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Technical Paper

Lateral Control Method of Intelligent Vehicles Based on Image Segmentation

2018-08-07
2018-01-1596
With the rapid development of automotive industry, the intelligent vehicles that can be viewed as the integrated carrier of advanced technology of automobile are paid much attention by society. It is imperative to study the motion control of the intelligent vehicles due to the nature of their nonholonomic operation constraint system whose dynamic characteristics are highly nonlinear with the uncertainty of parameters. In this paper, utilizing the vision system of intelligent vehicles, a vehicle lateral control strategy based on image segmentation is established to enhance the vehicle’s capability to predict future behavior and deal with unexpected situations. Applying the image recognition and tracking results of the visual system, the breadth and depth of the vision are divided into three-dimensional segmentation where each block is given different weights.
Technical Paper

Robust Multi-Target Tracking Algorithm Based on Automotive Millimeter-Wave Radar

2018-08-07
2018-01-1601
Automotive radar can be used to detect pedestrians and vehicles and keep stable tracking of the targets. Multi-targets tracking is the key techniques when tracking in the complicated road condition. Some targets may lose alarm and there may be some false targets among the measurement because the radar would be affected seriously in the complicated road condition especially by the clutter and multipath effect. Tracking can solve the effect of the false targets to a certain extent and provide a stable and accurate state of the targets. How to associate the track and the measurement is important in multi-targets tracking system. A robust tracking algorithm using joint integrated probabilistic data association and interactive multi-model (JIPDA-IMM) is proposed. Unlike the nearest neighbor method, all the possible combinations of track measurement assignments are considered and the probabilities of the joint events are calculated.
Technical Paper

Passenger Car 25% Overlapping Collision Accident Study Base on CIDAS

2018-08-07
2018-01-1595
With the development of vehicle technologies, vehicle safety is much better than before, many companies put research focus on harder accident scenarios. The 25% overlapping collision is considered as one type of most dangerous collision, this paper study this type accidents base on CIDAS database. Paper showed 7 scenarios appeared frequency in China, 11, 12, 1 o’clock are main impact direction. High way and freeway are the main places, and the head, thorax and lower extremities were the main sites of injury.
Technical Paper

Research on the Development Trend of Brain Controlled Cars

2018-08-07
2018-01-1587
This paper studies the development trend of the brain controlled cars. A brain controlled car is a new application of the brain-computer interface (BCI) to the on-road motor vehicles. As a new frontier science, the relevant studies are exploratory and still at an early stage. The prospect of the brain controlled cars is also unclear. In this paper, we summarizes the research status of the brain controlled cars based on both the academic articles and publicly released demo cars. The research history, the achievable control functions, the vehicle types that implemented on, the testing scenarios and the technology roadmaps are elaborated. According to the development traces of both the intelligent connected vehicle (ICV) and the artificial intelligence (AI) technologies, we predicted the development trend of the brain controlled cars.
Technical Paper

Research on Variable Steering Ratio Control Strategy of Steer-by-Wire System

2018-08-07
2018-01-1583
In this paper, the variable steering ratio control strategies under normal driving conditions and emergency driving conditions were proposed. The variable steering ratio control under normal driving conditions is based on variable yaw rate gain, and takes into account the driver’s operating habits and vehicle handling stability. The steering ratio varies with the vehicle speed and the steering wheel angle, which ensures the vehicle steering sensitivity at low speed and the steering stability at high speed. The variable steering ratio control under the emergency driving conditions is based on yaw rate dynamic feedback control, and the steering ratio varies with the vehicle movement status. We use active steering control which is based on active disturbance rejection control to achieve yaw rate dynamic feedback control, which can improve vehicle stability without affecting the longitudinal movement of vehicle.
Technical Paper

Velocity Trajectory Planning for Energy Savings of an Intelligent 4WD Electric Vehicle Using Model Predictive Control

2018-08-07
2018-01-1584
To reduce the fuel consumption of an intelligent four-wheel-drive (4WD) electric vehicle (EV), this paper presents a new method of speed trajectory planning. The proposed method can realize a fast real-time optimization of vehicle speed, aiming to achieve the minimum motor energy output according to the fuel consumption directly. In addition, the optimization method maintains the cruising speed within the deviation required to achieve a good control effect. First, the road slope information is considered, and then, a 4WD EV longitudinal dynamic prediction model and a fuel consumption function are established. Next, the state and control variables are chosen to establish the cost function; in this manner, the MPC optimization problem in each prediction horizon is transformed into quadratic form. Finally, the fast solving tool called GRAMPC is used to solve the MPC problem.
Technical Paper

Study on Important Indices Related to Driver Feelings for LKA Intervention Process

2018-08-07
2018-01-1586
Lane Keeping Assistance (LKA) system is a very important part in Advanced Driver Assistance Systems (ADAS). It prevents a vehicle from departing out of the lane by exerting intervention. But an inappropriate performance during LKA intervention makes driver feel uncomfortable. The intervention of LKA can be divided into 3 parts: intervention timing, intervention process and intervention ending. Many researches have studied about the intervention timing and ending, but factors during intervention process also affect driver feelings a lot, such as yaw rate and steering wheel velocity. To increase driver’s acceptance of LKA, objective and subjective tests were designed and conducted to explore important indices which are highly correlated with the driver feelings. Different kinds of LKA controller control intervention process in different ways. Therefore, it’s very important to describe the intervention process uniformly and objectively.
Technical Paper

A Path Planning Method Based on Large Amount of Artificial Driving Trajectories

2018-08-07
2018-01-1588
In recent years, autonomous vehicles have become the focus of research, among them, path planning is one of the key points. How to plan a trajectory in line with human driving habits in a complex traffic scenario is a concern of automatic driving agencies. Only if the trajectory closer to the driving habits of humankind, will people sitting in the car feel more stable and comfortable and there is no sense of difference with their own driving. To achieve this, this paper presents a method based on large amount of artificial driving trajectory generation planning path, combined with high-precision map and manual driving trajectory, through the road segment, standardization of road segments and building cell path sets, to obtain the optimal path. As the planning experiment of at the end of this paper shows, the results of our routing experiment at the roundabout show the effectiveness of our method.
Technical Paper

Evaluation and Optimization of Driver Steering Override Strategy for LKAS Based on Driver’s Acceptability

2018-08-07
2018-01-1631
In order to satisfy design requirements of Lane Keeping Assistance System (LKAS), a Driver Steering Override (DSO) strategy is necessary for driver’s interaction with the assistance system. The assistance system can be overridden by the strategy in case of lane change, obstacle avoidance and other emergency situations. However, evaluation and optimization of the DSO strategy for LKAS cannot easily be completed quantitatively considering driver’s acceptability. In this research, firstly subjective and objective evaluation experiment is designed. Secondly, correlations between the subjective and the objective evaluation results are established by using regression analysis. Finally, based on the correlations established previously, the optimal performance of DSO strategy is obtained by setting the desired comprehensive evaluation ratings as the optimized goal.
Technical Paper

Developmental Driver Model for Long Vehicles Based on Preview-Follower Theory

2018-08-07
2018-01-1629
A long vehicle is more difficult to drive than a short one, but the mechanism of this phenomenon is still ambiguous. This paper will devote main effort to elaborate this phenomenon based on the theory of preview-follower driver model. Drivers always hope that the vehicle center can travel according to a predetermined trajectory. However, there is often a deviation between the vehicle center predicted by the driver and the actual center. As for this phenomenon, a conception of driver preview eccentricity is proposed. In order to analyze the influence of the proposed conception on vehicle driving track, a multi-axle steering vehicle model is built and some basic expressions of important parameters are deduced from this model firstly. Then, the developmental driver model with the factor of preview eccentricity based on preview-follower theory is established in the state of low velocity quasi-static. Subsequently, this model for long vehicles is extended to a dynamic driver model.
Technical Paper

Critical Driving Scenarios Extraction Optimization Method Based on China-FOT Naturalistic Driving Study Database

2018-08-07
2018-01-1628
Due to the differences in traffic situations and traffic safety laws, standards for extraction of critical driving scenarios (CDSs) vary from different countries and areas around the world. To maintain the characteristic variables under the Chinese typical CDSs, this paper uses the three-layer detection method to extract and detect CDSs in the Natural Driving Data from China-FOT project which executing under the real traffic situation in China. The first layer of detection is mainly based on the feature distributions which deviate from normal driving situations. These distributions associated with speed and longitudinal acceleration/lateral acceleration/yaw rate also quantify the critical levels classification.
Technical Paper

Driver Risk Perception Model under Critical Cut-In Scenarios

2018-08-07
2018-01-1626
In China Cut-in scenarios are quite common on both highway and urban road with heavy traffic. They have a potential risk of rear-end collision. When facing a cutting in vehicle, driver tends to brake in most case to reduce collision risk. The timing and dynamic characteristics of brake maneuver are indicators of driver subjective risk perception. Time to collision (TTC) and Time Headway (THW) demonstrate objective risk. This paper aims at building a model quantitatively revealing the relationship between drivers’ subjective risk perception and objective risk. A total of 66 valid critical Cut-in cases was extracted from China-FOT, which has a travel distance of about 130 thousand miles. It is found that under Cut-in scenarios, driver tended to brake when the cutting in vehicle right crossing line. This time point was defined as initial brake time. Brake strength and brake speed were taken to describe brake maneuver.
Technical Paper

Study on Lane Change Trajectory Planning Considering of Driver Characteristics

2018-08-07
2018-01-1627
Automatic lane change of intelligent vehicles is a complex process. Besides of safety, feelings of the driver and passengers during the lane change are also very important. In this paper, a lane change trajectory planner is designed to generate an ideal collision-free trajectory to satisfy the driver’s preference. Various lane changing modes, gentle lane change, general lane change, radical lane change and personalized lane change, are designed to meet the needs of different passengers on vehicles simultaneously. In this paper, the condition of the two-lane change is studied. One vehicle is in front of the ego vehicle at the same lane and one is at the rear of the ego vehicle at the target lane. A trajectory planning method is then established based on constant speed offset and sine curve, vehicle distances and speed difference, etc. The key factors which can reflect drivers’ lane change characteristics are then acquired.
Technical Paper

Embedding CNN-Based Fast Obstacles Detection for Autonomous Vehicles

2018-08-07
2018-01-1622
Forward obstacles detection is one of the key tasks in the perception system of autonomous vehicles. The perception solution differs from the sensors and the detection algorithm, and the vision-based approaches are always popular. In this paper, an embedding fast obstacles detection algorithm is proposed to efficiently detect forward diverse obstacles from the image stream captured by the monocular camera. Specifically, our algorithm contains three components. The first component is an object detection method using convolution neural networks (CNN) for single image. We design a detection network based on shallow residual network, and an adaptive object aspect ratio setting method for training dataset is proposed to improve the accuracy of detection. The second component is a multiple object tracking method based on correlation filter for the adjacent images.
Technical Paper

Targets Location for Automotive Radar Based on Compressed Sensing in Spatial Domain

2018-08-07
2018-01-1621
Millimeter wave automotive radar is one of the most important sensors in the Advanced Driver Assistance System (ADAS) and autonomous driving system, which detects the target vehicles around the ego vehicle via processing transmitted and echo signals. However, the sampling rate of classical radar signal processing methods based on Nyquist sampling theorem is too high and the resolution of range, velocity and azimuth can’t meet the requirement of highly autonomous driving, especially azimuth. In spatial domain, targets are sparse distribution in the detection range of automotive radar. To solve these problems, the algorithm for targets location based on compressed sensing for automotive radar is proposed in this paper. Besides, the feasibility of the algorithm is verified through the simulation experiments of traffic scene. The range-doppler-azimuth model can be used to estimate the distance, velocity and azimuth of the target accurately.
Technical Paper

A Real-Time Traffic Light Detection Algorithm Based on Adaptive Edge Information

2018-08-07
2018-01-1620
Traffic light detection has great significant for unmanned vehicle and driver assistance system. Meanwhile many detection algorithms have been proposed in recent years. However, traffic light detection still cannot achieve a desirable result under complicated illumination, bad weather condition and complex road environment. Besides, it is difficult to detect multi-scale traffic lights by embedded devices simultaneously, especially the tiny ones. To solve these problems, this paper presents a robust vision-based method to detect traffic light, the method contains main two stages: the region proposal stage and the traffic light recognition stage. On region proposal stage, we utilize lane detection to remove partial background from the original image. Then, we apply adaptive canny edge detection to highlight region proposal in Cr color channel, where red or green color proposals can be separated easily. Finally, extract the enlarged traffic light RoI (Region of Interest) to classify.
Technical Paper

Personalized Eco-Driving for Intelligent Electric Vehicles

2018-08-07
2018-01-1625
Minimum energy consumption with maximum comfort driving experience define the ideal human mobility. Recent technological advances in most Advanced Driver Assistance Systems (ADAS) on electric vehicles not only present a significant opportunity for automated eco-driving but also enhance the safety and comfort level. Understanding driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system comfort. This research focuses on the personalized and green adaptive cruise control for intelligent electric vehicle, which is also known to be MyEco-ACC. MyEco-ACC is based on the optimization of regenerative braking and typical driving styles. Firstly, a driving style model is abstracted as a Hammerstein model and its key parameters vary with different driving styles. Secondly, the regenerative braking system characteristics for the electric vehicle equipped with 4-wheel hub motors are analyzed and braking force distribution strategy is designed.
Technical Paper

Lane Detection System for Night Scenes

2018-08-07
2018-01-1617
Most of algorithms of lane detection mainly aim at the scenes of daytime. However, those algorithms are unstable for the lane detection at night because the camera is very sensitive to the light change. This paper proposed a lane detection algorithm that largely improves the detection system’s performance when it is used at night. The algorithm has two main stage: Image processing and Kalman filter (KF). The key process steps of Stage 1 are: extracting the Region of Interesting (ROI)→Edge Detection →Binarization→Hough→ Lane Selection→Lane fitting. First step, a ROI could be extracted according to the relatively fixed location of lanes. In step of edge detection, we use a creative filter named Correlation filter to remove image noise and remain the feature of lane. The filter matrix looks like “[0 1 1, −1 0 1; −1 −1 0]”. Next, the candidate lines are detected by the Hough transform, then, the equations of lane are acquired by fitting spots obtained from Hough.
Technical Paper

Research on Track Management of Multi-Target Tracking Based on Modified Fast Algorithm for Data Association

2018-08-07
2018-01-1619
With the development of autonomous vehicle technology, there is an increasing tendency toward the application of intelligent sensors in environment-perception system on autonomous vehicle to assist vehicle in intelligent decision making relevant to autonomous driving. As for environment-perception system, a good track management method serves as the foundation, while multi-target tracking and multi-sensor data fusion are recognized as the key. In this paper, a track management method is proposed to deal with multi-target tracking based on the target-level data of multisource environmental sensors for autonomous vehicle. The track management includes four procedures as following: track initiation; point-track association; track update; track deletion. A modified fast algorithm for data association is applied in the point-track association procedure. Afterwards Kalman filter is implemented to update the track information of target. The algorithm has got through a simulation test.
Technical Paper

System Design and Model of a 3D 79 GHz High Resolution Ultra-Wide Band Millimeter-Wave Imaging Automotive Radar

2018-08-07
2018-01-1615
Automotive radar is an important environment perception sensor for advance driving assistance system. It can detect objects around the vehicle with high accuracy and it works in all bad weathers. For traditional automotive radar, it cannot measure the objects’ height. Thus, a manhole cover on the road surface or a guideboard high above the road would be taken erroneously as a non-moving car. In such cases, the adaptive cruise system would decelerate or stop the vehicle erroneously and make the driver uncomfortable. A 3D automotive radar with two-dimensional electronic scanning can measure the targets’ height as well as the targets’ azimuth angle. This paper presents a 79 GHz ultra-wide band automotive 3D imaging radar. Due to the 4 GHz wide bandwidth, the range resolution of this radar can be as small as 3.75 cm.
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