Active Safety Systems Research Articles

Evaluating the effectiveness of active vehicle safety systems

Advanced vehicle safety systems have been widely introduced in transportation systems and are expected to enhance traffic safety. However, these technologies mainly focus on assisting individual vehicles that are equipped with them, and less effort has been made to identify the effect of vehicular technologies on the traffic stream. This study proposed a methodology to assess the effectiveness of active vehicle safety systems (AVSSs), which represent a promising technology to prevent traffic crashes and mitigate injury severity. The proposed AVSS consists of longitudinal and lateral vehicle control systems, which corresponds to the Level 2 vehicle automation presented by the National Highway Safety Administration (NHTSA). The effectiveness evaluation for the proposed technology was conducted in terms of crash potential reduction and congestion mitigation. A microscopic traffic simulator, VISSIM, was used to simulate freeway traffic stream and collect vehicle-maneuvering data. In addition, an external application program interface, VISSIM’s COM-interface, was used to implement the AVSS. A surrogate safety assessment model (SSAM) was used to derive indirect safety measures to evaluate the effectiveness of the AVSS. A 16.7-km freeway stretch between the Nakdong and Seonsan interchanges on Korean freeway 45 was selected for the simulation experiments to evaluate the effectiveness of AVSS. A total of five simulation runs for each evaluation scenario were conducted. For the non-incident conditions, the rear-end and lane-change conflicts were reduced by 78.8% and 17.3%, respectively, under the level of service (LOS) D traffic conditions. In addition, the average delay was reduced by 55.5%. However, the system’s effectiveness was weakened in the LOS A–C categories. Under incident traffic conditions, the number of rear-end conflicts was reduced by approximately 9.7%. Vehicle delays were reduced by approximately 43.9% with 100% of market penetration rate (MPR). These results imply that from the perspective of traffic operations and control to address the safety and congestion issues of a traffic stream, smarter management strategies that consider both traffic conditions and MPR are required to fully exploit the effectiveness of the AVSS in the field.

Simultaneous braking and steering control method based on nonlinear model predictive control for emergency driving support

Autonomous emergency braking (AEB) has drawn a lot of attention as an active safety system preventing rear-end collision avoidance when the relative speed between vehicles is slow. To increase the operation range of current AEB system, this paper suggests a collision avoidance strategy using steering and braking simultaneously with nonlinear model predictive control (NMPC) method. The NMPC predicts the vehicle’s future trajectory with its open-loop dynamics and calculates the error between the predicted and the desired paths. Then NMPC calculates the control inputs such as the wheel steering angle and vehicle acceleration by optimizing the cost function over future receding horizon with predetermined constraints. In this paper, constraints on the wheel steering angle is proposed in consideration of vehicle’s predicted lateral acceleration, which should be smaller than the threshold in order to maintain lateral vehicle’s stability. To verify the performance of the proposed strategy, two simulation scenarios were tested in MATLAB and CarSim simulation environments.

Model-based braking control of a heavy commercial road vehicle equipped with an electropneumatic brake system

Heavy commercial road vehicles have a longer stopping distance, owing to the inherent time lag associated with the conventional air brake system used in them. In general, electropneumatic brake systems would respond more quickly, resulting in a shorter stopping distance; these are the focus of this study. In an earlier work, the best configuration of the electropneumatic brake system was determined, considering both response and cost perspectives. This study focuses on the development of an experimentally corroborated mathematical model for this brake system. Non-linear model-based deceleration and brake chamber pressure control schemes were subsequently developed and their performance evaluated using a hardware-in-loop system. The model-based analysis and the control schemes presented in this article will assist in the development of advanced and cost-efficient active safety systems for heavy commercial road vehicles.

Development of estimated disturbance rejection feedback for an armoured vehicle using active front wheel steering

An unwanted yaw motion occurred at the centre of gravity (CG) of the wheeled armoured vehicle caused by the impulse force generated during gun turret firing. The recoil force from the gun fire tends to create instability conditions for the armoured vehicle during firing condition and affects the dynamic performance of armoured vehicle in lateral direction. In this paper, an active safety system, active front wheel steering (AFWS) system using estimated disturbance rejection feedback (EDRF) embodiment is proposed to reject the unwanted yaw disturbance and stabilise the armoured vehicle. Besides, the proposed control strategy is also used to re-position the armoured vehicle back to its initial position. Therefore, a summation moment reference input is used to counter back the unwanted firing moment occurred due to gun firing impulse at CG of the armoured vehicle. The armoured vehicle is evaluated via simulation analysis in term of yaw rate, yaw angle, vehicle sideslip angle, lateral acceleration and lateral displacement. Significant improvements up to 75% have been achieved by using the proposed control strategy of AFWS system to reject the external disturbance due to the firing force.

Using Adaptive Pole Placement Control Strategy for Active Steering Safety System

Using Adaptive Pole Placement Control Strategy for Active Steering Safety System

Modeling and Simulation of the Motorcycle's Lowside Fall

The deployment of active safety systems enhancing the motorcycle stability and supporting riders in defusing critical and dangerous driving situations is a topic of major concern in the two-wheel research community. In the design and development of safety control systems, setting up an adequate model of the controlled system is a key issue since it should be able to describe adequately the motion of the vehicle in critical situations such as precarious adherence, cornering brake and acceleration, or dangerous falls. In literature, these situations are typically investigated by means of black box approaches, namely by using multibody numerical simulators in which the equations governing the vehicle dynamics are unknown. In this paper, instead, the authors propose an analytical model as alternative to black box approach for the simulation of critical and complex motorcycle's dynamics leading to falls. The model has been presented in author's earlier works, it has a minimum degree of complexity, considers the rear wheel traction/braking and takes into account the interactions between longitudinal and lateral friction forces acting on the tyres. This analytical model has allowed to investigate the lowside phenomenon and the simulation results will be presented.

Rational Lifetime of a Vehicle in Terms of Ensuring Security of Its Design

In recent years, automakers have been actively developing and implementing electronic active safety systems. These components and systems increase the vehicle safety, but complicate the design and increase the cost of maintaining it in good condition. Numerous theoretical studies have noted that the nature of the technical readiness coefficient changes during the time of operation exponentially, and by operational kilometers - linearly. The performed research allows concluding that the value of the realized technical readiness coefficient is determined by its minimum permissible value. The performed situational analysis suggests that the solution of the problem to ensure the lifetime of a vehicle, for example, according to the standards of safety features, requires optimization of solutions. This requires the formation of the multicriteria quality scorecards of the vehicle performance properties.

Identification of an optimum control algorithm to reject unwanted yaw effect on wheeled armored vehicle due to the recoil force

This article presents an active safety system for a wheeled armored vehicle to encounter the effect of the firing force. The firing force which acts as an external disturbance causes unwanted yaw moment occurred at the center of gravity of the wheeled armored vehicle. This effect causes the wheeled armored vehicle lose its handling stability and the traveling path after the firing condition. In order to overcome the stability problem, a Firing-On-the-Move assisted by an Active Front Wheel Steering system is proposed in this study. This system is developed based on two established systems, namely, Firing-On-the-Move and Active Front Wheel Steering systems. The proposed system is designed to improve the handling and directional stability performances of the armored vehicle while fires in dynamic condition. Four types of control strategies are designed and investigated in this study to identify the most optimum control strategy as the Firing-On-the-Move assisted by an Active Front Wheel Steering system using optimization tool, genetic algorithm. The control strategies for the Firing-On-the-Move assisted by an Active Front Wheel Steering are evaluated using various types of vehicle speeds and firing angle in order to obtain an appropriate control structure as the Firing-On-the-Move assisted by an Active Front Wheel Steering system for the wheeled armored vehicle.

A conceptual emotion recognition framework: stress and anger analysis for car accidents

In year 2013, 777,817 out of 22,702,211 of registered vehicles were involved in road traffic crashes, with a damage cost of more than 9.3 billion ringgits in Malaysia. Automotive makers have deployed a wide range of active safety systems (traction control, auto cruise and braking, collision avoidance, and lane switching) in recent years. However, these systems failed to significantly reduce road crash statistics. The automotive network comprises the vehicle, road and driver. Huge effort had been placed on the vehicle and road, whereas the driver remains the feeblest part. Consequently, automotive makers should focus their attention on monitoring drivers' emotion, which influences their driving behaviour. This study aims to explore available technology that monitors driver behaviour, besides proposing accident-stimulating emotion that affects driving. Furthermore, a conceptual framework for recognising anger and stress emotion, which is a cause of road crash, is proposed.

Special Issue on Future Active Safety Technology towards Zero-Traffic Accidents (FAST-zero) [Guest Editorial

The articles in this special section focus on traffic safety technology design to avoid traffic accidents. Innovation in the field of active safety is the key driving force towards the ultimate goal of realizing zero traffic-accidents. Researchers around the world have been investigating methods for active safety to reduce and possibly eliminate traffic accidents as well as road fatalities. Automated and connected vehicles in particular have the potential to enhance safety through new sensors, dynamic maps, artificial intelligence and other technologies that have experienced great improvements in recent years. Sensor fusion algorithms and platforms are intended to enhance the performance of active safety systems, and thus implement the ultimate goal of zero traffic accidents.

An Engine/Vehicle Model to Assess the Theoretical Increase of Car Safety by Using the Spark Ignition Engine to Support the Conventional Braking System

Introduction of active safety systems has led to a significant increase of passenger car safety. However, statistics on road accidents show that further improvements of active systems would be necessary. This paper presents a dynamical model of the engine–car–brakes system that is used to simulate vehicle deceleration and calculate the risk of injuries. The model is used to quantify the performance of active safety systems during specific collision scenarios in which several vehicle cruising speeds and different values of distance from the obstacle that causes the active system activation are considered. The base system constituted by actual hydraulic brakes with embedded ABS is first compared to the ideal active system. The latter allows for maximum vehicle deceleration owing to ideal operation of hydraulic brakes supported by ABS and also to mechatronic actuation which anticipates the human intervention and eliminates the delay due to reaction time. Then, the model is used to analyse two feasible evolutions of the ideal active safety system. In the first one, the internal combustion engine friction power aids the vehicle speed decrease before the action of brakes. In the second one, specifically devoted to vehicles powered by hybrid electrical–thermal units, the reversible electric motor operates in addition/substitution to the braking action exerted by the engine mechanical friction.

An Engine/Vehicle Model to Assess the Theoretical Increase of Car Safety by Using the Spark Ignition Engine to Support the Conventional Braking System

Introduction of active safety systems has led to a significant increase of passenger car safety. However, statistics on road accidents show that further improvements of active systems would be necessary. This paper presents a dynamical model of the engine–car–brakes system that is used to simulate vehicle deceleration and calculate the risk of injuries. The model is used to quantify the performance of active safety systems during specific collision scenarios in which several vehicle cruising speeds and different values of distance from the obstacle that causes the active system activation are considered. The base system constituted by actual hydraulic brakes with embedded ABS is first compared to the ideal active system. The latter allows for maximum vehicle deceleration owing to ideal operation of hydraulic brakes supported by ABS and also to mechatronic actuation which anticipates the human intervention and eliminates the delay due to reaction time. Then, the model is used to analyse two feasible evolutions of the ideal active safety system. In the first one, the internal combustion engine friction power aids the vehicle speed decrease before the action of brakes. In the second one, specifically devoted to vehicles powered by hybrid electrical–thermal units, the reversible electric motor operates in addition/substitution to the braking action exerted by the engine mechanical friction.

Trust in Technology as a Safety Aspect in Highly Automated Driving

Abstract Trust in technology is an important factor to be considered for safety-critical systems. Of particular interest today is the transport domain, as more and more complex information and assistance systems find their way into vehicles. Research in driving automation / automated driving systems is in the focus of many research institutes worldwide. On the operational side, active safety systems employed to save lives are frequently used by non-professional drivers that neither know system boundaries nor the underlying functional principle. This is a serious safety issue, as systems are activated under false circumstances and with wrong expectations. At least some of the recent incidents with advanced driving assistance systems (ADAS) or automated driving systems (ADS; SAE J3016) could have been prevented with a full understanding of the driver about system functionality and limitations (instead of overreliance). Drivers have to be trained to accept and use these systems in a way, that subjective trust matches objective trustworthiness (cf. “appropriate trust”) to prevent disuse and / or misuse. In this article, we present an interaction model for trust calibration that issues personalized messages in real time. On the showcase of automated driving we report the results of two user studies related to trust in ADS and driving ethics. In the first experiment (N = 48), mental and emotional states of front-seat passengers were compared to get deeper insight into the dispositional trust of potential users of automated vehicles. Using quantitative and qualitative methods, we found that subjects accept and trust ADSs almost similarly as male / female drivers. In another study (N = 40), moral decisions of drivers were investigated in a systematic way. Our results indicate that the willingness of drivers to risk even severe accidents increases with the number and age of pedestrians that would otherwise be sacrificed. Based on our initial findings, we further discuss related aspects of trust in driving automation. Effective shared vehicle control and expected advantages of fully / highly automated driving (SAE levels 3 or higher) can only be achieved when trust issues are demonstrated and resolved.

Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm

Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which first combines auxiliary particle filter and the iterated extended kalman filter (APF-IEKF), and then processes the results of the first step using iteration algorithm. APF-IEKF is used to estimate the slip angle of the front tires with strong nonlinearity and non-Gaussian noise, in which APF filters non-Gaussian noise and reach a preliminary estimation of sideslip angle, then IEKF is used to optimize the result, making the estimation of the sideslip angle more accurate. The iteration algorithm is used to estimate the tire-road friction coefficient based on self-aligning torque, which is more sensitive to tire slip angle and provides faster estimation. In this way, this method can estimate tire road friction coefficient more accurately and in real time. Both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm.

A design synthesis framework for directional performance optimization of multi-trailer articulated heavy vehicles with trailer lateral dynamic control systems

This paper presents a design synthesis framework for directional performance optimization of multi-trailer articulated heavy vehicles with trailer lateral dynamic control systems, e.g. active trailer steering, trailer differential braking, active roll control or the coordination of the three systems. In order to demonstrate the effectiveness of the proposed framework, it was applied to the design optimization of a multi-trailer articulated heavy vehicle with an active trailer steering controller. In the design, a set of lateral stability measures is originally defined, and the design problem under simulated test manoeuvres is implemented using a parallel computing technique. It is illustrated that the proposed framework and the performance measures can be used to identify effectively the desired variables and to predict reliably the performance envelopes of multi-trailer articulated heavy vehicles with active safety systems by considering the concept of driver-adaptive-vehicle design.

Application of vehicle to another entity (V2X) communications for motorcycle crash avoidance

ABSTRACTInformation and communication technologies are being massively applied in the automotive field as the basis of the new generation of active safety systems. In this extensive field of technologies, vehicular communications will constitute the core of a large set of advanced driving assistance systems for improving road safety as well as helping to reduce the environmental impact of transport. These communication technologies are currently under deployment, but their mandatory installation in newly manufactured cars is foreseen in the next 5 years. This equipment will enable the new Advanced Driver Assistance Systems (ADAS) system to be installed in these vehicles. Many of these safety applications are currently under development. However, there are some road users who are not commonly included in this vehicular communication ecosystem, specifically, vulnerable road users, such as pedestrians, cyclists, and motorcyclists. Current assistance systems focused on reducing crashes with this user group are based on sensors installed in the vehicles but do not include vehicular communications. In this article, we present a novel Vulnerable Road User (VRU) warning system based on Vehicle-to-Vehicle (V2V) communications, which is capable of detecting a motorcycle circulating in the vicinity of the connected vehicles, launching sound and visual warnings, and using a smartphone as human-machine interface. The system has been designed, implemented, and tested in the laboratory as well as on real roads in real traffic flow.

Mechanisms and Mitigation of Head and Spinal Injuries Due to Motor Vehicle Crashes.

Synopsis Head and spinal injuries commonly occur during motor vehicle crashes (MVCs). The goal of this clinical commentary is to discuss real-life versus simulated MVCs and to present clinical, biomechanical, and epidemiological evidence of MVC-related injury mechanisms. It will also address how this knowledge may guide and inform the design of injury mitigation devices and assist in clinical decision making. Evidence indicates that there exists no universal injury tolerance applicable to the entire population of the occupants of MVCs. Injuries sustained by occupants depend on a number of factors, including occupant characteristics (age, height, weight, sex, bone mineral density, and pre-existing medical and musculoskeletal conditions), pre-MVC factors (awareness of the impending crash, occupant position, usage of and position of the seatbelt and head restraint, and vehicle specifications), and MVC-related factors (crash orientation, vehicle dynamics, type of active or passive safety systems, and occupant kinematic response). Injuries resulting from an MVC occur due to blunt impact and/or inertial loading. An S-shaped curvature of the cervical spine and associated injurious strains have been documented during rear-, frontal-, and side-impact MVCs. Data on the injury mechanism and the quantification of spinal instability guide and inform the emergent and subsequent conservative or surgical care. Such care may require determining optimal patient positioning during transport, which injuries may be treated conservatively, whether reduction should be performed, optimal patient positioning intraoperatively, and whether bracing should be worn prior to and/or following surgery. The continued improvement of traditional injury mitigation systems, such as seats, seatbelts, airbags, and head restraints, together with research of newer collision-avoidance technologies, will lead to safer motor vehicles and ultimately more effective injury management strategies. J Orthop Sports Phys Ther 2016;46(10):826-833. Epub 3 Sep 2016. doi:10.2519/jospt.2016.6716.

Predicting crash-relevant violations at stop sign–controlled intersections for the development of an intersection driver assistance system

ABSTRACTObjective: Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent.Methods: Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop—that is, required deceleration parameter (RDP) and brake application—were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities.Results: A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3–71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5–26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3–65.8%) of the vehicles could have been stopped.Conclusions: This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

Sideslip estimation for articulated heavy vehicles at the limits of adhesion

ABSTRACTVarious active safety systems proposed for articulated heavy goods vehicles (HGVs) require an accurate estimate of vehicle sideslip angle. However in contrast to passenger cars, there has been minimal published research on sideslip estimation for articulated HGVs. State-of-the-art observers, which rely on linear vehicle models, perform poorly when manoeuvring near the limits of tyre adhesion. This paper investigates three nonlinear Kalman filters (KFs) for estimating the tractor sideslip angle of a tractor–semitrailer. These are compared to the current state-of-the-art, through computer simulations and vehicle test data. An unscented KF using a 5 degrees-of-freedom single-track vehicle model with linear adaptive tyres is found to substantially outperform the state-of-the-art linear KF across a range of test manoeuvres on different surfaces, both at constant speed and during emergency braking. Robustness of the observer to parameter uncertainty is also demonstrated.

Target classification layer design via vehicle-to-vehicle communication

Recently, an active safety system based on vehicle-to-vehicle communication was introduced to minimize the threat of car accidents on the road and to overcome the limitations of the current sensor-based advanced driver assist system. In order to implement the system based on vehicle-to-vehicle communication, target classification is the key layer to be developed. In this study, based on the transmitted path history of the remote vehicles, the road geometry around the host vehicle is reconstructed without in-vehicle sensors such as vision cameras. A tracking algorithm for the remote vehicle is formulated in order to predict its position continuously by using an extended Kalman filter. A local map is obtained with an outlier filter, and the target classification algorithm is designed from vehicle-to-vehicle communication data. The proposed algorithms are validated by simulations and experiments carried out using test vehicles.