VANET Jamming and Adversarial Attack Defense for Autonomous Vehicle Safety

The development of Vehicular Ad-hoc Network(VANET)technology is helping Intelligent Transportation System(ITS)services to become a reality.Vehicles can use VANETs to communicate safety messages on the road(while driving)and can inform their location and share road condition information in real-time.However,intentional and unintentional(e.g.,packet/frame collision)wireless signal jamming can occur,which will degrade the quality of communication over the channel,preventing the reception of safety messages,and thereby posing a safety hazard to the vehicle’s passengers.In this paper,VANET jamming detection applying Support Vector Machine(SVM)machine learning technology is used to classify jamming and non-jamming situations.The analysis is based on two cases which include normal traffic and heavy traffic conditions,where the results show that the probability of packet dropping will increase when many vehicles are using the wireless channel simultaneously.When using SVM classification,the most appropriate feature set applied in determining a jamming situation shows an accuracy of 98%or higher.Furthermore,more advanced jamming attacks need to be considered for preparation of more reliable and safer autonomous ITS services.Such research can use vehicular communication transmission and reception data based on selected published datasets.In this paper,an additional adversarial defense algorithm using the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)method is proposed,which assumes that evolutionary attacks of the jammer will attempt to confuse the trained classifier.The simulation results show that applying DBSCAN can improve the accuracy by elimination of outliers before conducting classification testing.

Design of crashworthy attenuator structures as a part of vehicle safetyagainst impact:Application of waste aluminum can-based material

The impact attenuator is an essential system in both race cars and urban vehicles.The structure of animpact attenuator serves as a safety barrier between the impacted surface and the driver in an accident.Attenuator materials tend to have a high price;thus,alternative materials were explored in the currentwork,i.e.,used cans from food and beverage containers.The study deployed a nonlinear finite elementalgorithm to calculate a series of impacts on the attenuator structures.The thickness of the cans andvelocity of the impact were considered as the main parameters.Analysis results concluded that the at-tenuator’s average energy was 16000 J for a can thickness of 1 mm.This value is more than two times the0.5 mm thick used cans.The attenuator’s new design was then matched with an attenuator regulation,and the results surpassed the standard value of 7350 J.

STEERING SAFETY EVALUATION OF DRIVER VEHICLE CLOSED LOOP SYSTEM WITH RANDOM ROAD INPUT

The response simulation is studied and the steering safety is evaluated by using finer integration method for driver vehicle closed loop system with stationary random road input.This algorithm not only is precise, but also can shorten the evaluation period of steering safety and reduce the tremendous cost for real vehicle testing.The response simulation and the vehicle steering safety evaluation are also studied for the closed loop system with evolutionary random road input.The study can more truly evaluate vehicle driving for including the slowly varying of vehicle velocity with time.

Revision of the National Standard on Safety Specification for Power Driven Vehicles Operating on Roads

The national standard--Safety Specifications for Power Driven Vehicles Operating on Roads-is the most basic technieal regulation for safety and technical management of motor vehicles in China. It is the safety and technical basis for the Public Security Traffic Control Dept. to register new vehicles, periodic inspection of vehicles under operation and inspection of vehicles involved in traffic accidents. It is also one of the important technical bases of our country for compulsory inspection of new vehicles on finalization of its model, ex-works inspection of new vehicles and the inspection of imported motor vehicles.

Design and evaluation of V2X communication system for vehicle and pedestrian safety

As the vehicles gain the extensive popularity and increasing demand, traffic accident is one of the most serious problems faced by modem transportation system. Hereinto, crashes between cars and pedestrians cause plenty of injuries and even death. Diverting attention from walking to smartphones is one of the main reasons for pedestrians getting injured by vehicles. However, the traditional measures protecting pedestrians from the vehicles heavily rely on the sound warning method, which do not capable for pedestrians focusing on the smartphones. As the smartphones become ubiquitous and intelligent, they have the capacity to provide alert for the pedestrians with the help of vehicle-to-pedestrian （V2P） communication. In this paper, an efficient vehicle-to-X （V2X） communication system is designed for the vehicle and pedestrian communication to guarantee the safety of people. It achieves the IEEE 802.11p and the WiFi protocols meanwhile on the on-board unit （OBU） designed for vehicles. Extensive evaluation shows that the OBU can provide the reliable communication for vehicle-to-vehicle （V2V） and V2P in terms of packet delivery rate and average delay. Furthermore, two safety applications have been developed to protect the safety of vehicles and pedestrians based on the data transferred from the OBU. The first application is designed to show the driving information and provide the collision forewaming alert on the tablet within the vehicle. The second application is developed for the smartphone to provide forewarning alert information to the smartphone-distracted vulnerable pedestrians. Smartphone states are appreciable to provide the adaptive alert modes. Experimental results show that these applications are capable of alerting the intersection accidents, and the pedestrians can get the adaptive alerts according to smartphone usage contexts.

Investigating safety and liability of autonomous vehicles:Bayesian random parameter ordered probit model analysis

Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.

Bivariate macro-level safety analysis of non-motorized vehicle crashes and crash-involved road users

The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones generally by crash frequency or density,which is effective for roadway engineering improvements but neglects characteristics related to other improvements such as safety education.As safety education would be more effective if targeted at the residences of crash-involved road users,the traditional approach to hot zones may therefore provide biased results for such alternative countermeasures.After confirming that 77.17%of NMV crashes occurred outside the involved riders’areas of residence,this study compared the differences between the locations of crashes and the residences of NMV crash-involved riders in safety influencing factors and hot zone identification.A Poisson lognormal bivariate conditional autoregressive(PLN-BCAR)model was developed to account for potential correlations between crashes and involved riders.The model was compared with the univariate Poisson lognormal conditional autoregressive(UPLN-CAR)model and the bivariate Poisson lognormal conditional autoregressive(BPLNCAR)model;the PLN-BCAR model outperformed the other two models in its better interpretation of the influencing factors and its more efficient parameter estimation.Model results indicated that crashes were mainly associated with roadway and land use characteristics,while involved road users were mainly associated with socioeconomic and land use characteristics.The potential for safety improvement method was adopted to identify hot zones for countermeasure implementation.Results showed over 60%of the identified hot zones were inconsistent:they needed improvement in either engineering or education but not both.These findings can help target the type of improvement to better utilize resources for NMV safety.

Anthropometric Comparison of Three-Year-Old Nigerian Child and Crash Dummies

In this work, anthropometric data measured from three-year-old Nigerian child were compared with United States anthropometric database collected by Snyder, 1977 which formed the basis of US anthropometry used today. Further comparison was also carried out with the dimensions of crash dummies: Hybrid III three-year-old (HIII 3YO) and Q3s dummies in order to determine the validity of using such crash dummies for safety evaluation of cars and child restraint systems (CRS) used for Nigerian children. Anthropometric survey was performed on 30 Nigerian children aged 2.5 to 3.5 years old. Twenty three standard measurements were taken from each child including the weight, height and circumferences etc. Various percentiles mean and standard deviation values were obtained and compared with international database. As observed, the dimensions of three-year-old Nigerian child appeared to be about 25% lower than US data reported by Snyder. Significant difference was also found between the dimensions of three-year-old Nigerian child and crash dummies. This study provides the external dimensions of 3-year-old Nigerian child that could be used for crash dummy and CRS design.

基于在线轨迹优化的运载火箭可重构制导方法

In order to improve the safety and reliability of a launch vehicle, we present a reconfigurable guidance method based on online trajectory optimization for thrust decrease at the ascending stage of the launch vehicle in this paper. We used a multiple shooting method to convert the optimal control problem into a nonlinear programming(NLP) problem. Finally, we used the interior point method to solve the NLP problem. The simulation results show that the method can effectively adapt to thrust decreases by 5% and 10%. This reconfigurable guidance method based on online planning is proposed to realize launch missions under the condition of power descent, thus verifying the feasibility of the method.

Collision mitigation and vehicle transportation safety using integrated vehicle dynamics control systems

The aim of this paper is to investigate the effect of vehicle dynamics control systems （VDCS） on both the collision of the vehicle body and the kinematic behaviour of the ve- hicle＇s occupant in case of offset frontal vehicle-to-vehicle collision. A unique 6-degree-of- freedom （6-DOF） vehicle dynamics/crash mathematical model and a simplified lumped mass occupant model are developed. The first model is used to define the vehicle body crash parameters and it integrates a vehicle dynamics model with a vehicle front-end structure model. The second model aims to predict the effect of VDCS on the kinematics of the occupant. It is shown from the numerical simulations that the vehicle dynamics/crash response and occupant behaviour can be captured and analysed quickly and accurately. Yurthermore, it is shown that the VDCS can affect the crash characteristics positively and the occupant behaviour is improved.

A novel intelligent vehicle risk assessment method combined with multi-sensor fusion in dense traffic environment

Purpose–The purpose of this paper is to accurately capture the risks which are caused by each road user in time.Design/methodology/approach–The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment.Firstly,they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory.This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception.The information of object type,position and velocity was accurately obtained.Then,they conducted several experiments in real dense traffic environment on highways and urban roads,which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios.By analyzing the generation process of traffic risks between vehicles and the road environment,the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.Findings–The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking,and the road traffic risk was described as afield of equivalent force.The results extend the understanding of the traffic risk,which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.Originality/value–This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception.The information of object type,position and velocity was used to reduce erroneous data association between tracks and detections.Then,the authors conducted several experiments in real dense traffic environment on highways and urban roads,which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios.By analyzing the generation process of traffic risks between vehicles and the road environment,the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

Research on Driver Fatigue Early Warning Method Based on ARM

Fatigue driving is one of the important reasons of road traffic accidents, fatigue driving is refers to the driver in a long time continuous driving or physical fatigue condition, and then come into being physiological and psychological function disorder. In order to overcome the limitation of single sensor in the fatigue test, aimed at the requirements of monitoring on the fatigue driving, this article designed an driver fatigue monitor system based ARM926EJ-S as a controller, it is used to determine the driver＇s fatigue and reduce the traffic accident. On the basis of fully considering the source correlation and complementary, it adopts the method of multi-source information fusion; by monitoring the pulse, heart rate, temperature of the human body, steering wheel grip strength to realized the fatigue level. The system of graphical interface adopts UCGUI. Finally, testing the main function modules of early warning system, the feasibility of the proposed early warning system is verified fusion .