic signals is proposed for the first time, which leverages traffic and signal characteristics such as the flow rate, vehicle speed, and signal phase time. Shannon’s entropy is used to calculate the uncertainty associated with the likelihood of particular evidence and Dempster-Shafer (DS) decision theory is used to fuse the evidential information. Finally, to improve the reliability of a future ITS, we introduce a model that assesses the trust level of four major On-Board Units (OBU) of a self-driving car along with Global Positioning System (GPS) data and safety messages. Both subjective logic (DS theory) and CertainLogic are used to develop the theoretical underpinning for estimating the trust value of a self-driving car by fusing the trust value of four OBU components, GPS data and safety messages. For evaluation and validation purposes, a popular and widely used traffic simulation package, namely Simulation of Urban Mobility (SUMO), is used to develop the simulation platform using a real map of Melbourne CBD. The relevant historical real data taken from the VicRoads website were used to inject the traffic flow and density in the simulation model. We evaluated the performance of our proposed techniques considering different traffic and signal characteristics such as occupancy rate, flow rate, phase time, and vehicle speed under many realistic scenarios. The simulation result shows the potential efficacy of our proposed techniques for all selected scenarios.Doctor of Philosoph