Relative Position Of Vehicle Research Articles

Modeling of Lane Changing Behavior of Connected Driving Based on Vehicle Interaction Potential

Aiming at the interactive behavior of vehicles changing lanes in the intelligent network traffic environment, the relative position of vehicle, speed, acceleration, and steering angle are introduced to correct the molecular interaction potential, and the vehicle interaction potential model is established. The spatial distribution map of the vehicle interaction potential field under different motion states was drawn, and the changing law of the vehicle interaction potential field was described. By analyzing the longitudinal critical distance of the lane changing safe critical time, the expression of acceptable clearance for lane changing is defined, and the relationship between acceptable clearance and the speed and acceleration of the interactive vehicle is verified by simulation. Combined with the acceptable clearance of lane changing, a lane changing behavior model based on the vehicle interaction potential is established, and the situation of lane changing vehicles subjected to the interaction potential and potential field forces generated by the surrounding vehicles is analyzed, and the driving decision of lane changing vehicles under the action of different potential field forces is given. Compared with the molecular dynamics lane changing model and LS2015 lane changing model, the results show that the vehicle action potential lane changing model can effectively improve the running speed and stability of traffic flow. The research has theoretical significance for the lane changing behavior decisions of networked autonomous vehicles in the future.

Design and Experiments of Autonomous Path Tracking Based on Dead Reckoning

Path tracking is an important component of autonomous driving and most current path tracking research is based on different positioning sensors, such as GPS, cameras, and LIDAR. However, in certain extreme cases (e.g., in tunnels or indoor parking lots), if these sensors are unavailable, achieving accurate path tracking remains a problem that is worthy of study. This paper addresses this problem by designing a dead reckoning method that is solely reliant on wheel speed for localization. Specifically, a differential drive model is first used for estimating the current relative vehicle position in real time by rear wheel speed, and the deviation between the current path and the reference path is then calculated using the pure pursuit algorithm as a means of obtaining the target steering wheel angle and vehicle speed. The steering wheel and vehicle speed signals are then output by two PID controllers in order to control the vehicle, and the automatic driving path tracking is ultimately realized. Through exhaustive tests and experiments, the stop position error and tracking process error are compared under different conditions, and the effects of vehicle speed, look-ahead distance, starting position angle, and driving mode on tracking accuracy are analyzed. The experimental results show the average error of the end position to be 0.26 m, 0.383 m, and 0.505 m when using BMW-i3 to drive one lap automatically at speeds of 5 km/h, 10 km/h, and 15 km/h in a test area with a perimeter of approximately 200 m.

Development and experimental validation of a system for agricultural grain unloading-on-the-go

This paper describes the development, simulation, and experimental validation of a novel grain unloading-on-the-go automation system (automatic offloading) for agricultural combine harvesters. Unloading-on-the-go is desirable during harvest, but it requires highly-skilled and exhausting labor because the combine operator must fulfill multiple tasks simultaneously. The automatic offloading system can unburden the combine operator by automatically monitoring the grain cart fill status, determining the appropriate auger location, and controlling the relative vehicle position and auger on/off. An automation architecture is proposed and experimentally demonstrated to automate the unloading-on-the-go process. To simulate the automatic offloading operation, a grain fill model and vehicle dynamics models were developed and validated with in-field testing. To allow for different operator-selected unloading scenarios, the automatic offloading controller has three fill strategies and two movement control options, “open-loop” and “closed-loop”. Simulation results demonstrated that both movement control options can achieve the fill target. The automatic offloading controller was implemented on a dSPACE MicroAutoBox II and integrated into a combine harvester. A PC-based user interface was developed for the combine operator to monitor unloading status and provide commands during the test. In addition, a stereo-camera-based perception system was connected to the automatic offloading controller via an Ethernet cable for grain fill profile measurement during unloading. In-field testing demonstrated that the automatic offloading system can effectively automate the unloading-on-the-go of a combine harvester to fill a grain cart to the desired level under nominal harvesting conditions. The achievable fill level for a 1000-bushel grain cart without spillage ranges from −0.7 m to −0.2 m for the near-edge grain height relative to the cart edge.

Automation of Agricultural Grain Unloading-on-the-go

This paper describes the development and experimental validation of a novel grain unloading-on-the-go automation system (automatic offloading) for agricultural combine harvesters. Unloading-on-the-go is desirable during harvest, but it requires highly-skilled and exhausting labor because the combine operator must fulfill multiple tasks simultaneously. The automatic offloading system can unburden the combine operator by automatically monitoring the grain cart fill status, determining the appropriate auger location, and controlling the relative vehicle position and auger on/of. An automation architecture is proposed and experimentally demonstrated to automate the unloading-on-the-go process. To allow for diferent operator-selected unloading scenarios, the automatic offloading controller has three fill strategies and two movement control options, “open-loop” and “closed-loop”. The automatic offloading controller was implemented on a dSPACE MicroAutoBox II and integrated into a combine harvester. In addition, a stereo-camera-based perception system was connected to the automatic offloading controller via an Ethernet cable for grain fill profile measurement during unloading. In-feld testing demonstrated that the automatic offloading system can effectively automate the unloading-on-the-go of a combine harvester to fill a grain cart to the desired level under nominal harvesting conditions.

FST-Convoy: A Leader Tracking Control of Vehicles Connected by Shape Sensor FST

This paper describes FST-Convoy, a leader tracking control system for vehicles using the shape sensor flexible sensor tube (FST). Among many methods of autonomous driving, follow-driving is one of them. Some of these have been put into practical use in a limited environment. Unfortunately, there are situations in which such sensors do not work well. One of these is underground. In the underground, GNSS signals do not reach vehicles, so they cannot obtain their positions. Therefore, we propose a new way to achieve follow-driving in such environments. We used the shape sensor, FST. The FST is a shape sensor with a serial link structure and many joints. It can measure its shape by solving its kinematics and determine the relative position of the start link to the end link. Therefore, we can measure the relative positions of vehicles that connected a leader and a follower using FST. We call this system FST-Convoy. We developed and verified the system using a platooning-driving experiment.

Dynamic Stabilization of Unmanned Vehicle Convoy in Road Climatic Environment of the Russian Federation

This work analyzes experimental results of traffic control of unmanned vehicle convoy (UMV) with manned master vehicle in Russian road climatic environment. The problem of obstacle avoidance in driving lanes and position stabilization on preset motion path is reduced to the problem of dynamic stabilization of state variables. Its solution is aided by virtual data sensors requiring for minimum configuration of engineering tools. Relative positions of vehicles are determined by algorithms of combined data processing of navigation systems and machine vision which make it possible to solve this problem without visible road markings and radio vision for satellite navigation. Experimental results show that the developed control algorithms of UMV convoy are capable to solve the problem of its dynamic stabilization in actual traffic environment. The developed control algorithms of traction, braking, and path provide efficient operation on all types of surfaces including slippery roads. Scientific novelty of this work is comprised of experimental verification of efficiency of the developed solutions for advanced unmanned vehicles in Russia.

Shadowing Characterization for 5-GHz Vehicle-to-Vehicle Channels

As one of the most important parts of intelligent transportation systems, vehicle-to-vehicle (V2V) communications have been widely studied because of the potential improvements it can provide in terms of traffic efficiency and traffic safety through various applications. The research on propagation characteristics for V2V channels is of primary importance, and one particular significant topic is shadowing effects induced by obstructing vehicles between transmitter (Tx) and receiver (Rx). In this paper, we present shadowing measurement results for V2V channels in both urban and highway scenarios, in which a truck and a van were used as the obstacles. Channel measurements in the 5-GHz band were performed in both line-of-sight (LOS) and non-LOS (NLOS) conditions, and different relative positions of vehicles on the road were considered. Based on the measured results, statistics for the shadowing loss and the root mean square delay spread (RMS-DS) are provided, and shadowing effects in each case are compared. By utilizing the temporal power delay profile correlation coefficient, the stationarity distance for each case is estimated, and the nonstationarity phenomenon and its relation to the shadowing effect are investigated. The mean value of shadowing loss was found to range from 3.38 to 9.33 dB with standard deviation ranging from 3.20 to 6.98 dB, and a normal distribution can well describe the statistics of the shadowing loss. With smaller RMS-DS values, the highway shows larger shadowing losses than the urban street. Moreover, in any specific scenario (e.g., highway or urban), the shadowing effect is generally closely related to the RMS-DS and stationarity distance: Larger shadowing loss always occurs when RMS-DS is large and average stationarity distance is small.

Optical illusions and life-threatening traffic crashes: A perspective on aerial perspective

Aerial perspective illusion is a feature of visual perception where landscapes appear relatively close in clear light and distant in dim light. We hypothesized that bright sunlight might cause drivers to perceive distant terrain as relatively close and misinterpret the approach speed of surrounding landscape as unduly slow. This hypothesis would mean, in turn, that drivers in bright sunlight may underestimate their progress on the road, compensate by traveling at a faster baseline speed, and ultimately increase the prevailing risk of a life-threatening traffic crash.We conducted three pilot studies to illustrate how the illusion might contribute to a life- threatening traffic crash. The first illustration used a questionnaire to demonstrate that most respondents were mistaken when judging the distance between simple balls in different positions. The second illustration involved an experimental manipulation to assess whether aerial perspective influenced judgments about the relative positions of vehicles in traffic. The third illustration analyzed a segment of high-volume fast-speed traffic and found an increased frequency of speeding under bright sunlight.Together with past work based on the visual arts, these examples illustrate how an aerial perspective illusion can affect distance perception, may appear in realistic traffic situations, and could potentially contribute to the risk of a life-threatening traffic crash. An awareness of this hypothesis might lead to applications on how optical illusions could extend to everyday traffic and might potentially inform safety warnings to prevent life- threatening crashes.

A Unified Framework of Clustering Approach in Vehicular Ad Hoc Networks

Effective clustering algorithms are indispensable in order to solve the scalability problem in vehicular ad hoc networks. Although current existing clustering algorithms show increased cluster stability under some certain traffic scenarios, it is still hard to address which clustering metric performs the best. In this paper, we propose a unified framework of clustering approach (UFC), composed of three important parts: 1) neighbor sampling; 2) backoff-based cluster head selection; and 3) backup cluster head based cluster maintenance. Three mobility-based clustering metrics, including vehicle relative position, relative velocity, and link lifetime, are considered in our approach under different traffic scenarios. Furthermore, a detailed analysis of UFC with parameters optimization is presented. Extensive comparison results among UFC, lowest-ID, and VMaSC algorithms demonstrate that our clustering approach performs high cluster stability, especially under high dynamic traffic scenarios.

1401 悪天候時レーンキーピングシステムのロジック検証とHMIの検討

The authors have proposed a kind of lane keeping system using roadside markers and onboard sensors to achieve safer and smoother road traffic in adverse weather conditions. The system acquires the relative positions of roadside passive markers by laser sensor, and their absolute positions by communication with roadside active markers. Using these data, the system estimates the vehicle's relative position in the lane, and assists the driver to keep the lane. In this paper, the developed system and the implemented logics are verified. Moreover, various kinds of Human Machine Interfaces are listed and a Head-Up Display projected to windshield with Augmented Reality is introduced.

Cooperative Relative Positioning for Intelligent Transportation System

Global navigation satellite system-based positioning plays an important role in support system for safe driving, where relative positions of vehicles are used to prevent collision accidents from happening. In urban areas, however, multipath errors (MPEs) in pseudo-ranges, caused by obstruction and reflection of roadside buildings, greatly degrade the precision of relative positions. On the other hand, simply removing all reflected signals might lead to a shortage of satellites in fixing positions. This dilemma is solved in this paper by exploiting spatial correlation of MPEs. First, by analysis, ray-tracing simulation and testbed experiments, we show that MPEs in pseudo-ranges are spatially correlated in a small area. Then, we suggest a cooperative relative positioning scheme to exploit correlated signals, including reflected ones, in computing relative positions of nearby vehicles. Efficient transmission of pseudo-ranges is also discussed. The proposed scheme, which can be implemented either in a distributed way or via a cloud of intelligent transportation system, helps to improve the precision of relative positions in urban canyons.

A Method to Determine Relative Vehicle Positioning for Safety Warning

Determining relative vehicle positioning for vehicle safety warning services requires high level of accuracy. Positioning based on general satellite information has a large margin of error due to cost constraints. This paper proposes a method to determine relative vehicle position for vehicle safety warning, based on conditional extremum and relative vehicle history positioning. Special attention is paid to improve not only the computational efficiency but also the accuracy of determining the relative position of two vehicles or a vehicle and reference frame. Field test results demonstrate the significance of improved accuracy in determining relative vehicle position. Theoretical analysis and realistic systematic tests provide useful insights into potential applications in safety warning.

Benefit Estimation of Automatic Braking System Based on Real-World Pedestrian Accidents

The aim of the current study was to assess effectiveness of automatic braking system quantitatively using real pedestrian accident data selected from IVAC database. Based on the IVAC pedestrian accident scenarios, vehicle and pedestrian trajectories, and other information, the relative position of vehicles and pedestrians were estimated one second (0.5 second) prior to the actual crash. According to the pedestrian fatal (AIS3+) risk and compared with the real pedestrian casualty risk, the benefit of the automatic braking system was calculated. About 86.8% (82.3%) reduction in pedestrian fatal (AIS3+) injury at a field of view of 60°.

Intelligent vehicle. Adaptation of subsystem for determination the relative position of moving vehicles

In this article there are considered the history of unmanned vehicles, showed the status of developments in Russia and the world, considered the issues of determining the relative position of vehicles based on optical tracking technology.

Limitations of employing undirected information flow graphs for the maintenance of rigid formations for heterogeneous vehicles

In this paper, we consider the problem of decentralized control of a collection of heterogeneous vehicles trying to maintain a rigid formation. In a rigid formation of vehicles, the separation distance between any pair of vehicles does not change throughout their motion and equals a pre-specified value that defines the formation. In each formation, there is a set of reference vehicles and a set of following vehicles. A reference vehicle may not be influenced by the motion of the following vehicle, but the motion of the following vehicle is influenced by the motion of the reference vehicle. Since we will be primarily dealing with translational maneuvers of the formation, we will consider formations where there is only one reference vehicle whose motion specifies the desired motion for all the vehicles in the formation. Each following vehicle attempts to maintain a specified constant safe distance from its adjacent vehicles in the collection. We call a vehicle B adjacent to a vehicle A if the relative position of vehicle B is known to vehicle A either by communication or by sensing. We only consider information flow graphs that are undirected when restricted to the set of following vehicles, i.e., graphs where a following vehicle A is adjacent to a following vehicle B if and only if the following vehicle B is adjacent to the following vehicle A. We model each vehicle as a point mass of one unit with two types of forces act on each vehicle – a controlled force, which is the output of an actuation system and a disturbing force over which there is no control. The actuation system is assumed to be linear and time invariant, and may be representable by a rational and strictly proper transfer function. The input to the control system of a vehicle in the formation is based on the error in maintaining the desired separation from its adjacent vehicles and the output of the control system is a command to the actuator. An earlier result showed that spacing errors due to disturbances amplify in a collection of identical vehicles with identically structured linear controllers if the reference vehicle information is not available to Ω( n) (A function f( n) is Ω( g( n)) if there is a constant c > 0 and a N > 0 such that ∣ f( n)∣ > c∣ g( n)∣ for all n > N.) vehicles, n being the size of the collection [1]. From the viewpoint of tolerance to communication failures, it is therefore necessary that there be at least two vehicles in the formation that are adjacent to Ω( n) vehicles in the formation. In this paper, we consider a broad class of heterogeneously structured controllers defined by a pre-specified bound, say B c > 0 as follows: the allowable controller in conjunction with the actuation systems on-board any vehicle will produce a force no greater than B c in response to a constant input to the control system. If this class of controllers were to be employed with the aforesaid undirected information flow graphs, we show that there is a critical size of the formation beyond which the motion of the vehicles in the formation will be unstable. This result shows the inability to scale such controllers for maintenance of rigid formations in conjunction with undirected information flow graphs.

Real-time image processing for the guidance of a small agricultural field inspection vehicle

This paper describes the image processing for an autonomous field inspection vehicle that uses a webcam for the navigation between two rows of agricultural crop. The relative vehicle position is calculated by segmentation and classification of the images and by then extracting geometrical lines corresponding to the crop rows. An autonomous vehicle was built and tested successfully in an agricultural environment.

Solution of Mixed Integer Linear Programming for Multi-target Pursuit Problem

The path planning for multi-target pursuit(MTP)is studied.Two MTP models,the nearest target pursuit and one-vehicle-one-target enable pursuit,based on the mixed integer linear programming(MILP)are presented.In the two MTP models, the dynamic equation of mass point with linear damping is taken as the state equation of vehicle motion.Integer variables are used to describe the relative position of vehicle and obstacle.Target expansion size is proposed to describe the pursuit process for target. Pursuit direction of vehicle is defined.The isometric plane method selecting integer variables is used to solve MILP pursuit problem. How to select the integer variables in initial inner point is also given.Finally,simulation experiment 1 is given to make comparisons between two MTP models and simulation experiment 2 to show the efficiency of the method.

Vehicular Node Localization Using Received-Signal-Strength Indicator

Vehicle-to-vehicle communications via dedicated-short-range-communication (DSRC) devices will enable safety applications such as cooperative collision warning. These devices use the IEEE 802.11p standard to support low-latency vehicle-to-vehicle and vehicle-to-infrastructure communications. However, a major challenge for the cooperative collision warning is to accurately determine the location of vehicles. In this paper, we present a novel cooperative-vehicle-position-estimation algorithm which can achieve a higher accuracy and more reliability than the existing global-positioning-system-based positioning solutions by making use of intervehicle-distance measurements taken by a radio-ranging technique. Our algorithm uses signal-strength-based intervehicle-distance measurements, vehicle kinematics, and road maps to estimate the relative positions of vehicles in a cluster. We have analyzed our algorithm by examining its performance-bound, computational-complexity, and communication-overhead requirements. In addition, we have shown that the accuracy of our algorithm is superior to previously proposed localization algorithms.

Design of a robust high-performance fuzzy path tracker for autonomous vehicles

This paper deals with automatic steering of autonomous wheeled mobile robots by using fuzzy logic. The fuzzy controller has as inputs the vehicle's relative position and orientation with respect to the path to follow, and the controller's output is the steering angle. The dynamic behaviour of path tracking with fuzzy controllers is investigated. The problem is not easy, owing to the nonlinear nature of the feedback tracking system. A new method for designing and tuning fuzzy path trackers for autonomous vehicles is proposed. The results of the application of the designed fuzzy path tracking controllers to RAMA, a mobile robot designed and built for navigation in indoor and outdoor industrial environments, are shown. The experiments demonstrate a very stable and precise path tracking.