Study on the Driving Style Adaptive Vehicle Longitudinal Control Strategy

This paper presents a fusion control strategy of adaptive cruise control(ACC) and collision avoidance(CA),which takes into account a driver’s behavioral style. First, a questionnaire survey was performed to identify driver type, and the corresponding driving behavioral data were collected via driving simulator experiments, which served as the template data for the online identification of driver type. Then, the driveradaptive ACC/CA fusion control strategy was designed, and its effect was verified by virtual experiments. The results indicate that the proposed control strategy could achieve the fusion control of ACC and CA successfully and improve driver adaptability and comfort.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

PERFORMANCE SIMULATION OF VEHICLES EQUIPPED WITH TRACTION DRIVE CVTS

A computer model for the performance simulation of vehicles equipped with traction drive continuously variable transmission （CVT） is presented. The model integrates the traction drive CVT subsystem into an existing overall vehicle system. The characteristics of engine output torque are formulated using neural networks, and torque converter is modeled using lookup tables. Component inputs and outputs are coupled in the dynamic equations and interfaces in the powertrain system. The model simulation can provide evaluation of vehicle performance in drivability, fuel economy and emission levels for various drive ranges prior to the prototyping of the vehicle. As a design tool, the model assists engineers in understanding the effect ofpowertrain components on vehicle performance and making decisions in the selection of key design parameters. The model is implemented in the MATLAB/Simulink environment. The performance simulation of a test vehicle is included as a numerical example to illustrate the effectiveness of the model.

Development of driver-vehicle-road closed-loop semi-physical simulation system

As hybrid vehicles introduced the motor, the vehicle structure has a significant change in the power matching. A driver-vehicle-road closed-loop semi-physical simulation system, which makes real driving parts together with the simulation car, will bring convenience to the new car design. We used the computer software to simulate the road with a slope, curve and some other features based on the actual road condition, and analyzed the whole road scene in addition to geometry and physical characteristics. Analyzing and constructing the vehicle dynamics basic template, appropriate changes to the template can obtain the desired vehicle dynamics model with an external device to control the model vehicle. It combined the physical operation system with visual display, which gave us real driving feelings and increased the vehicle design predictive accuracy.

Impact of binocular visual field loss on driving performance in glaucoma patients

AIM:To evaluate the driving performance in young and middle-aged Chinese glaucoma patients with mild to severe visual field loss compared to those without glaucoma by using a driving simulation test.METHODS:Twenty-nine participants were included in this study:nine patients with glaucoma but pass the binocular Esterman visual field test,ten patients with glaucoma and fail the binocular Esterman visual field test,and ten age-matched healthy controls.A driving simulation test was designed as a frequency-based analysis of a lanekeeping task.The total performance error,the controlresponse amplitude and delay were calculated.RESULTS:Esterman visual field test fail group showed the longest delay of control-response among three groups(P=0.02).And the delay in lane-keeping task was significantly associated with inferior field of better-eye(r=0.51,P=0.004)and integrated visual field(r=0.55,P=0.002).CONCLUSION:Young and middle-aged glaucoma patients with binocular visual field loss suffered from a longer delay of response in driving simulation test,while inferior visual field having more impact than superior visual field.

Dynamics Modeling of Heavy Special Driving Simulator

Based on the dynamical characteristic parameters of the real vehicle, the modehng approach ancl procedure of dynamics of vehicles are expatiated. The layout of vehicle dynamics is proposed, and the sub-models of the diesel engine, drivetrain system and vehicle multi-body dynamics are introduced. Finally, the running characteristic data of the virtual and real vehicles are compared, which shows that the dynamics model is similar closely to the real vehicle system.

A Review on the Development of Vehicle Driving Simulator

With the development of the economy, cars have become the common means of transportation for people, and the safety issues related to this and the new technologies are being taken seriously. Vehicle driving simulator, as a kind of simulation equipment, is mostly used in the research, experiment and development of new technology enterprises, meanwhile, it also can realize simulation of car running performance, driving training, and make users get real driving experience. In this paper, present development situation at home and abroad of vehicle driving simulator, and the species, composition and working principle of vehicle driving simulator are introduced and teviewed. Based on vehicle driving simulator ＂driver-vehicle-road environment＂ in the simulation environment, the dynamic simulation of virtual driving system, visual simulation system, driving simulation of ABS and ESP control were analyzed.

Neural Network-Based State of Charge Estimation Method for Lithium-ion Batteries Based on Temperature

Lithium-ion batteries are commonly used in electric vehicles,mobile phones,and laptops.These batteries demonstrate several advantages,such as environmental friendliness,high energy density,and long life.However,battery overcharging and overdischarging may occur if the batteries are not monitored continuously.Overcharging causesfire and explosion casualties,and overdischar-ging causes a reduction in the battery capacity and life.In addition,the internal resistance of such batteries varies depending on their external temperature,elec-trolyte,cathode material,and other factors;the capacity of the batteries decreases with temperature.In this study,we develop a method for estimating the state of charge(SOC)using a neural network model that is best suited to the external tem-perature of such batteries based on their characteristics.During our simulation,we acquired data at temperatures of 25°C,30°C,35°C,and 40°C.Based on the tem-perature parameters,the voltage,current,and time parameters were obtained,and six cycles of the parameters based on the temperature were used for the experi-ment.Experimental data to verify the proposed method were obtained through a discharge experiment conducted using a vehicle driving simulator.The experi-mental data were provided as inputs to three types of neural network models:mul-tilayer neural network(MNN),long short-term memory(LSTM),and gated recurrent unit(GRU).The neural network models were trained and optimized for the specific temperatures measured during the experiment,and the SOC was estimated by selecting the most suitable model for each temperature.The experimental results revealed that the mean absolute errors of the MNN,LSTM,and GRU using the proposed method were 2.17%,2.19%,and 2.15%,respec-tively,which are better than those of the conventional method(4.47%,4.60%,and 4.40%).Finally,SOC estimation based on GRU using the proposed method was found to be 2.15%,which was the most accurate.

Development of the Driving Simulation System MOVIC-T4 and Its Validation Using Field Driving Data

Underground urban expressways are a possibility for solving many existing transportation-related problems, such as traffic congestion in high density areas and the division of neighborhoods due to elevated roadways. However, they may also pose high risks regarding traffic safety. Therefore, it is important for a pre-analysis of traffic safety to be made. This paper describes recent efforts to develop a driving simulation system, MOVIC-T4, for traffic safety analysis of underground urban expressways. In order to develop a small portable simulator, a small-sized motion-base with two-degrees-of-freedom is used to duplicate acceleration cueing together with a head-mounted-display （HMD） for the visual system. An overview of this system is given and the reliability of driving data obtained from the experiments using MOVIC-T4 is discussed through a validation study using field driving data. The results of validation indicate that the perceived speed distance headway, and physiological data in the simulator show the almost same trend as that in the real world, but larger decelerations tend to be produced in the simulator.

AB095. Development of an assessment system of driver visual behaviours on a car simulator

Background:(I)To describe the development and components of the automobile simulator driving behavior evaluation system developed by CRIR-Institut Nazareth et Louis-Braille;(II)to present the preliminary results of the content evaluation of the driving behavior evaluation grid.Methods:The evaluation system consists of five components:(I)the VS500M Car Simulator(Virage Simulation);(II)four VS500M driving scenarios,modified to minimize the occurrence of simulator sickness and expose subjects to commonly encountered driving situations on highways and city boulevards;(III)the Tobii Pro Glasses 2 eye tracking device;(IV)a car simulator driving behavior observation grid(DBOG);(V)a software application used during the behaviour evaluation phase,where synchronized video tracking,certain data from the simulator(e.g.,speed)and the DBOG grid are presented.Initially,the expected safe driving behaviors were identified,including 235 of a visual nature,supported by literature data and consultation of the project steering committee and an expert in driving assessment.Driving behaviors were assessed in 22 subjects without visual impairment(mean age 55±20 years).Subsequently,the items were revised to determine their relevance based on their importance in terms of road safety or on the frequency with which behaviors were observed among participants.For analysis purpose,the items of the DBOG were grouped according to their content,by type of expected driving behavior(e.g.,following a stop,look to the left and right before crossing the intersection)or element to be detected(e.g.,pedestrians).Results:Some visual behaviors are difficult to observe with the eye tracker device because they are more dependent on peripheral than central vision.Others are rarely observed,possibly because they are little or not realized in daily life or the representation of reality on the simulator does not stimulate their adoption.On the other hand,the visual detection behaviors expected in a situation where safety can be compromised are mostly carried out(e.g.,detection of oncoming vehicles,side mirror verification when changing lanes).Conclusions:This first phase of the study has made possible to better target the items to be kept in the car simulator driving behavior observation grid,and those that will have to be removed as they are too difficult to observe or too rarely adopted by the participants.Content validity and inter-rater reliability will be assessed from the simplified grid.

Drivers’ Reaction of Warning Messages in Work Zone Termination Areas with Left Turn

Work-zone crashes have always drawn public attention. A number of fatalities are recorded every year nationwide within work zone areas. Most existing countermeasures have been dedicated more to the advance warning areas, transition areas, and activity areas of work zone, than the termination areas, where drivers might play less attention to safety threats. In this study, the vehicle-to-vehicle communication based left turn warning system was applied at a work zone termination area, which is immediately followed by a T-intersection. The work-zone is located on the minor road side, while left turn vehicles will be appearing from the major street through the said T-intersection. A smart phone application was designed using Android coding system to provide several types of warning messages to drivers. Corresponding scenarios were designed in a driving simulator, and 20 subjects were recruited to participate in the simulation test followed by a questionnaire survey. The subjects received a warning message when driving to the termination area of a work zone on the coming left turn vehicles. Twenty test drivers’ driving speed, acceleration rates, and break reaction distance to the warning messages were studied in four different scenarios. Results show that the smartphone application has a great impact on driving behaviors, especially the female voice and the beep tone warning, which are recommended for possible field tests. Besides, the developed smartphone applications can be further updated for practical applications of similar needs.

Intelligent speed adaptation for visibility technology affects drivers’speed selection along curves with sight limitations

Sight obstructions along road curves can lead to a crash if the driver is not able to stop the vehicle in time.This is a particular issue along curves with limited available sight,where speed management is necessary to avoid unsafe situations(e.g.,driving off the road or invading the other traffic lane).To solve this issue,we proposed a novel intelligent speed adaptation(ISA)system for visibility,called V-ISA(intelligent speed adaptation for visibility).It estimates the real-time safe speed limits based on the prevailing sight conditions.V-ISA comes with three variants with specific feedback modalities(1)visual and(2)auditory information,and(3)direct intervention to assume control over the vehicle speed.Here,we investigated the efficiency of each of the three V-ISA variants on driving speed choice and lateral behavioural response along road curves with limited and unsafe available sight distances,using a driving simulator.We also considered curve road geometry(curve direction:rightward vs.leftward).Sixty active drivers were recruited for the study.While half of them(experimental group)tested the three V-ISA variants(and a V-ISA off condition),the other half always drove with the V-ISA off(validation group).We used a linear mixed-effect model to evaluate the influence of V-ISA on driver behaviour.All V-ISA variants were efficient at reducing speeds at entrance points,with no discernible negative impact on driver lateral behaviour.On rightward curves,the V-ISA intervening variant appeared to be the most effective at adapting to sight limitations.Results of the current study implies that V-ISA might assist drivers to adjust their operating speed as per prevailing sight conditions and,consequently,establishes safer driving conditions.

Assessment of driver compliance on roadside safety signs with auditory warning sounds generated from pavement surfaceea driving simulator study

A variety of word messages are used in highways in different forms to inform drivers of traffic safety information or to influence positively drivers＇ behavior. These include direct word messages for a particular event （such as road work） or general safety messages that warn drivers of risky driving behaviors （such as distracted driving and speeding）. However, it is often observed that many drivers even do not recognize the safety messages despite being displayed on roadside signs in a fairly good visibility condition. The present study focused on an engineering method, namely auditory warning sound （AWS）, which calls driver＇s attention on driving tasks and helps them comply with roadside safety signs. A driving simulator experiment was conducted to assess effects of AWS on driver compliance to roadside safety signs. AWS was implemented into driving simulator scenarios as a parameter to generate a certain level of growling warning sounds when subject vehicles are entering within a legi- bility distance of a roadside safety sign. The present study described laboratory setup and data for the driving simulator experiment, and drew conclusions on driver compliance to roadside safety signs with and without presence of AWS. The experiment results show that drivers are more compliant to roadside safety signs when AWS is used. It is expected that AWS will greatly help drivers comply with roadside safety signs where a specific safety concern is raised, such as a work-zone or a drowsy driving advisory zone.

Behavioral adaptation of drivers when driving among automated vehicles

Purpose–This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles(AVs)compared to driving among manually driven vehicles(MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic situations.Here,mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional MVs.Design/methodology/approach–A driving simulator study is designed to explore whether such behavioral adaptations exist.Two different driving scenarios were explored on a three-lane highway:driving on the main highway and merging from an on-ramp.For this study,18 research participants were recruited.Findings–Behavioral adaptation can be observed in terms of car-following speed,car-following time gap,number of lane change and overall driving speed.The adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or MVs.Although significant differences in behavior were found in more than 90%of the research participants,they adapted their behavior differently,and thus,magnitude of the behavioral adaptation remains unclear.Originality/value–The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding vehicles.This finding differs from previous studies,which have shown that drivers tend to adapt their behaviors with respect to the surrounding vehicles.Furthermore,the surrounding vehicles in this study are more“free flow’”compared to previous studies with a fixed formation such as platoons.Nevertheless,long-term observations are required to further support this claim.

Research on the classification for road traffic visibility based on the characteristics of driving behaviour–a driving simulator experiment

Purpose–The purpose of this paper is to performfine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions.Design/methodology/approach–A driving simulator experiment was conducted to collect data of speed and lane position.ANOVA was used to explore the difference in driving behavior under different visibility conditions.Findings–The results show that only average speed is significantly different under different visibility conditions.With the visibility reducing,the average vehicle speed decreases.The road visibility conditions in a straight segment can be divided intofive levels:less than 20,20-30,35-60,60-140 and more than 140 m.The road visibility conditions in a curve segment can be also divided into four levels:less than 20,20-30,35-60 and more than 60 m.Originality/value–Afine classification of road traffic visibility has been performed,and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

Evaluation of fog warning system on driving under heavy fog condition based on driving simulator

Purpose–Heavy fog results in low visibility,which increases the probability and severity of traffic crashes,and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers.This paper aims at exploring the effects of dynamic message sign(DMS)of fog warning system on driver performance.Design/methodology/approach–First,a testing platform was established based on driving simulator and driver performance data under DMS were collected.The experiment route was consisted of three different zones(i.e.warning zone,transition zone and heavy fog zone),and mean speed,mean acceleration,mean jerk in the whole zone,ending speed in the warning zone and transition zone,maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected.Next,the one-way analysis of variance was applied to test the significant difference between the metrics.Besides,drivers’subjective perception was also considered.Findings–The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone.Besides,when drivers enter a heavy fog zone,DMS can reduce the tension of drivers and make drivers operate more smoothly.Originality/value–This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform.The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

Evaluation of intersection conflict warning system at unsignalized intersections:A review

Unsignalized intersections are identified as the critical locations due to higher number of road crashes at these locations.The primary causes of crashes at unsignalized intersections are limited sight distance,incorrect assessment of gaps by drivers on the minor road,and higher speeds of vehicles on the major road.In an effort to improve safety and reduce the severity of crashes at unsignalized intersections,an intelligent transportation system(ITS)called the intersection conflict warning system(ICWS)has been developed.The ICWS consists of an activated warning sign and sensors that detect vehicles approaching the intersection.This paper aims to summarize the performance evaluation of ICWS that has been published in the literature.The review commences with an overview of the purpose of designing and installing ICWS at unsignalized intersections.It then discusses driving performance measures considered to evaluate the effectiveness of ICWS in three different environments,i.e.,real world,driving simulator,and simulations,and their results are presented.The paper also discusses the type of sensors used to detect vehicles approaching the intersection and their accuracy in vehicle detection.The results reveal that ICWS had substantially improved driver behaviour.In the presence of ICWS,drivers resulted in shorter reaction time,lower approach speed,increased critical gap acceptance,and reduction in conflicts.An improvement in the performance of ICWS can be achieved by educating drivers about the sign,maintaining system reliability,and further examining the effect of various traffic factors,driver factors,and environmental factors on ICWS.The findings of this study can help researchers and engineers to design a better ICWS that can greatly enhance driving performance and safety at unsignalized intersections.

Ethical decision-making in older drivers during critical driving situations: An online experiment

The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios.204 participants from North America,grouped into two age groups(18–30 years and 65 years and above),were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem.Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment.Bayesian hierarchical models were used to analyze participants’responses,response time,and acceptability of utilitarian ethical decision-making.The results showed significant pedestrian placement,age,and time-to-collision(TTC)effects on participants’ethical decisions.When pedestrians were in the right lane,participants were more likely to switch lanes,indicating a utilitarian approach prioritizing pedestrian safety.Younger participants were more likely to switch lanes in general compared to older participants.The results imply that older drivers can maintain their ability to respond to ethically fraught scenarios with their tendency to switch lanes more frequently than younger counterparts,even when the tasks interacting with an automated driving system.The current findings may inform the development of decision algorithms for intelligent and connected vehicles by considering potential ethical dilemmas faced by human drivers across different age groups.

Modelling lane-changing execution behaviour in a connected environment:A grouped random parameters with heterogeneity-in-means approach

Lane-changing is performed either to follow the route to a planned destination(i.e.,mandatory lane-changing)or to achieve better driving conditions(i.e.,discretionary lane-changing).A connected environment is expected to assist during lane-changing manoeuvres,but it is not known well how driving aids in a connected environment assist lane-changing execution.As such,this study investigates the impact of a connected environment on lanechanging execution time during mandatory and discretionary lane-changing manoeuvres.To this end,this study designed an advanced driving simulator experiment where 78 drivers performed these manoeuvres on a simulated motorway in three randomised driving conditions.The conditions were baseline(without driving aids),a fully functioning connected environment with a perfect supply of driving aids,and an impaired connected environment with delayed driving aids.The lane-changing execution time has been modelled by a random parameters hazard-based duration modelling approach,which accounts for the panel nature of data and captures the unobserved heterogeneity.Results suggest that,compared to the baseline condition(i.e.,a non-connected environment),most of the drivers in the connected environment take more time to complete their lane-changing manoeuvres,indicating drivers’safer lane-changing execution behaviour in the connected environment.The communication delay driving condition has been found to have more deteriorating effects on mandatory lanechanging manoeuvres than discretionary lane-changing manoeuvres.This study concludes that(i)the connected environment increases safety margin during both lane-changing manoeuvres,and(ii)a higher magnitude of safety margin is observed during mandatory lane-changing manoeuvres whereby drivers have a higher need for assistance.

Experimental and Numerical Study of Cervical Muscle Contraction in Frontal Impact

In a crash situation,drivers typically make evasive maneuvers before an upcoming impact,which can affect the kinematics and injury during impact.The purpose of the current study was to investigate the response and effect of drivers’cervical muscles in a frontal impact.A crash scenario was developed using a vehicle driving simulator,and 10 volunteers were employed to drive the simulator at 20 km/h,50 km/h,80 km/h and 100 km/h.Electromyography(EMG)was recorded from the sternocleidomastoideus(SCM),splenius cervicis(SPL)and trapezium(TRP)muscles using a data acquisition system,and the level of muscle activation was calculated.A numerical study was conducted using data collected in the experiment.The results revealed that the cervical muscles were activated during drivers’protective action.EMG activity of cervical muscles before impact was greater than that during normal driving.EMG activity increased with driving speed,with the SCM and TRP exhibiting larger increases than the SPL.The kinematics and load of the driver were influenced by muscle activation.Before the collision,the head of an active model stretched backward,while the passive model kept the head upright.In low-speed impact,the torque and shear of the cervical muscle in the active model were much lower than those in the passive model,while the tension of the cervical muscle was higher in the active model compared with the passive model.The results indicated that the incidence of cervical injury in high-speed impact is complex.