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Technical Paper

Parking slots allocation for multiple autonomous valet parking vehicles

2022-03-29
2022-01-0148
Although autonomous valet parking technology can replace the driver to complete the parking operation, it is easy to cause traffic chaos in the case of lack of scheduling of multiple parking agents, especially when multiple cars compete for the same parking slot at the same time. Therefore, in order to ensure orderly traffic and parking safety, it is necessary to allocate parking slots reasonably for multiple autonomous valet parking vehicles. The parking slots allocation model is built as an optimization problem with constraints. Both parking mileage cost and parking difficult cost are considering at the objective function of the optimization problem. There are three types of constraints. The first is the capacity limit of a single parking slot, the second is the space limit occupied by a single vehicle, and the third is the total capacity limit of the parking lot. After establishing parking slots allocation model, the immune algorithm is coded to solve the problem.
Technical Paper

Research on Engine Compartment Thermal Management Based on STAR-CCM+ software

2022-03-29
2022-01-0184
Nowadays, energy conservation and emission reduction have raised the awareness of more and more people. The heat dissipation of the engine compartment is an important evaluation index for automobile thermal management, which directly affects the vehicle's power, economy, durability and riding comfort. In this paper, aiming at the problem of unsatisfactory thermal management effect of a certain passenger car engine compartment, the systematic model of engine compartment thermal management is used to carry out research and program optimization. Based on the STAR-CCM+ software, we discuss the distribution law of the speed field and pressure of the engine compartment, and the influence of the front frame baffle on the flow field. The longitudinal position of the oil cooler was investigated for the cooling module, and it was found that the block position of the oil cooler has a certain degree of influence on the heat dissipation of the radiator.
Technical Paper

Field Experimental Investigation On Human Thermal Comfort In Vehicle Cabin

2022-03-29
2022-01-0195
With the popularization of automobiles, people’s driving time increases gradually. However, the accompanying problem is that the interior space of the vehicle passenger compartment is narrow and relatively closed. If drivers and passengers are permanently in the uncomfortable passenger compartment, they will feel tired, agitated, inattention, etc., which is prone to traffic accidents. This makes people gradually improve the requirements of driving comfort. And thermal comfort is an important aspect of vehicle comfort, which is closely related to the energy consumption of air conditioning. The thermal environment in the vehicle passenger compartment is a special non-uniform thermal environment. However, due to the complexity of the thermal environment inside the automobile, the basic research on human thermal comfort in the non-uniform thermal environment is carried out in the building environment.
Technical Paper

Path Planning Method for Perpendicular Parking based on Vehicle Kinematics Model using MPC Optimization

2022-03-29
2022-01-0085
In recent years, intelligent driving technology is being extensively studied. This paper proposes a path planning method for perpendicular parking based on vehicle kinematics model using MPC optimization, which aims to solve the perpendicular parking task. Firstly, in the case of any initial position and orientation of the vehicle, judging whether the vehicle can be parked at one step according to the location of the parking place and the width of the lane, and then calculating the starting position for parking, and use the Bezier curve to connect the initial position and the starting position. Secondly, reference parking path is calculated according to the collision constraints of the parking space. Finally, because the parking path based on the vehicle kinematics model is composed of circle arcs and straight lines, the curvature of the path is discontinuous. The reference parking path is optimized using Model Predictive Control (MPC).
Technical Paper

Parking Planning with Genetic Algorithm for Multiple Autonomous Vehicles

2022-03-29
2022-01-0087
The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem.
Technical Paper

An Optimized Design of Multi-Chamber Perforated Resonators to Attenuate Turbocharged Intake System Noise

2021-04-06
2021-01-0669
The turbocharger air intake noise during transient conditions like wide open throttle and tip-in/out affects the passenger ride comfort. This paper aims to study an optimized design of multi-chamber perforated resonators to attenuate this noise. The noise produced by a turbocharger in a test vehicle has been measured to find out the noise spectral characteristics which can be used to design the acoustic targets including the amplitude and frequency range of transmission loss (TL). The structural parameters of the resonators are optimized based on genetic algorithm (GA) and two-dimensional prediction theory of the resonator TL. The optimized resonators are installed on the test vehicle to verify the actual noise reduction effect. The results suggest that the broadband noise has been eliminated, and subjective feelings are greatly improved.
Technical Paper

Reward Function Design via Human Knowledge Graph and Inverse Reinforcement Learning for Intelligent Driving

2021-04-06
2021-01-0180
Motivated by applying artificial intelligence technology to the automobile industry, reinforcement learning is becoming more and more popular in the community of intelligent driving research. The reward function is one of the critical factors which affecting reinforcement learning. Its design principle is highly dependent on the features of the agent. The agent studied in this paper can do perception, decision-making, and motion-control, which aims to be the assistant or substitute for human driving in the latest future. Therefore, this paper analyzes the characteristics of excellent human driving behavior based on the six-layer model of driving scenarios and constructs it into a human knowledge graph. Furthermore, for highway pilot driving, the expert demo data is created, and the reward function is self-learned via inverse reinforcement learning. The reward function design method proposed in this paper has been verified in the Unity ML-Agent environment.
Technical Paper

Optimization of Speed Fluctuation of Internal Combustion Engine Range Extender by a Dual Closed-Loop Control Strategy

2021-04-06
2021-01-0782
With the increasing concern on environmental pollution and CO2 emission all over the world, range-extended electrical vehicle (REEV) has gradually got more attention because it could avoid the mileage anxiety of the battery electrical vehicles (BEV) and get high energy efficiency. Nevertheless, NVH performance of internal combustion engine range extender (ICRE) is a critical problem that affects the driving experiences for REEV. In this paper, a two-cylinder PFI gasoline engine and a permanent magnet synchronous motor (PMSM) are coaxially mounted to run as an ICRE. The ICRE control system was established based on Compact RIO hardware and LabVIEW, who has the functions of the intake throttle PID closed-loop control, autonomous ICRE operation control, and speed PID closed-loop control. In this paper, the gasoline engine was first driven to the idle condition by PMSM in speed-control mode.
Technical Paper

IMM-KF Algorithm for Multitarget Tracking of On-Road Vehicle

2020-04-14
2020-01-0117
Tracking vehicle trajectories is essential for autonomous vehicles and advanced driver-assistance systems to understand traffic environment and evaluate collision risk. In order to reduce the position deviation and fluctuation of tracking on-road vehicle by millimeter-wave radar (MMWR), an interactive multi-model Kalman filter (IMM-KF) tracking algorithm including data association and track management is proposed. In general, it is difficult to model the target vehicle accurately due to lack of vehicle kinematics parameters, like wheel base, uncertainty of driving behavior and limitation of sensor’s field of view. To handle the uncertainty problem, an interacting multiple model (IMM) approach using Kalman filters is employed to estimate multitarget’s states. Then the compensation of radar ego motion is achieved, since the original measurement is under the radar polar coordinate system.
Technical Paper

Optimized Control of Dynamical Engine-Start Process in a Hybrid Electric Vehicle

2020-04-14
2020-01-0268
Engine start while driving is one of the most typical and frequent work conditions for hybrid vehicles. Engine start has very significant impact on the driving comfort. Engine start, especially a dynamical engine start, have high control requirements regarding control time, torque output and riding comfort. In some hybrid transmissions such as P2, engine is cranked and synchronized through wet clutch slipping. Because clutch pressure control has time-varying delay and estimation precision of engine torque by ECU (Engine Control Unit) is poor, conventional PID controller is unable to meet the high requirements of control quality. A new control algorithm is proposed in this paper to cope with all these challenges. The new control algorithm is based on LADRC (Linear Active Disturbance Rejection Controller) and is improved through combination with Smith predictor and Adaline network. LADRC is adopted to reduce negative effects of poor precision of engine torque.
Journal Article

Nonlinear Model Predictive Control of Autonomous Vehicles Considering Dynamic Stability Constraints

2020-04-14
2020-01-1400
Autonomous vehicle performance is increasingly highlighted in many highway driving scenarios, which leads to more priorities to vehicle stability as well as tracking accuracy. In this paper, a nonlinear model predictive controller for autonomous vehicle trajectory tracking is designed and verified through a real-time simulation bench of a virtual test track. The dynamic stability constraints of nonlinear model predictive control (NLMPC) are obtained by a novel quadrilateral stability region criterion instead of the conventional phase plane method using the double-line region. First, a typical lane change scene of overtaking is selected and a new composited trajectory model is proposed as a reference path that combines smoothness of sine wave and comfort of linear functional path. Reference lateral velocity, azimuth angle, yaw rate, and front wheel steering angle are subsequently taken into account.
Technical Paper

Prediction Model of Driving Range of Electric Vehicle Based on Driver’s Driving Behavior

2019-11-04
2019-01-5058
Aiming at the problem of "mileage anxiety" caused by the inaccurate estimation of vehicle owners due to the complicated and changeable actual driving conditions, the current study of electric driving range prediction focuses on exploring the battery parameters or fitting the linear relationship between electric vehicle SOC (state of charge) and driving range under ideal conditions of experiments or software simulation, which ignores the actual vehicle driving conditions and the difference in driving range due to differences in driver's driving behaviors. This paper puts forward an innovative prediction model of the driving mileage of pure electric vehicles based on driver's driving behavior.
Technical Paper

Analysis of the Driver’s Breaking Response in the Safety Cut-in Scenario Based on Naturalistic Driving

2019-11-04
2019-01-5053
For the personification of automotive vehicle function performance under common traffic scenarios, analysis of human driver behavior is necessary. Based on China Field Operational Test (China-FOT) database of China Natural Driving Study project, this paper studies the driver's response in the common cut-in scenario. A total of 266 cut-in cases are selected by manual interception of driving recorder video. The relevant traffic environment characteristics are also extracted from video, including light conditions, road conditions, scale and lateral position of cut-in vehicle, etc. Dynamic information is decoded form CAN, such as speed, acceleration and so on. Then image processing results, such as relative speed and distance of cut-in and subject vehicles, are calculated. Statistical results based on above information show the response type and distribution of human driver: the behavior of keeping lane is 96.24%, in which the ratio of braking response is 51.13%.
Technical Paper

Adaptive Design of Driver Steering Override Characteristics for LKAS

2019-11-04
2019-01-5030
Lane Keeping Assistance System (LKAS) is a typical lateral driver assistance system with low acceptance. One of the main reasons is that fixed parameters cannot satisfy individual differences. So LKAS adaptive to driver characteristics needs to be designed. Driver Steering Override (DSO) process is an important process of LKAS. It happens when contradiction between driver’s intention and system behavior occurs. As feeling of overriding will affect the overall experience of using LKAS, the design of DSO characteristics is worthy of attention. This research provided an adaptive design scheme aiming at DSO characteristics for LKAS by building Driver Preference Model (DPM) based on simulator test data from preliminary experiments. The DPM was to represent the relationship between driver characteristics indices and driver preferred system characteristics indices. So that new drivers’ preference can be predicted by DPM based on their own daily driving data with LKAS switched off.
Technical Paper

Naturalistic Driving Behavior Analysis under Typical Normal Cut-In Scenarios

2019-04-02
2019-01-0124
Cut-in scenarios are common and of potential risk in China but Advanced Driver Assistant System (ADAS) doesn’t work well under such scenarios. In order to improve the acceptance of ADAS, its reactions to Cut-in scenarios should meet driver’s driving habits and expectancy. Brake is considered as an express of risk and brake tendency in normal Cut-in situations needs more investigation. Under critical Cut-in scenarios, driver tends to brake hard to eliminate collision risk when cutting in vehicle right crossing lane. However, under less critical Cut-in scenarios, namely normal Cut-in scenarios, driver brakes in some cases and takes no brake maneuver in others. The time when driver initiated to brake was defined as key time. If driver had no brake maneuver, the time when cutting-in vehicle right crossed lane was defined as key time. This paper focuses on driver’s brake tendency at key time under normal Cut-in situations.
Technical Paper

Driver Behavior Classification under Cut-In Scenarios Using Support Vector Machine Based on Naturalistic Driving Data

2019-04-02
2019-01-0136
Cut-in scenario is common in traffic and has potential collision risk. Human driver can detect other vehicle’s cut-in intention and take appropriate maneuvers to reduce collision risk. However, autonomous driving systems don’t have as good performance as human driver. Hence a deeper understanding on driving behavior is necessary. How to make decisions like human driver is an important problem for automated vehicles. In this paper, a method is proposed to classify the dangerous cut-in situations and normal ones. Dangerous cases were extracted automatically from naturalistic driving database using specific detection criteria. Among those cases, 70 valid dangerous cut-in cases were selected manually. The largest deceleration of subject vehicle is over 4 m/s2. Besides, 249 normal cut-in cases were extracted by going through video data of 2000km traveled distance. In normal driving cases, subject vehicle may brake or keep accelerating and the largest deceleration was less than 3 m/s2.
Technical Paper

Research and Development of an Electromagnetic Actuated Active Suspension

2019-04-02
2019-01-0858
Active suspension could achieve good ride comfort and road holding performance. Traditional active suspension which utilizes air actuator or hydraulic actuator features relatively slow response or high energy consumption. Utilizing Permanent Magnet Synchronous Motor (PMSM) as actuator, the Electromagnetic Actuated Active Suspension (EAAS) benefits quick response and energy harvesting from vibration at the same time. Benchmarked with luxury cars available on the market, design parameters and design boundary are determined. A mechanism includes push bar and bell crank is designed to transfer the rotary motion of PMSM into linear motion of suspension, or verse vice. A prototype of EAAS is built in compromise of limited budget and a test bench is designed and set up. Different from conventional quarter car model, the model of EAAS in this paper is investigated and the total inertial of PMSM, gearbox and suspension control arms are calculated and simplified as an equivalent mass.
Technical Paper

A Steerable Curvature Approach for Efficient Executable Path Planning for on-Road Autonomous Vehicle

2019-04-02
2019-01-0675
A rapid path-planning algorithm that generates drivable paths for an autonomous vehicle operating in structural road is proposed in this paper. Cubic B-spline curve is adopted to generating smooth path for continuous curvature and, more, parametric basic points of the spline is adjusted to controlling the curvature extremum for kinematic constraints on vehicle. Other than previous approaches such as inverse kinematics, model-based prediction postprocess approach or closed-loop forward simulation, using the kinematics model in each iteration of path for smoothing and controlling curvature leading to time consumption increasing, our method characterized the vehicle curvature constraint by the minimum length of segment line, which synchronously realized constraint and smooth for generating path. And Differ from the path of robot escaping from a maze, the intelligent vehicle traveling on road in structured environments needs to meet the traffic rules.
Technical Paper

Analysis of the Correlation between Driver's Visual Features and Driver Intention

2019-04-02
2019-01-1229
Driver behaviors provide abundant information and feedback for future Advanced Driver Assistance Systems (ADAS). Driver’s eye and head may present some typical movement patterns before executing driving maneuvers. It is possible to use driver’s head and eye movement information for predicting driver intention. Therefore, to determine the most important features related to driver intention has attracted widespread research interests. In this paper, a method to analyze the correlation between driver’s visual features and driver intention is proposed, aiming to determine the most representative features for driver intention prediction. Firstly, naturalistic driving experiment is conducted to collect driver’s videos during executing lane keeping and lane change maneuvers. Then, driver’s head and face visual features are extracted from those videos. By using boxplot and independent samples T-test, features which have significant correlation with driver intention are found.
Technical Paper

Analysis of Human Machine Interaction Program in Lane Keeping Assist System Based on Field Test

2018-08-07
2018-01-1632
Lane-keeping assist system (LKA) alerts the driver or intervenes in the driving when the vehicle deviates from the lane. But its effect is highly dependent on the driver’s acceptance. Distance to Lane Crossing (DTLC) and Time to Lane Crossing (TTLC) are two important factors to consider the danger level of the scenario, which are also two references for drivers to make decisions. At present, most of the functional design standards are based on these values, while they often differ for different vehicle movements. This study uses a driving robot to precisely control the test conditions and performs field tests on two advanced autonomous vehicles in National Intelligent Connected Vehicle (Shanghai) Pilot Zone. The test conditions are extended based on various test standards and the LKA performance of vehicles in the pre-experiment.
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