Mission Mobility Reliability Analysis of Off-Road Ground Vehicles

2020 ◽  
Author(s):  
Yixuan Liu ◽  
Chen Jiang ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
Yan Fu ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Mobility Model ◽  
Dynamic Decision Making ◽  
Ground Vehicles ◽  
Mobility Data ◽  
Uncertainty Sources ◽  
Vehicle Mobility ◽  
On Line ◽  
Dynamic Updating ◽  
Kriging Surrogate Modeling

Abstract The NATO Reference Mobility Model (NRMM) has been developed to predict the mobility of off-road ground vehicles based on modeling and simulation (M&S). Due to various uncertainty sources in the M&S, uncertainty is inherent in the vehicle mobility. Aims to account for the uncertainty in the mobility prediction in mission planning, this paper develops a simulation-based mission mobility reliability analysis framework for off-road ground vehicles. A concept of mission mobility reliability (MMR) is first proposed to quantify the reliability of a mission path which passes through different types of soils. A single-loop Kriging surrogate modeling method is then employed to overcome the challenge in the mission mobility reliability assessment caused by the computationally expensive mobility simulation. Built upon the surrogate model-based mission mobility reliability analysis, a dynamic updating scheme is proposed to update the MMR estimation based on the on-line mobility data, during the course of a specific mission and for a particular vehicle. The online dynamic updating of MMR allows for effective and dynamic decision making during the mission phase. A case study is used to demonstrate the effectiveness of the proposed MMR analysis and updating framework.

Simulation-Based Mission Mobility Reliability Analysis of Off-Road Ground Vehicles

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Yixuan Liu ◽  
Chen Jiang ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
Paramsothy Jayakumar ◽  
...  
Keyword(s):  
Mission Planning ◽  
Dynamic Decision Making ◽  
Analysis Framework ◽  
Ground Vehicles ◽  
Mobility Data ◽  
Simulation Based ◽  
Different Types ◽  
Dynamic Updating ◽  
Kriging Surrogate Modeling

Abstract This paper develops a simulation-based mission mobility reliability (MMR) analysis framework to account for uncertainty in mobility prediction of off-road ground vehicles in mission planning. A concept of MMR is first proposed to quantify reliability of a mission path which passes through different types of soils. A single-loop Kriging surrogate modeling method is then employed to overcome the computational challenge in MMR assessment caused by expensive mobility simulations. Built upon the surrogate model-based MMR analysis, a dynamic updating scheme is proposed to update the MMR estimation using online mobility data, during the course of a specific mission and for a particular vehicle. The online dynamic updating of MMR allows us for effective and dynamic decision-making during the mission phase, thus proactively avoid rare events of immobility during the mission. A case study demonstrates the efficacy of the proposed MMR analysis and updating framework.

Reliability-Based Mission Planning of Off-Road Autonomous Ground Vehicles Using an Outcrossing Approach

2021 ◽  
Author(s):  
Chen Jiang ◽  
Yixuan Liu ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
...  
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Gaussian Random Field ◽  
Mobility Model ◽  
Outcrossing Rate ◽  
Mission Planning ◽  
Ground Vehicles ◽  
Practical Applications ◽  
Autonomous Ground Vehicles ◽  
Uncertainty Sources

Abstract Reliability-based mission planning aims to identify an optimal path for off-road autonomous ground vehicles (AGVs) under uncertain terrain environment, while satisfying specific mission mobility reliability (MMR) constraints. The evaluation of MMR during path planning poses computational challenges for practical applications. This paper presents an efficient reliability-based mission planning using an outcrossing approach that has the same computational complexity as deterministic mission planning. A Gaussian random field is employed to represent the spatially dependent uncertainty sources in the terrain environment. The latter are then used in conjunction with a vehicle mobility model to generate a stochastic mobility map. Based on the stochastic mobility map, outcrossing rate maps are generated using the outcrossing concept which is widely used in time-dependent reliability. Integration of the outcrossing rate map with a rapidly-exploring random tree (RRT*) algorithm, allows for efficient path planning of AGVs subject to MMR constraints. A reliable RRT* algorithm using the outcrossing approach (RRT*-OC) is developed to implement the proposed efficient reliability-based mission planning. Results of a case study verify the accuracy and efficiency of the proposed algorithm.

Indices and Computational Strategy for Unmanned Ground Wheeled Vehicle Mobility Estimation and Enhancement

2013 ◽  
Author(s):  
Jeremy P. Gray ◽  
Vladimir V. Vantsevich ◽  
Jim L. Overholt
Keyword(s):  
United States Army ◽  
The United States ◽  
Stability Control ◽  
Past Century ◽  
Ground Vehicles ◽  
Analytical Criterion ◽  
Vehicle Mobility ◽  
On Line ◽  
Control Stability ◽  
Wheeled Vehicles

The United States Army began developing Unmanned Ground Vehicles (UGV) in the early 1900’s. Concurrently, researchers developed and enhanced passenger and commercial ground vehicles. Although significant progress has been made for improving vehicle mobility for all ground vehicles throughout the past century, mobility has lacked a concise mutually agreed definition and analytical standardized criteria. The implementations of improved technologies, such as vehicle traction control, stability control, and torque vectoring systems require researchers to take a step back and reevaluate mobility criteria. UGVs require additional enhancement to include on-line mobility estimation since the vehicle cannot predict nor anticipate terrain conditions on their own prior to the vehicle traversing those conditions. This paper analyzes methodologies researchers have employed for defining and improving vehicle mobility of wheeled vehicles. The analysis is done from a view point of concurrent mobility methodologies’ enhancement and applicability to wheeled UGVs. This analysis is then used to develop off-line and on-line analytical criterion for mobility estimation, and to derive a strategy which can be applied to wheeled vehicles, both manned and unmanned. The on-line mobility estimation enables the UGV to make control changes as the events occur rather than after the event, causing the vehicle to then optimize its reaction to regain control.

Efficient Reliability-Based Mission Planning of Off-Road Autonomous Ground Vehicles Using an Outcrossing Approach

2021 ◽  
pp. 1-45
Author(s):  
Chen Jiang ◽  
Yixuan Liu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
Yan Fu ◽  
...  
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Gaussian Random Field ◽  
Mobility Model ◽  
Outcrossing Rate ◽  
Mission Planning ◽  
Ground Vehicles ◽  
Practical Applications ◽  
Autonomous Ground Vehicles ◽  
Uncertainty Sources

Abstract Reliability-based mission planning aims to identify an optimal path for off-road autonomous ground vehicles (AGVs) under uncertain terrain environment, while satisfying specific mission mobility reliability (MMR) constraints. The evaluation of MMR during path planning poses computational challenges for practical applications. This paper presents an efficient reliability-based mission planning using an outcrossing approach that has the same computational complexity as deterministic mission planning. A Gaussian random field is employed to represent the spatially dependent uncertainty sources in the terrain environment. The latter are then used in conjunction with a vehicle mobility model to generate a stochastic mobility map. Based on the stochastic mobility map, outcrossing rate maps are generated using the outcrossing concept which is widely used in time-dependent reliability. Integration of the outcrossing rate map with a rapidly-exploring random tree (RRT*) algorithm, allows for efficient path planning of AGVs subject to MMR constraints. A reliable RRT* algorithm using the outcrossing approach (RRT*-OC) is developed to implement the proposed efficient reliability-based mission planning. Results of a case study with two scenarios verify the accuracy and efficiency of the proposed algorithm.

scholarly journals Mobility patterns are associated with experienced income segregation in large US cities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Esteban Moro ◽  
Dan Calacci ◽  
Xiaowen Dong ◽  
Alex Pentland
Keyword(s):  
Large Scale ◽  
Mobility Model ◽  
Coarse Grained ◽  
Spatial Proximity ◽  
Mobility Patterns ◽  
Data Set ◽  
Residential Patterns ◽  
Income Segregation ◽  
Mobility Data ◽  
Mobility Behavior

AbstractTraditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns.

Mining urban recurrent congestion evolution patterns from GPS-equipped vehicle mobility data

2016 ◽  
Vol 373 ◽  
pp. 515-526 ◽  
Author(s):  
Shi An ◽  
Haiqiang Yang ◽  
Jian Wang ◽  
Na Cui ◽  
Jianxun Cui
Keyword(s):  
Mobility Data ◽  
Vehicle Mobility

Mission Mobility Reliability Analysis of Off-Road Ground Vehicles

2021 ◽  
Author(s):  
Yixuan Liu ◽  
Chen Jiang ◽  
Zissimos Mourelatos ◽  
David Gorsich ◽  
Yan Fu ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Ground Vehicles

Tire-Terrain Normal and Longitudinal Dynamics and Slip Power Losses of an Unmanned Ground Vehicle

2013 ◽  
Author(s):  
Mostafa Salama ◽  
Vladimir V. Vantsevich
Keyword(s):  
Rolling Resistance ◽  
Computational Time ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicles ◽  
Power Losses ◽  
Ground Vehicle ◽  
Longitudinal Dynamics ◽  
Straight Line ◽  
On Line ◽  
Terrain Characteristics

Studies of the tire-terrain interaction have mostly been completed on vehicles with steered wheels, but not much work has been done regarding skid-steered Unmanned Ground Vehicles (UGV). This paper introduces a mathematical model of normal and longitudinal dynamics of a UGV with four skid-steered pneumatic tire wheels. Unlike the common approach, in which two wheels at each side are treated as one wheel (i.e., having the same rotational speeds), all four wheels in this study are independently driven. Thus the interaction of each tire with deformable terrain is introduced as holonomic constraints. The stress-strain characteristics for tire-soil interaction are analyzed based on modern Terramechanics methods and then further used to determine the circumferential wheel forces of the four tires. Contributions of three components of each tire circumferential force to tire slippages are modeled and analyzed when the tire normal loads vary during vehicle straight-line motion. The considered tire-soil characteristics are mathematically reduced to a form that allows condensing the computational time for on-line computing tire-terrain characteristics. Additionally, rolling resistance of the tires is analyzed and incorporated in the UGV dynamic equations. Moreover, the paper describes the physics of slip power losses in the tire-soil interaction of the four tires and applies it to small skid-steered UGV. This study also formulates an optimization problem of the minimization of the power losses in the tire-soil interactions due to the tire slippage.

Efficiency prediction of control room operators based on human reliability analysis and dynamic decision-making style in the process industry

2015 ◽  
Vol 35 (2) ◽  
pp. 192-199 ◽  
Author(s):  
Esmaeil Zarei ◽  
Iraj Mohammadfam ◽  
Mostafa Mirzaei Aliabadi ◽  
Ali Jamshidi ◽  
Fakhradin Ghasemi
Keyword(s):  
Decision Making ◽  
Reliability Analysis ◽  
Process Industry ◽  
Dynamic Decision Making ◽  
Control Room ◽  
Human Reliability ◽  
Human Reliability Analysis

Testing Design Optimization for Uncertainty Reduction in Generating Off-Road Mobility Map Using a Bayesian Approach

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
Paramsothy Jayakumar ◽  
Monica Majcher
Keyword(s):  
Design Optimization ◽  
Epistemic Uncertainty ◽  
Uncertainty Reduction ◽  
Soil Conditions ◽  
Mobility Prediction ◽  
Soil Maps ◽  
Optimization Framework ◽  
Uncertainty Sources ◽  
Vehicle Mobility ◽  
Testing Design

Abstract The Next Generation NATO Reference Mobility Model (NG-NRMM) plays a vital role in vehicle mobility prediction and mission planning. The complicated vehicle–terrain interactions and the presence of heterogeneous uncertainty sources in the modeling and simulation (M&S) result in epistemic uncertainty/errors in the vehicle mobility prediction for given terrain and soil conditions. In this paper, the uncertainty sources that cause the uncertainty in mobility prediction are first partitioned into two levels, namely uncertainty in the M&S and uncertainty in terrain and soil maps. With a focus on the epistemic uncertainty in the M&S, this paper presents a testing design optimization framework to effectively reduce the uncertainty in the M&S and thus increase the confidence in generating off-road mobility maps. A Bayesian updating approach is developed to reduce the epistemic uncertainty/errors in the M&S using mobility testing data collected under controllable terrain and soil conditions. The updated models are then employed to generate the off-road mobility maps for any given terrain and soil maps. Two types of design strategies, namely testing design for model selection and testing design for uncertainty reduction, are investigated in the testing design framework to maximize the information gain subject to limited resources. Results of a numerical example demonstrate the effectiveness of the proposed mobility testing design optimization framework.

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