Understanding the Lateral Dimension of Traffic: Measuring and Modeling Lane Discipline

2021 ◽  
pp. 036119812110318
Author(s):  
Rafael Delpiano
Keyword(s):  
New Technologies ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Lateral Position ◽  
Multiple Cameras ◽  
Lateral Velocity ◽  
Lane Changing ◽  
Lateral Dimension ◽  
Vehicle Position ◽  
Longitudinal Position

There is growing interest in understanding the lateral dimension of traffic. This trend has been motivated by the detection of phenomena unexplained by traditional models and the emergence of new technologies. Previous attempts to address this dimension have focused on lane-changing and non-lane-based traffic. The literature on vehicles keeping their lanes has generally been limited to simple statistics on vehicle position while models assume vehicles stay perfectly centered. Previously the author developed a two-dimensional traffic model aiming to capture such behavior qualitatively. Still pending is a deeper, more accurate comprehension and modeling of the relationships between variables in both axes. The present paper is based on the Next Generation SIMulation (NGSIM) datasets. It was found that lateral position is highly dependent on the longitudinal position, a phenomenon consistent with data capture from multiple cameras. A methodology is proposed to alleviate this problem. It was also discovered that the standard deviation of lateral velocity grows with longitudinal velocity and that the average lateral position varies with longitudinal velocity by up to 8 cm, possibly reflecting greater caution in overtaking. Random walk models were proposed and calibrated to reproduce some of the characteristics measured. It was determined that drivers’ response is much more sensitive to the lateral velocity than to position. These results provide a basis for further advances in understanding the lateral dimension. It is hoped that such comprehension will facilitate the design of autonomous vehicle algorithms that are friendlier to both passengers and the occupants of surrounding vehicles.

scholarly journals Integrated Avoid Collision Control of Autonomous Vehicle Based on Trajectory Re-Planning and V2V Information Interaction

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1079 ◽  
Author(s):  
Fen Lin ◽  
Kaizheng Wang ◽  
Youqun Zhao ◽  
Shaobo Wang
Keyword(s):  
Autonomous Vehicles ◽  
Control Method ◽  
Integrated Control ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Reference Trajectory ◽  
Threshold Method ◽  
Lane Changing ◽  
Information Interaction ◽  
Fitting In

An integrated longitudinal-lateral control method is proposed for autonomous vehicle trajectory tracking and dynamic collision avoidance. A method of obstacle trajectory prediction is proposed, in which the trajectory of the obstacle is predicted and the dynamic solution of the reference trajectory is realized. Aiming at the lane changing scene of autonomous vehicles driving in the same direction and adjacent lanes, a trajectory re-planning motion controller with the penalty function is designed. The reference trajectory parameterized output of local reprogramming is realized by using the method of curve fitting. In the framework of integrated control, Fuzzy adaptive (proportional-integral) PI controller is proposed for longitudinal velocity tracking. The selection and control of controller and velocity are realized by logical threshold method; A model predictive control (MPC) with vehicle-to-vehicle (V2V) information interaction modular and the driver characteristics is proposed for direction control. According to the control target, the objective function and constraints of the controller are designed. The proposed method’s performance in different scenarios is verified by simulation. The results show that the autonomous vehicles can avoid collision and have good stability.

scholarly journals Development and nonlinear mathematical modeling of a hybrid land autonomous vehicle that applies agrochemicals to ornamental plants

2020 ◽  
pp. 9-14
Author(s):  
Carlos HERNÁNDEZ ◽  
Nicandro FARÍAS ◽  
Noel GARCÍA ◽  
J. Reyes BENAVIDES
Keyword(s):  
Mathematical Modeling ◽  
Information And Communication Technologies ◽  
Precision Agriculture ◽  
Autonomous Vehicles ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Longitudinal Velocity ◽  
Ornamental Plants ◽  
Lateral Velocity ◽  
Agricultural Industry

The development of electronics, information and communication technologies have favored the dissemination of precision agriculture. While in other countries important scientific innovations are carried out and Hybrid Land Autonomous Vehicles (VATH) are used in various agricultural activities, in our country there is very little development in this regard and some of these production activities are still manual. This research presents the development and non-linear mathematical modeling of VATH for the automated application of agrochemicals in ornamental plants, for modeling the dynamics of longitudinal velocity, lateral velocity and angular velocity of turn or yaw that were simulated in SciLab are observed with the ISO 3888 standard. For the construction of this vehicle, we took an ATV and other low-cost electronic components that make it more affordable in the national agricultural industry will be considered as a motor base, compared to that proposed in other similar developments.

Lateral obstacle avoidance control based on driving behavior recognition of the preceding vehicles in adjacent lanes

2020 ◽  
Vol 68 (10) ◽  
pp. 880-892
Author(s):  
Youguo He ◽  
Xing Gong ◽  
Chaochun Yuan ◽  
Jie Shen ◽  
Yingkui Du
Keyword(s):  
Obstacle Avoidance ◽  
Lateral Displacement ◽  
Longitudinal Velocity ◽  
Driving Behavior ◽  
Lateral Acceleration ◽  
Lateral Motion ◽  
Behavior Recognition ◽  
Dynamic Surface ◽  
Lane Changing ◽  
The Impact

AbstractThis paper proposes a lateral lane change obstacle avoidance constraint control simulation algorithm based on the driving behavior recognition of the preceding vehicles in adjacent lanes. Firstly, the driving behavior of the preceding vehicles is recognized based on the Hidden Markov Model, this research uses longitudinal velocity, lateral displacement and lateral velocity as the optimal observation signals to recognize the driving behaviors including lane-keeping, left-lane-changing or right-lane-changing; Secondly, through the simulation of the dangerous cutting-in behavior of the preceding vehicles in adjacent lanes, this paper calculates the ideal front wheel steering angle according to the designed lateral acceleration in the process of obstacle avoidance, designs the vehicle lateral motion controller by combining the backstepping and Dynamic Surface Control, and the safety boundary of the lateral motion is constrained based on the Barrier Lyapunov Function; Finally, simulation model is built, and the simulation results show that the designed controller has good performance. This active safety technology effectively reduces the impact on the autonomous vehicle safety when the preceding vehicle suddenly cuts into the lane.

scholarly journals A Game Theory-Based Approach for Modeling Autonomous Vehicle Behavior in Congested, Urban Lane-Changing Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Traffic ◽  
Road User ◽  
Lane Change ◽  
Traffic Light ◽  
User Interactions ◽  
Lane Changing

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.

Drivers’ Gaze Behaviors are Influenced by Vehicle Position

2020 ◽  
Vol 64 (1) ◽  
pp. 1625-1629 ◽  
Author(s):  
Yuki Okafuji ◽  
Takahiro Wada ◽  
Toshihito Sugiura ◽  
Kazuomi Murakami ◽  
Hiroyuki Ishida
Keyword(s):  
Driving Simulator ◽  
Lateral Position ◽  
Gaze Behavior ◽  
Lateral Deviation ◽  
Simulated Driving ◽  
The Gaze ◽  
Fixation Distance ◽  
Long Time ◽  
Vehicle Position ◽  
Lane Keeping

Drivers’ gaze behaviors in naturalistic and simulated driving tasks have been investigated for decades. Many studies focus on driving environment to explain a driver’s gaze. However, if there is a great need to use compensatory steering for lane-keeping, drivers could preferentially acquire information directly required for the task. Therefore, we assumed that a driver’s gaze behavior was influenced not only by the environment but also the vehicle position, especially the lateral position. To verify our hypothesis, we carried out a long-time driving simulator experiment, and the gaze behaviors of two participating drivers were analyzed. Results showed that gaze behavior—the fixation distance and the lateral deviation of the fixation—was influenced by the lateral deviation of the vehicle. Consequently, we discussed processes that determined drivers’ gaze behaviors.

scholarly journals Assessment of Social Acceptance for Autonomous Vehicles in Southeastern Poland

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5778
Author(s):  
Agnieszka Dudziak ◽  
Monika Stoma ◽  
Andrzej Kuranc ◽  
Jacek Caban
Keyword(s):  
Autonomous Vehicles ◽  
Social Acceptance ◽  
New Technologies ◽  
Consumer Preferences ◽  
Autonomous Vehicle ◽  
Developed Countries ◽  
Automotive Market ◽  
Advantages And Disadvantages ◽  
Autonomous Cars ◽  
The Impact

New technologies reaching out for meeting the needs of an aging population in developed countries have given rise to the development and gradual implementation of the concept of an autonomous vehicle (AV) and have even made it a necessity and an important business paradigm. However, in parallel, there is a discussion about consumer preferences and the willingness to pay for new car technologies and intelligent vehicle options. The main aim of the study was to analyze the impact of selected factors on the perception of the future of autonomous cars by respondents from the area of Southeastern Poland in terms of a comparison with traditional cars, with particular emphasis on the advantages and disadvantages of this concept. The research presented in this study was conducted in 2019 among a group of 579 respondents. Data analysis made it possible to identify potential advantages and disadvantages of the concept of introducing autonomous cars. A positive result of the survey is that 68% of respondents stated that AV will be gradually introduced to our market, which confirms the high acceptance of this technology by Poles. The obtained research results may be valuable information for governmental and local authorities, but also for car manufacturers and their future users. It is an important issue in the area of shaping the strategy of actions concerning further directions of development on the automotive market.

Development of Operation Guidelines for Leader–Follower Autonomous Maintenance Vehicles at Work Zone Locations

2021 ◽  
pp. 036119812110566
Author(s):  
Qing Tang ◽  
Xianbiao Hu ◽  
Ruwen Qin
Keyword(s):  
Decision Making ◽  
Autonomous Vehicle ◽  
Field Testing ◽  
Work Zone ◽  
Lane Changing ◽  
The Public ◽  
Car Following ◽  
Technical Requirements ◽  
Car Following Model ◽  
Niche Area

The rapid advancement of connected and autonomous vehicle (CAV) technologies, although possibly years away from wide application to the general public travel, are receiving attention from many state Departments of Transportation (DOT) in the niche area of using autonomous maintenance technology (AMT) to reduce fatalities of DOT workers in work zone locations. Although promising results are shown in testing and deployments in several states, current autonomous truck mounted attenuator (ATMA) system operators are not provided with much practical driving guidance on how to drive these new vehicle systems in a way that is safe to both the public and themselves. To this end, this manuscript aims to model and develop a set of rules and instructions for ATMA system operators, particularly when it comes to critical locations where essential decision making is needed. Specifically, three technical requirements are investigated: car-following distance, critical lane-changing gap distance, and intersection clearance time. Newell’s simplified car-following model, and the classic lane-changing behavior model are modified, with roll-ahead distance taken into account, to model the driving behaviors of the ATMA vehicles at those critical decision-making locations. Data are collected from real-world field testing to calibrate and validate the developed models. The modeling outputs suggest important thresholds for ATMA system operators to follow. For example, on a freeway with a speed limit of 70 mph and ATMA operating speed of 10 mph, car-following distance should be no less than 75 ft for the lead truck and 100 ft for the follower truck, the critical lane-changing gap distance is 912 ft, and a minimum intersection clearance is 15 s, which are all much higher than the requirements for a general vehicle.

Effect of the Fish-Bone Dam Angle on the Flow Mechanisms of a Fish-Bone Type Dividing Dike

2020 ◽  
Vol 54 (3) ◽  
pp. 58-67
Author(s):  
Jia Ni ◽  
Linwei Wang ◽  
Xixian Chen ◽  
Luan Luan Xue ◽  
Isam Shahrour
Keyword(s):  
Water Level ◽  
Longitudinal Velocity ◽  
Flow Characteristics ◽  
Fish Bone ◽  
Flume Experiments ◽  
Lateral Velocity ◽  
Engineering Structures ◽  
Flow Mechanisms ◽  
River Training ◽  
Large Velocity Gradient

AbstractFish-bone type dividing dikes are river engineering structures used for river training and to protect a mid-channel bar from scour. The flow characteristics around fish-bone type dividing dikes are very complicated, especially near its fish-bone dam. To understand the flow and scour processes associated with fish-bone dams, this paper conducts a numerical simulation of flow characteristics for different fish-bone dam angles. Based on the Yudaizhou fish-bone type dividing dike of the Dongliu Waterway, a 3-D numerical model is established via Flow-3D to simulate the flow characteristics around a fish-bone type dividing dike, which is verified by flume experiments. Based on the results, the effects of different fish-bone dam angles on water level and velocity distribution are investigated. With increasing fish-bone dam angle, the longitudinal and lateral gradients of the water level gradually decreased, and the variation degree of the longitudinal velocity also decreased; however, the variation degree of the lateral velocity increased. Vortex areas formed around the fish-bone dam and the downstream zone of the dike. A large velocity gradient was found around the dike, and the downstream vortex area decreased with increasing fish-bone dam angle.

scholarly journals Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1242
Author(s):  
Jiangyi Lv ◽  
Hongwen He ◽  
Wei Liu ◽  
Yong Chen ◽  
Fengchun Sun
Keyword(s):  
Autonomous Vehicles ◽  
Estimation Error ◽  
Longitudinal Velocity ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Lateral Velocity ◽  
Empirical Correction ◽  
Vehicle Velocity ◽  
Wide Range

Accurate and reliable vehicle velocity estimation is greatly motivated by the increasing demands of high-precision motion control for autonomous vehicles and the decreasing cost of the required multi-axis IMU sensors. A practical estimation method for the longitudinal and lateral velocities of electric vehicles is proposed. Two reliable driving empirical judgements about the velocities are extracted from the signals of the ordinary onboard vehicle sensors, which correct the integral errors of the corresponding kinematic equations on a long timescale. Meanwhile, the additive biases of the measured accelerations are estimated recursively by comparing the integral of the measured accelerations with the difference of the estimated velocities between the adjacent strong empirical correction instants, which further compensates the kinematic integral error on short timescale. The algorithm is verified by both the CarSim-Simulink co-simulation and the controller-in-the-loop test under the CarMaker-RoadBox environment. The results show that the velocities can be accurately and reliably estimated under a wide range of driving conditions without prior knowledge of the tire-model and other unavailable signals or frequently changeable model parameters. The relative estimation error of the longitudinal velocity and the absolute estimation error of the lateral velocity are kept within 2% and 0.5 km/h, respectively.

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