Integrated Strategy for Automatic Lane-Changing Decision and Trajectory Planning in Dynamic Scenario

Automatic lane change is a necessary part for autonomous driving. This paper proposes an integrated strategy for automatic lane-changing decision and trajectory planning in dynamic scenario. The Back Propagation Neural Network (BPNN) is used in decision-making layer, whose prediction accuracy of the discretionary lane-changing is 94.22%. The planning layer determines the adjustable range of the average vehicle speed based on the size of the “lane-changing demand”, which is obtained based on the data of hidden layer in neural network, and then dynamically optimizes the lane-changing curve according to the vehicle speed and the current scenario. In order to verify the rationality of the proposed lane-changing architecture, simulation experiments based on a driving simulator is performed. The experiments show that the vehicle’s maximum lateral acceleration under the proposed lane-changing trajectory at a speed of 70km/h is about 0.1g, which means the vehicle has better comfort during lane-changing. At the same time, the proposed lane-changing trajectory is more in line with the human driver’s lane-changing trajectory compared with that of other planning strategy. Meanwhile, the planning strategy can also support the lane-changing trajectory planning on a curved road.

A Model Predictive Control Strategy for Lateral and Longitudinal Dynamics in Autonomous Driving

This paper presents a controller dedicated to the lateral and longitudinal vehicle dynamics control for autonomous driving. The proposed strategy exploits a Model Predictive Control strategy to perform lateral guidance and speed regulation. To this end, the algorithm controls the steering angle and the throttle and brake pedals for minimizing the vehicle’s lateral deviation and relative yaw angle with respect to the reference trajectory, while the vehicle speed is controlled to drive at the maximum acceptable longitudinal speed considering the adherence and legal speed limits. The technique exploits data computed by a simulated camera mounted on the top of the vehicle while moving in different driving scenarios. The longitudinal control strategy is based on a reference speed generator, which computes the maximum speed considering the road geometry and lateral motion of the vehicle at the same time. The proposed controller is tested in highway, interurban and urban driving scenarios to check the performance of the proposed method in different driving environments.

Development of a Multi-DOF Tuned Dynamic Absorber for Reducing Hand Vibrations on an Off-Highway Vehicle

A variety of off-highway vehicles are subject to significant steering wheel vibrations during operation. Typical examples of such machines are vibratory asphalt and soil compactors. Large compacting forces, while essential for the proper compacting operation, will inevitably cause undesired effects such as severe vibrations of steering wheels. Traditional vibration control measures are often found either impractical or less effective in reducing the level of hand vibrations which is considered an important quality and safety issue in compacter design and sales. In this paper, an advanced concept of reducing hand vibrations is presented in the context of Multi-degree-of-freedom Tuned Dynamic Absorbers (MTDA). The MTDA essentially represents an assembly of simple dynamic absorbers individually tuned to different targeted vibration modes in different degree of freedoms. While the design concept and associated parameters are numerically determined by FEA, the prototype is fine tuned to the desired vibration modes through a bench test. The effectiveness of the MTDA is experimentally verified in-situ through a sequence of tests which are carefully designed to adequately reflect its performance under field conditions.

Active Aerodynamics Through Active Body Control: Modelling and Static Simulator Validation

Active aerodynamics is a growing field in the race car and high-performance vehicles segments, since each situation on the track may require different aero forces to achieve the best vehicle dynamics performance. This paper presents an active aerodynamics control system developed through the active control of the body trim. By interchanging four different setups on the suspension heights with a fuzzy logic control, relevant advantage is obtained in terms of lap time reduction. Two systems, a PID and a Feedforward logic, are studied to implement the control strategy and important differences are found in the stability of tire-ground forces benefiting the latter. Furthermore, the system was validated in a Driver-In-the-Loop (DIL) static simulator with a more realistic road conditions and important insights in terms of subjective evaluation.

Design of an Onboard Directional Anemometer for Bicycles

Wind speed has large influence on the results of road tests applied to bicycles. For this reason, this paper presents the design process of an onboard anemometer dedicated to bicycle testing. The design provides an affordable way to quantify both magnitude and direction of the wind velocity relative to the bicycle, allowing recording on arbitrary wind conditions that could arise during a test. The design methodology was structured with two major phases. The first was centered on the proof-of-concept for the use of a multi-hole pitot tube as main component for the onboard anemometer. The second was focused on the design of the structure, considering both packaging and structural integrity. The prototype of anemometer was tested in a wind tunnel to verify its performance, and it was also tested under severe vibrations to verify its structural integrity. The results showed that this concept can be used as a part of the bicycle instrumentation for road tests.

Propulsion Dynamic Requirements Analysis for Multi-Axle Skid-Steer Wheeled Vehicles

Multi-axle skid-steer wheeled vehicles have the advantages of simplicity and enhanced traction. That’s why they are used in off-road environments and also in mobile robots. In the present work, a dynamic analysis of the propulsion system requirements for multi-axle wheeled vehicles is investigated. As the multi-axle wheeled vehicle differentially steers at a smaller turning radius, the driving torque requirements approach their peak. The adhesion at each tire of the multi-axle vehicle and its relation to the contact patches are analyzed. The analysis presented starts with four wheel drive, six wheel drive and eight wheel drive vehicles, then it is widened to n-wheel drive vehicles. A generic formula for obtaining the propulsion torque requirements for multi-axle skid-steer wheeled vehicles is presented. The analysis is extended to include experimental validation of the obtained analytical results. The experimental work includes three small electrically driven skid-steer vehicles; four wheel drive vehicle, six wheel drive vehicle and eight wheel drive vehicle. The selection of the drive motors for each of those vehicles was based on the proposed formula. Each of the three vehicles was tested in the worst case adhesion torque requirement. The experimental results showed that the proposed formula is capable, to a great extent, to predict the torque requirements for the multi-axle skid-steer wheeled vehicles in the design phase.

Real-Time Applicable Power Management of Multi-Source Fuel Cell Vehicles Using Situation-Based Model Predictive Control

Power management in all-electric powertrains has a significant potential to optimally handle the limited energy and power density of electric power sources. Situation-based power management strategies (SB-PMSs), defining optimized solutions related to specific vehicle situations, offer the ability to reduce computational requirements and enhance the solution optimality of simple rule-based algorithms. Moreover, the local optimality of SB-PMSs can be addressed by considering online optimization of the situated solutions for limited horizons. This paper presents a novel PMSs using model predictive control (MPC) to define optimal control strategies based on situated solutions for fuel cell hybrid vehicles. Vehicle states are defined in terms of multiple characteristic variables and power management decisions are optimized offline for each vehicle states. Prediction of vehicle states is conducted using statistical predictive model based on state transitions in a number of driving cycles. Preoptimized solutions related to predicted states are iterated online to achieve better optimality over the look-ahead horizon. Results analysis from online testing revealed the ability of SB-MPC to improve the optimality of situation-based solutions and hence reduce total energy cost in different driving cycles.

The Influence of Gait Stance and Vehicle Type on Pedestrian Kinematics and Injury Risk

Pedestrians are one of the most vulnerable road users. In 2018 the USA reported the highest number of pedestrian fatalities number in nearly three decades. Government safety agencies and car manufacturers have started paying greater attention towards pedestrian protection. The pre-impact conditions of Car-to-Pedestrian Collisions (CPC) varies significantly in terms of the characteristics of vehicles (e.g. front-end geometry, stiffness, etc.) and pedestrians (e.g. anthropometry, posture, etc.). The influence of vehicle type and pedestrian gait has not been analyzed. The purpose of this study was to numerically investigate the changes in pedestrian kinematics and injuries across various gait postures and two different car types. Five finite element (FE) human body models, representing 50th percentile male in gait cycle, were developed and used to perform CPC simulations with two generic vehicle FE models representing a family car (FCR), and a sport utility vehicle (SUV). In the impacts with the high-profile vehicle (SUV), the pedestrian models usually slide above the bonnet leading edge and report shorter wrap around distances (WAD) than in low-profile vehicle (FCR) impacts. The pedestrian postures influenced the post-impact rotation of the pedestrian and consequently, the impacted head region. The pedestrian posture also influenced the risk of injuries in the lower extremities. Higher risk of bone fractures was observed in the stance phase posture compared to the swing phase. The findings of this study should be taken into consideration when examining pedestrian protection protocols. In addition, the results of this study can be used to improve the design of active safety systems used to protect pedestrians in collisions.

Influence of the Chainring Geometry on the Critical Power of Recreational Cyclists

Science has come to a disagreement regarding the real effect that chainrings’ geometry has on cyclists’ performance. In this study, the influence of the use of a noncircular chainring on recreational cyclists’ performance is determined through experimental power delivery tests. A critical power model was used to estimate variations on cyclists’ performance. In addition, a new protocol for estimating critical power was proposed. Fourteen recreational cyclists (two females and twelve males) performed a series of self-paced constant-time tests with a circular and a noncircular (i.e., Osymetric) chainring during two different test sessions. Power output, cadence and time were registered to compute the critical power. According to the results of this study, it seems there is a change in the critical power of the majority of the recreational cyclists due to the use of a noncircular chainring. Thus, a performance improvement was obtained during long-endurance tests. However, the order of the tests (i.e., starting with the circular chainring or starting with the noncircular chainring) was proven to have an impact on the results due to a familiarization effect to the test conditions. Finally, a new protocol to estimate the critical power of a cyclist by performing a single riding session was proposed and assessed on a pilot test (i.e., error < 3%).

Lightweight Design of a Multi-Material Suspension Lower Control Arm

This paper is focused on the design, analysis and testing of a multi-material (carbon fibre and steel) Lower Control Arm (LCA) of a McPherson suspension for a C segment vehicle. Therefore, starting from the existing component (made of steel), the LCA mass has been reduced by using a hybrid technology, diminishing the steel thickness and adding a carbon fiber tailored cover without compromising the mechanical performance in terms of stiffness and stress distribution. In so doing, it has been possible to evaluate the potential and the capabilities of the hybridization without re-designing the component totally. In particular, it has been developed a specific methodology that combines both virtual and experimental procedures to face the hybridization challenges of mechanical coupling, safety and lightweight. For these reasons, the multi-material lower control arm represents a noticeable case study in which this methodology has been applied, correlated and validated.