Browse Topic: Traffic management

Items (130)
Find
test software title CURATDEV-46712345-software3/25/2026
467
TEST TESTSAE-SUP-TEST103/24/2026
TEST https://wcm14-tst.cld.sae.org/site/binaries/content/gallery/mobilus-brx/digital-supplements/software-diagram.png/software-diagram.png/sae%3Amedium
3526 information report arinc standard3526_informationarincstandard (Current)3/5/2026
3526 information report arinc standard
Aviation Maintenance Committee
3526 characteristic3526_characteristicstandard (Historical)3/5/2026
3526 characteristic standard
Aviation Maintenance Committee
3526 specification arinc standard3526_specification (Current)3/5/2026
3526 specification arinc standard
Airlines Electronic Engineering Committee
3526 aerospace information report standard3526_aerospacestandardinfo (Current)3/5/2026
3526 aerospace information report standard
Aviation Maintenance Committee
3526 aerospace standard3526-aerospacestandard (Current)3/5/2026
3526 aerospace standard
Aviation Maintenance Committee
jms test ingjmsIngestionTest (Historical)5/19/2025
jms test ing
Airlines Electronic Engineering Committee, Aviation Maintenance Committee
Arrangement and Control Method of Cooperative Vehicle Platoon2021-01-01134/6/2021
With the development of cellular communication technology and for the sake of reducing drag resistance, the multi-lane platoon technology will be more prosperous in the future. In this article, the cooperative vehicle platoon method on the public road is represented. The method’s architecture is mainly composed of the following parts: decision-making, path planning and control command generation. The decision-making uses the finite state machine to make decision and judgment on the cooperative lane change of vehicles, and starts to execute the lane change step when the lane change requirements are met. In terms of path planning, with the goal of ensuring comfort, the continuity of the vehicle state and no collision between vehicles, a fifth-order polynomial is used to fit every vehicle trajectory. In terms of control command generation module, a model predictive control algorithm is used to solve the multi-vehicle centralized optimization control problem. We use the two DOF vehicle model to simulate vehicle dynamics. The front wheel angle and acceleration or braking commands of multiple vehicles are optimized to ensure that the vehicle can well follow the trajectory of the vehicle which is calculated by the control command generation module. At the same time, the energy consumed by performing steering, acceleration and deceleration is also minimized. Finally, in the simulation process, we simulate one direction two lanes scenario. The result shows that the proposed method can effectively handle multi-lane platoon re-configuration scenario.
Chen, Guosheng, Wu, Jian, Li, Shuai, Zhang, Jinghua, Du, Zhiqiang, Wang, Guojun, Chen, Zhicheng
The Design of Safe-Reliable-Optimal Performance for Automated Driving Systems on Multiple Lanes with Merging Features2020-01-01224/14/2020
Safety function for automated driving systems including advanced driver assistance systems and autonomous vehicle systems is very important. Inside safety function, predictive judge sub-function should be designed with the consideration of more and more penetration of automated driving vehicles. This paper presents the design on multiple lanes with merging features based on the author's previous Patent JP2019-147944 using predictive time-head-way and time-to-collision maps. In the author's previous work (Model Predictive Control for Hybrid Electric Vehicle Platooning Using Slope Information-Published on IEEE Transactions on Intelligent Transportation Systems), a model predictive control framework was designed. Due to the difficulty to detail the sub-safety function deeply with merging features, few works are found to deal with sensor platforms focusing on rear side, and situations of merging lane side with the consideration of relative relation variations with other vehicles and road border markers. However, performance enhancement is needed assuring 100% safety-reliability-optimality and single-objectivity. Also, platforms of on-board sensors including side and rear view are needed to deal with false negative operations and false positive operations. The optimal operation line model of human factors is designed based on time-head-way (reliability), time-to-collision (safety), and combinations of time-head-way and time-to-collision (optimality). The general theory of model predictive control is used to find the target. The model based methodology is applied to solve the human factor model of risk feeling based on only time-head-way and time-to-collision for the human reaction and acceptance metric. Experimental results validated the effectiveness of the proposed approach. The model parameters can be calibrated internationally by tuning the metric of cooperativeness. The target of the predictive judge sub-function is to move the operation point to the specified area. The predictive judge sub-function on high level is decisive for regulation control to move the operation point from difficult areas to the target area in future.
Yu, Kaijiang
LiDAR-Based Urban Autonomous Platooning Simulation2020-01-07174/14/2020
The technological advancements of Advanced Driver Assistance Systems (ADAS) sensors enable the ability to; achieve autonomous vehicle platooning, increase the capacity of road lanes, and reduce traffic. This article focuses on developing urban autonomous platooning using LiDAR and GPS/IMU sensors in a simulation environment. Gazebo simulation is utilized to simulate the sensors, vehicles, and testing environment. Two vehicles are used in this study; a Lead vehicle that follows a preplanned trajectory, while the remaining vehicle (Follower) uses the LiDAR object detection and tracking information to mimic the Lead vehicle. The LiDAR object detection is handled in multiple stages: point cloud frame transformation, filtering and down-sampling, ground segmentation, and clustering. The tracking algorithm uses the clustering information to provide position and velocity of the Lead vehicle which allows for vehicle platooning. This paper covers the LiDAR object detection and tracking algorithms as well as the autonomous platooning control algorithms which were tested in a simulation environment. Test results illustrate that the Follower vehicle was able to attain the autonomous platooning based on the LiDAR data.
Alzu'bi, Hamzeh, Tasky, Tom
What If the Speed Had Been Less? Causation in Time Limited and Distance Limited Hazards2020-01-08814/14/2020
With a path intrusion incident, it is almost always the case that the collision would have been avoided if the pedestrian had not run out, or if the vehicle on the minor road had stopped, or so on. However should the other party be thought to have been travelling at an excessive speed, often the reconstructionist is asked to make a calculation of what whether the collision would, at some alternative speed say equal to the speed limit, still have occurred. In that way causation is addressed. The paper distinguishes between those hazards which are distance limited and those which are time limited, giving definitions of the two types. Distance limited hazards are deterministic, but time limited hazards have a probabilistic basis. This difference has important implications for causation. For a hazard at a fixed distance, there is a well known formula for calculating whether the collision would have been avoided at a slower alternative speed. However a time limited hazard often has no clear cut boundary between avoided/not avoided. According to the warning time during which the hazard develops, the alternative speed of the vehicle may mean that a collision would certainly be avoided, the alternative speed may have no effect, or the effect of the alternative speed may be in between. A method is given for estimating the effect of a slower speed. A further type of path intrusion is where the pedestrian, or driver on a minor road, has seen the oncoming vehicle but gauged that there was time to cross in front of it. This also is considered, with its implications for causation. Traffic lights, where one must not go over on red, have similarities and differences with path intrusion incidents. The paper gives a formula for the maximum speed at which a traffic light might be approached if drivers made the best choices, with a discussion of the difference between the unrealistic result of this calculation and a realistic maximum.
Searle, John
Mapping Canada - Centimeter by Centimeter19AVEP11_0511/1/2019
A Montreal-based company leverages artificial intelligence to take on the task of developing high-definition maps of Canada. Fully-automated vehicles will only be as smart as the datasets they use to determine their driving pathways. Jakarto Cartographie 3D, a young company based in Montreal, Canada, is working on artificial-intelligence (AI)-powered, high-definition (HD) maps that it claims offer 2-3 cm (.787- to 1.2-inch) absolute precision and relative precision measured in millimeters. In other words, better maps that will allow for better automated vehicles (AVs). Started two years ago, Jakarto currently has three Nissan NV200 mapping vans equipped with a data collection unit that contains five cameras, a GPS unit and two ZF-supplied lidar sensors that each generate one million points per second. Jakarto calls the resulting maps RoadSkeleton, claiming they'll be beneficial for smart cities and AVs.
Blanco, Sebastian
RDS Phrase ListsJ2540/1_201906 (Current)6/11/2019
This SAE Standard provides a table of textual messages meeting the requirements for expressing “Radio Data Systems” (RDS) phrases commonly used in the ITS industry. They can be used both over the RDS subcarrier transmission media as part of a 37-bit long “Group 8a message” as well as being used to provide a common content list of phrases used in a wide number of other media and applications. This document SHALL define the normative index values to be used, extending the CEN established list to provide phrases needed by US practitioners. This standard provides non-normative textual phrases which MAY be used by implementers to ensure intelligible results. This document SHALL follow the formats and rules established in SAE J2540 in the expressions, manipulations, and use of such tables. It should be pointed out that within the rules established by this document a variety of final table are all considered “compliant” with the document, and may vary as fits the needs of implementers.
V2X Core Technical Committee
Messages for Handling Strings and Look-up Tables in ATIS StandardsJ2540_201906 (Current)6/11/2019
This SAE Standard defines methods and messages to efficiently translate sequences of text and other types of data into and out of indexed values and look-up tables for effective transmission. This document defines: a Methods and Data Elements for handling indexes and strings in ATIS applications and message sets b Message Sets to support the delivery and translations of tables used in such strings c Tables of Nationally standardized strings for use in ATIS message descriptions And examples of each in illustrative portions. While developed for ATIS use, the methods defined in this document are useful for any textual strings in any Telematics applications found both in Intelligent Vehicles and elsewhere.
V2X Core Technical Committee
Developing Knowledge and Understanding for Autonomous Systems for Analysis and Assessment Events and CampaignsTBMG-343345/1/2019
There are many challenges in developing complete performance ontologies and test methodologies to define and evaluate the performance of autonomous systems. Chief among them is the dynamic environment in which the autonomous system is expected to operate. Change in the autonomous system’s environment is expected to affect system performance. Test methodologies have to include all aspects of this dynamic environment.
Behavior of Electric Scooter Operators in Naturalistic Environments2019-01-10074/2/2019
The use of electric scooters (e-scooters), which are more generally categorized as motorized scooters, has undergone explosive growth owing to “scooter share” programs in which an e-scooter is rented for a limited period of time. The near-spontaneous ubiquity of e-scooters has prompted government and scooter share companies to address issues partly motivated by concerns related to the inclusion of a large population of e-scooters into vehicular traffic. These issues are influenced by the decisions and behaviors of the scooter operators, who, despite being licensed to drive passenger vehicles, potentially have limited experience operating an e-scooter in the presence of traffic. E-scooters are in a relative unique position where they are small enough to negotiate pedestrian traffic, yet fast enough to travel on roadways. This enables an e-scooter operator to change when and where he rides, e.g., from traveling on a sidewalk to riding in a clear traffic lane in order to avoid a group of pedestrians standing at an intersection. Such changes may catch nearby motorists off-guard, thereby increasing the risk of a collision with the e-scooter. The present observational study assessed e-scooter rider behavior in west Los Angeles, a region with a robust presence of rental e-scooters. The large population, preponderance of e-scooters, and high traffic volumes provide an exemplary area to observe not just how drivers and e-scooter riders adapt to one-another’s presence, but also the increased risk of an interaction between e-scooters with other vehicles and pedestrians. Operator behavior of rented e-scooters is quantified and reviewed according to current regulations, public concerns regarding e-scooters, and behaviors present that may affect an individual’s ability to safely operate an e-scooter in the presence of traffic, including both vehicular and pedestrian.
Todd, Jay, Krauss, David, Zimmermann, Jacqueline, Dunning, Amber
Examples of Indicating Occupied Spacetime in Traffic Simulation Results2019-01-14033/25/2019
Traffic simulations could be beneficial to evaluate systems aiming to improve traffic safety and/or throughput. Possibly the simulation may include rather larger number of vehicles. Especially in the junctions, on a two dimensional Cartesian space, trajectory plots are likely to have intersections with each other. However, the intersections do not necessarily mean collisions; hence, evaluation may require animating the result over a period of time, possibly repetitively. This work aims to add time as one more axis to the plot and indicate space that each road user (a vehicle, a pedestrian, or a personal transporter user) occupies at a given time as a rectangle. In addition, this work would connect vertices of the rectangles of the same road user over time. The resultant plot of the trajectory of one particular road user would be similar to a duct or tube; if a particular road user maintains straight forward trajectory with a non-zero constant speed, it would look like a straight tube with slope. A vehicle making a turn at a corner would be similar to a spatially curved tube. If any intersection of such representation would imply a collision between two road users; thus improving the possibility of explicitly evaluating traffic safety. In the resultant 3D plot, it would be also possible to visually observe propagation of congestion within the traffic flow depending on the situations and/parameters. Regarding the traffic simulation, this work would utilize SUMO open source traffic simulation software with simple junctions. To visualize the traffic, this work would employ matplotlib package of open source SciPy stack for python.
Lee, Kangwon
Prediction of Weather Impacts on Airport Arrival Meter Fix Capacity2019-01-13503/19/2019
This paper introduces a data driven model for predicting airport arrival capacity with 2-8 hour look-ahead forecast data. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport’s arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system. Severe imbalances between demand and capacity occur most frequently when the airport capacity is severely degraded due to either bad airport terminal surface weather or inclement convective weather around airport arrival fixes. A model that predicts the weather-impacted airport arrival meter fix throughput may help ATM personnel to plan GDP operations more efficiently. This paper identifies the characteristics of air traffic flow across arrival meter fixes at Newark Liberty International Airport (EWR). The proposed approach, based on machine-learning methods, is developed to predict the weather impacted EWR arrival Meter Fix (MF) throughput. Sector forecast coverage is used to envision the weather impact on airport arrival MF flow, and the validation is accomplished by using Convective Weather Avoidance Model (CWAM) 0.5 to 2-hour and Collaborative Convective Forecast Product (CCFP) 4 to 8-hour look-ahead forecast data for the period of April-September in 2014. Furthermore, the regression tree ensemble learning of random forests approach for translating a sector forecast coverage model to EWR arrival meter fix throughput is examined. The results suggest that ATM decision makers in charge of MF flow control and GDP planning may benefit from adopting the airport arrival meter capacity prediction models to estimate the inclement weather impacts.
Wang, Yao
Still Unsettled on Vehicle Connectivity Standard19AVEP03_103/1/2019
As data and data-sharing become more crucial to the transportation evolution, the auto sector has yet to gain consensus on the best connectivity format. As autonomous vehicles inch closer to reality, a diverse range of companies and public entities are exploring ways to maximize their positive impact on traffic flows and congestion. Communication at all levels, both between vehicles and between public and private interest groups, will be an important element for improving efficiency.
Costlow, Terry
Road Tested19AVEP03_113/1/2019
Transportation-infrastructure expert Kirk Steudle reflects on the rapid progress toward the connected-AV future and the challenges ahead. In the auto industry, mechanical and electrical engineers work from the tire up. Civil engineers work from the tire down,” quips Kirk Steudle. “And although it's taken a while for both to understand each other's jargon, the connected-and-autonomous vehicle is forcing them all together-to solve problems for society's mobility.” Steudle, a registered professional engineer, has been at the vehicle-to-road nexus his entire career. Last October he retired as director of the Michigan Dept. of Transportation where, among many achievements, his leadership helped put the state and its core industry in the vanguard of connected-car and AV-related developments, testing, and infrastructure standards. During his final year at MDoT, he also served as interim CEO of the American Center for Mobility, the new 500-acre AV proving ground and test center near Ann Arbor.
Brooke, Lindsay
Modeling the Road Ahead for AVs19AVEP03_123/1/2019
Detailed virtual environments are vital to developing, testing and validating autonomous systems. The next million miles of autonomous-vehicle test roadways are about to deploy from a start-up company's virtual-world toolbox. “For each mile of real-world autonomous-vehicle testing, developers will test hundreds of thousands of simulated driving miles,” declared Alex Goldberg, CTO of VectorZero, a Carlsbad, California, start-up company whose RoadRunner software product debuted in July 2018. The next release is nearing deployment.
Buchholz, Kami
A Real-Time Traffic Light Detection Algorithm Based on Adaptive Edge Information2018-01-16208/7/2018
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. On traffic light recognition stage, a tinny but effective convolution neural network (CNN), named TLRNet, classifies each traffic light RoI into its own class. In fact, deep learning (DL) is bad for detecting small object in many fields, so we use region proposal stage to get RoI and classification by CNN to achieve a good result. We validate our method both on Laboratory for Intelligent and Safe Automobiles (LISA) Traffic Lights Dataset and video sequences captured from Beijing’s streets. The experimental results prove that the proposed method can achieve a good result for the multi-scales traffic lights in the TX1 embedded platform, and reach a real-time performance at 28fps.
Yu, Guizhen, Lei, Ao, Li, Honggang, Wang, Yunpeng, Wang, Zhangyu, Hu, Chaowei
Intelligent Traffic Control Method for Emergency Vehicles Prioritization Based on DSRC Transportation System2018-01-16448/7/2018
Emergency Vehicles (EmVs) prioritization is critical to be studied in view of the effectiveness of emergency delivery. Adaptive traffic lights can be employed based on DSRC (Dedicated Short Range Communication) system, as vehicle status and traffic lights information can be delivered to Road Side Unit (RSU). In other research work of manipulating traffic lights, only the EmVs are considered. Therefore there are still risks for non-EmVs due to insufficient time of braking. This paper provides an adaptive traffic light control method which takes into account of EmVs and non-EmVs on all the directions of lanes at the road section. In this control method, three operation modes of traffic light are proposed and the traffic light can be converted among three operation modes: Normal mode, Warning mode and Priority mode. Moreover, a collision prediction of upcoming non-EmVs on the orthogonal lane of EmVs in the junction is performed, which results in non-EmVs protection within predefined distance to guarantee the safe mobility of no-EmVs in the orthogonal direction. Afterwards, the traffic light enters into Warning mode to provide a warning and buffering time for upcoming drivers. Then traffic lights turn into Priority mode until emergency vehicle leaves the junction. Before the traffic lights are back to the Normal mode, Warning mode is carried out again to ensure sufficient braking time for following non-EmVs in case of change of traffic lights. In a summary, this adaptive traffic light control method not only protects EmVs, but also improves the safe mobility of non-EmVs. Finally simulation is carried out and the results show that this method can greatly improve the efficiency and safety for EmVs and non-EmVs and reduce the accident rate in the junction.
Guo, Peng, Wang, Mengdan, Rong, Hui, Wang, Wenyang
Autonomous Vehicle Engineering: August 201818AVEP088/2/2018
Editorial V2Reality Blockchain Unchained! The weird world of cryptocurrency exists because of the intense mathematics of blockchain technology. The mobility sector is looking beyond Bitcoin to put blockchain to work in potentially game-changing ways. Are Blockchain and 'Smart Contracts' the Secure Future? Legal risk and reward of blockchain and smart contracts as a prescription for automotive applications Software Building Blocks for AV Systems Elektrobit's unique software framework is designed to smooth development of automated driving functions. Cyber Security Goes Upstream The first cloud-based solution for connected vehicles was born in Israel and is now pilot testing at global OEMs. Electronic Architectures Get Smart Upgradable, scalable and powerful new architectures will help enable data-hungry connected, autonomous vehicles. Aptiv's VP of Mobility Architecture explains. Reliability, Safety, and AV Development An overemphasis on safety without a robust and equivalent reliabili-ty process and organization will result in errors that could be catastrophic. Understanding the Self-Driving Revolution A new book on autonomy from one of the ultimate insiders. Software Rewrites the Rules Revenue streams and business models are changing as more vehicle functions move to software. Blackberry QNX's John Wall explains. Truck Platoons on the Move Trials increase to determine if fuel economy, safety improvements make platooning worthwhile-but issues still need to be resolved. Defanging Driverless Cars A pioneering program gives everyday people the chance to ride in an automated vehicle on public roads.
Study on Target Tracking Based on Vision and Radar Sensor Fusion2018-01-06134/3/2018
Faced with intricate traffic conditions, the single sensor has been unable to meet the safety requirements of Advanced Driver Assistance Systems (ADAS) and autonomous driving. In the field of multi-target tracking, the number of targets detected by vision sensor is sometimes less than the current tracks while the number of targets detected by millimeter wave radar is more than the current tracks. Hence, a multi-sensor information fusion algorithm is presented by utilizing advantage of both vision sensor and millimeter wave radar. The multi-sensor fusion algorithm is based on centralized fusion strategy that the fusion center takes a unified track management. At First, vision sensor and radar are used to detect the target and to measure the range and the azimuth angle of the target. Then, the detections data from vision sensor and radar is transferred to fusion center to join the multi-target tracking with the prediction of current tracks. Vision sensor uses Global Nearest Neighbor (GNN), and radar uses Probabilistic Data Association (PDA) for data association. For target detection, the vision sensor has high accuracy at azimuth angle and low accuracy at range, while radar has medium accuracy at azimuth angle and very high accuracy at range. The detection properties of two sensors should be considered when designing the association gate. Simulation based on real test data which was taken by a monocular camera and a 77GHz millimeter wave radar is performed in MATLAB. Simulation result indicates that the design of association gate has a great impact on fusion performance.
Wu, Xian, Ren, Jing, Wu, Yujun, Shao, Jianwang
Study on Test Scenarios of Environment Perception System under Rear-End Collision Risk2018-01-10794/3/2018
The foundation of both advanced driving assistance system(ADAS) and automated driving (AD) is an accurate environment perception system(EPS). However, evaluation and test method of EPS are seldom studied. In this paper, naturalistic driving environment was studied and test scenarios for EPS under rear-end collision risk were proposed accordingly. To describe driving environment, a new concept named environment perception element(EPE) was first proposed in this paper, which refers to all the objects that the EPS must perceive during driving. Typical environment perception elements include weather and light conditions, road features, road markings, traffic signs, traffic lights, other vehicles, pedal cyclists and pedestrians and others. Driving behaviors collected in Shanghai, China were classified and rear-end collision risk scenarios were obtained and described using EPEs. Probability distribution of EPEs was therefore obtained. Afterwards, the correlation between EPEs and risk level of scenarios (evaluated by maximum longitudinal deceleration) were revealed by means of Fisher’s Exact Test. Based on these two characteristics of driving environment, typical test scenarios for EPS were established with the help of cluster analysis, and the test scenarios were simulated in Prescan. These test scenarios were generally consistent with the probability distribution of EPEs, making the test results reliable. Results from this paper fill the gap between the high demand of dynamic and representative EPS test scenarios and the existing static picture database used in development and validation of EPS and are of great significance to the development of ADAS and AD in China.
Liu, Lin, Zhu, Xichan, Ma, Zhixiong
2021-12-29.TEST Drive Scenario Generation Based on Metrics for Evaluating an Autonomous Vehicle Controller2018-01-00344/3/2018
An important part of automotive driving assistance systems and autonomous vehicles is speed optimization and traffic flow adaptation. Vehicle sensors and wireless communication with surrounding vehicles and road infrastructure allow for predictive control strategies taking near-future road and traffic information into consideration to improve fuel economy. For the development of autonomous vehicle speed control algorithms, it is imperative that the controller can be evaluated under different realistic driving and traffic conditions. Evaluation in real-life traffic situations is difficult and experimental methods are necessary where similar driving conditions can be reproduced to compare different control strategies. A traditional approach for evaluating vehicle performance, for example fuel consumption, is to use predefined driving cycles including a speed profile the vehicle should follow. However, if the vehicle speed is part of the vehicle control output, a different vehicle evaluation framework is necessary. Here, speed constraints are defined based on route and traffic conditions, such as speed limits, traffic signs and signals, and the locations of surrounding vehicles. Hence, route generation is an important task for evaluating speed control algorithms. A route is a distance-based description of the road conditions and locations of traffic signs and signals. A driving scenario is defined as a route which also includes information about traffic density and the location of surrounding traffic as function of time. It is discussed how driving scenarios can be used to evaluate and compare different speed control algorithms. The generation of driving scenarios is performed in two steps, route generation and traffic data generation. First, two approaches are discussed for generating the route conditions, such as varying speed limits and locations of traffic signals, either using real road map data or to recreate from vehicle speed data. In a second step, traffic conditions are simulated using the software SUMO to generate speed profiles of surrounding vehicles on the road. To assure that the selected driving scenarios represent varying driving conditions, a set of metrics is selected and used for driving scenario selection.
Tamilarasan, Santhosh, Jung, Daniel, Guvenc, Levent
2021-12-29.TEST Overtaking or Merging? Eco-Routing Decision and Speed Trajectory with Full Terrain Information2018-01-00384/3/2018
With vehicle platooning becoming an important research field in recent years, it is now imperative to introduce platoons as part of the dynamic environment, considering overtaking and merging possibilities. This article studies optimal speed trajectories and longitudinal control with optimized energy efficiency for an autonomous vehicle with several preceding platoons and full terrain information. It aims at improving the energy efficiency of vehicles with Advanced Driver Assistance Systems (ADAS). A forward discrete dynamic programming (DDP) algorithm with distance as the discretization basis is used to derive speed trajectories in the trade-off between air drag reduction and energy saved by utilizing the road slope information. The problem is decomposed into decisions whether to overtake or to merge into the nearest platoon with the assumption of sufficient distance among platoons. During the process, speed choices and cost function reflect interactions among the controlled vehicle, the platoons, and the road. Simulations confirm that the energy consumed can be reduced significantly when tracking optimal trajectories compared to driving by the existing model predictive control (MPC) tracking strategy and linear quadratic regulator (LQR). For a trip of 500 m, if the primary velocity of the ego vehicle is 7.5 m/s and the initial state of a preceding platoon is 10 m from the ego car, 8 m/s, the energy cost saving of the proposed solution can be up to 3.45% compared by LQR. When there are two platoons whose original states are 10 m, 7 m/s, and 35 m, 7.5 m/s respectively, the energy saving of the ego car with initial velocity of 8 m/s is 3.07% compared by LQR and 1.99% by MPC. Simulations indicate the potential of energy efficiency of the proposed method for further studies with more sophisticated conditions. Sensitivity analysis has shown that the energy saving is not sensitive to the initial speed of the ego car when it is relatively low.
Li, Ting Jun, Shen, Minghao, Zheng, Hongyu
Introduction to Traffic Signal Data Loggers and their Application to Accident Reconstruction2018-01-05274/3/2018
Each year in the United States, approximately 1 million collisions occur at signalized intersections, representing over 15% of all collisions and almost 9% of traffic fatalities. Engineers seeking to understand the roadway, vehicular, and driver factors related to these collisions are often asked to investigate and assess the traffic signal timing, right of way issues, and the signal indications displayed to involved drivers during the period of time leading up to and including the impact events. Until relatively recently, investigators were limited by the absence of any recording devices within the systems used for traffic signal phasing and timing. Accident reconstruction methods have long relied on the generalized signal phasing and timings programmed for that intersection by the responsible jurisdiction, combined with the vehicle dynamics calculated for the collision sequence in conjunction with witness testimony regarding signal indications and phase changes. Recent technological advancements in signal timing data collection, recording, and logging can provide engineers and investigators with a new, time-specific, incident-relatable and more robust method of analyzing signalized intersection collisions. This paper presents the current state of the art for traffic signalization: Signal Timing Data Loggers. This paper also presents how to obtain, analyze, and interpret the data logger data and possible applications of such data to accident reconstruction.
Przybyla, Jay, Rush, Thomas, Palframan, Kelly, Melcher, Daniel
The Impact of the Autonomous Vehicle in Society and in the Urban Mobility in the City of São Paulo2017-36-038611/7/2017
The safety, reliability and efficiency in the progress of the autonomous vehicle have increased in recent years. In parallel, companies in the segment of people transportation, either individually or shared, took the world leadership using smartphone app into a new concept of urban mobility with conventional vehicles with drivers, starting consequently a change of habit of the population, and defying the laws of local transport. These services for urban mobility are related as tendencies of driving forces in the face of the relevance of the limitations of resources, population density, greater awareness toward the environment and traffic congestion. The acquisition of the “own vehicle” as currently, conceived and successful by Alfred Sloan in the 1920s, has become a question for future generations. This study shows that the provision of a more secure service, reliable, and efficient, will enable a significant reduction in total cost of ownership to the increasingly sophisticated and highly informed generation Z, who continually seeks to optimize its resources, availability and quality of life in real time. It also shows how the autonomous vehicles will transform urban mobility in the next 20 years and the impact generated in the city of São Paulo, the largest city in Latin America and with more than 12 million inhabitants.
Briganti, Murilo Cesar Perin, de Mello Filho, Luiz Vicente Figueira, Cardamoni, Raquel, Iano, Yuzo
EDITORIAL: EVs lack a robust charging grid17AUTP10_0410/1/2017
The flames lit up the sky when the electric-power substation in my town blew up one night last August. TV news had it covered: A transformer at the DTE Energy site had exploded, immediately knocking out power for over 4,000 homes and businesses. More than 9,000 residents dug out flashlights, lit candles and sweated the summer heat. The utility acted quickly, bringing in a convoy of five flatbed trailers-DTE Energy's mobile emergency units-each carrying a large diesel-electric generator rig. Humming away behind a makeshift fence and “DANGER: High Voltage” signs, the generator trailers formed the nucleus of a temporary grid while an army of helmeted technicians worked to get the juice flowing. Two days after the fire, the town's lights were back on and my beer was cold again. But as I write this seven weeks later, the emergency generators are still powering the town. And the utility still doesn't know for certain the cause of the explosion.
Brooke, Lindsay
Driverless cars and freeway traffic flow17AUTP10_0310/1/2017
Analysis shows platooning and wave damping can reduce congestion. The integration of driverless cars onto multilane freeways brings challenges for vehicle and infrastructure planners, not the least of which is ever increasing congestion. The threshold for serious congestion is a population of 300,000. The U.S. currently has 51 traffic-congested cities with population of 380,000 or more. Can driverless vehicles with full vehicle-to-infrastructure (V2I) connectivity favorably affect congestion? The answer is yes. This means construction of new freeway lanes may not be needed except in exceptional cases.
Fuhs, Allen
A Method towards the Systematic Architecting of Functionally Safe Automated Driving- Leveraging Diagnostic Specifications for FSC design2017-01-00563/28/2017
With the advent of ISO 26262 there is an increased emphasis on top-down design in the automotive industry. While the standard delivers a best practice framework and a reference safety lifecycle, it lacks detailed requirements for its various constituent phases. The lack of guidance becomes especially evident for the reuse of legacy components and subsystems, the most common scenario in the cost-sensitive automotive domain, leaving vehicle architects and safety engineers to rely on experience without methodological support for their decisions. This poses particular challenges in the industry which is currently undergoing many significant changes due to new features like connectivity, servitization, electrification and automation. In this paper we focus on automated driving where multiple subsystems, both new and legacy, need to coordinate to realize a safety-critical function. This paper introduces a method to support consistent design of a work product required by ISO 26262, the Functional Safety Concept (FSC). The method arises from and addresses a need within the industry for architectural analysis, rationale management and reuse of legacy subsystems. The method makes use of an existing work product, the diagnostic specifications of a subsystem, to assist in performing a systematic assessment of the influence a human driver, in the design of the subsystem. The output of the method is a report with an abstraction level suitable for a vehicle architect, used as a basis for decisions related to the FSC such as generating a Preliminary Architecture (PA) and building up argumentation for verification of the FSC. The proposed method is tested in a safety-critical braking subsystem at one of the largest heavy vehicle manufacturers in Sweden, Scania C.V. AB. The results demonstrate the benefits of the method including (i) reuse of pre-existing work products, (ii) gathering requirements for automated driving functions while designing the PA and FSC, (iii) the parallelization of work across the organization on the basis of expertise, and (iv) the applicability of the method across all types of subsystems.
Mohan, Naveen, Törngren, Martin, Behere, Sagar
Impact of Different Desired Velocity Profiles and Controller Gains on Convoy Driveability of Cooperative Adaptive Cruise Control Operated Platoons2017-01-01113/28/2017
As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC. The acceleration of the previous vehicle is available to the next vehicle as input, and the simulations are performed as Cooperative Adaptive Cruise Control of a convoy of vehicles. Individual vehicle acceleration profiles have been analyzed for driveability for two different velocity profiles that are followed in a stretch of 720 m between stop signs. The controller gains have been re-tuned based on the parameter space robust control PID approach for driveability and compared with the original gains. The US06 SFTP drive cycle has also been used for the comparison of the two different controller gain sets.
Tamilarasan, Santhosh, Guvenc, Levent
Region Proposal Technique for Traffic Light Detection Supplemented by Deep Learning and Virtual Data2017-01-01043/28/2017
In this work, we outline a process for traffic light detection in the context of autonomous vehicles and driver assistance technology features. For our approach, we leverage the automatic annotations from virtually generated data of road scenes. Using the automatically generated bounding boxes around the illuminated traffic lights themselves, we trained an 8-layer deep neural network, without pre-training, for classification of traffic light signals (green, amber, red). After training on virtual data, we tested the network on real world data collected from a forward facing camera on a vehicle. Our new region proposal technique uses color space conversion and contour extraction to identify candidate regions to feed to the deep neural network classifier. Depending on time of day, we convert our RGB images in order to more accurately extract the appropriate regions of interest and filter them based on color, shape and size. These candidate regions are fed to a deep neural network. In this paper, we focus on a region of interest (ROI) proposal method, which works to minimize false negative and false positive candidate regions that are then fed to the deep neural network for classification. This camera-only solution has applications for many levels of autonomy, from driver assistance technology (SAE Level 2) to fully automated vehicles (SAE Level 4).
Moosaei, Maryam, Zhang, Yi, Micks, Ashley, Smith, Simon, Goh, Madeline J., Nariyambut Murali, Vidya
Cloud-Driven Traffic Monitoring and Control Based on Smart Virtual Infrastructure2017-01-00923/28/2017
The new cyber-technological culture of the transport control based on virtual road signs and streetlight signals on the screen of car is the future of Humanity. A cyber-physical system (CPS) Smart Cloud Traffic Control, which realizes the mentioned culture, is proposed; it is characterized by the presence of the digitized regulatory rules, vehicles, infrastructure components, and also accurate monitoring, active cloud streetlight-free cyber control of road users, traffic lights, automatic output of operational regulatory actions (virtual traffic signs and traffic signals) to monitor of each vehicle. The main components of the cyber-physical system are the following: infrastructure, road users and rules, which have digital representation in cyberspace to realize a route, based on digital monitoring and cloud mobile control. We offer innovative services, which implement digital monitoring and cloud control as a scalable prototype of a global system that uses the following technology: precise positioning of moving and stationary objects, digital cartography, cyber-physical systems and Internet of Things, Advanced Wireless Communication and Big Data Analytics. The basic idea is to improve the quality and safety of traffic through the implementation of metric regulation of traffic, based on digital monitoring and active cloud cyber control, and also the use of intelligent virtual traffic lights and signs, which gives an opportunity to significantly improve the comfort of a car trip, reduce the overhead in time and cost of route execution. Components for the implementation of global cloud traffic control services are the following: 1) Smart is the definition of the process or phenomenon associated with the network interaction of the addressable system components in time and space between themselves and the environment, based on self-learning technologies to achieve their goals. 2) The Smart Cyber-Physical System is a set of communicatively connected to the network addressable virtual and real components in the digitized metric space with features of adequate physical monitoring, optimal cloud control and self-learning in real time to achieve their goals. 3) Internet of Things is a structure of cyber-physical systems, combining the centers of large data, knowledge, services and applications aimed to monitor and control of smart processes and phenomena in the digitized physical space by using the sensors actuators to provide high standards of living and saving the planet environment. 4) Computing is a branch of knowledge, focused on research, design and application of systems, networks and cloud-mobile services for monitoring and control of cyber-physical processes and phenomena. The development of computing, the main function of which is cyber control, should only be considered in conjunction with the real or the physical world, a part of which is humanity. There is interaction between the two worlds, the real and the virtual ones: humanity always poorly manages the real world and creates computing as his assistant. As a perfect mechanism, computing takes control of technological processes in humanity. 5) The market feasibility of the global cloud services for traffic control without physical infrastructure, traffic lights and road signs is at least 100 billion dollars. The economic effect of the transfer of road infrastructure in cyberspace, including the license plates is 500 billion dollars a year.
Hahanov, Vladimir, Gharibi, Wajeb, Litvinova, Eugenia, Chumachenko, Svitlana, Ziarmand, Arthur, Englesi, Irina, Gritsuk, Igor, Volkov, Vladimir, Khakhanova, Anastasiia
Method and System for Air Traffic Rerouting for Airspace Constraint ResolutionTBMG-265233/1/2017
NASA's National Airspace System Constraint Evaluation and Notification Tool (NASCENT) is a dynamic constraint avoidance system that automatically analyzes routes of aircraft flying, or to be flown, in or near constraint regions, and attempts to find more time- and fuel-efficient reroutes around current and predicted constraints. NASCENT provides an evaluation of avoidance routes that saves more than a user-specified number of minutes of wind-corrected flying time savings for all the 20 Air Route Traffic Control Centers (ARTCCs or Centers) in the National Airspace System (NAS) simultaneously. The dynamic constraint avoidance route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time. This system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.
Miles-In-Trail with Passback Restrictions for Use in Air Traffic ManagementTBMG-2600212/1/2016
NASA has developed a unique innovation to compute passed back spacing requirements in air traffic management. The air traffic managers of the National Airspace System (NAS) in the United States regularly implement various Traffic Management Initiatives (TMI) to handle traffic in a safe and efficient manner. One such initiative is the Miles-in-Trail restriction. Imposed Miles-in-Trail is the value of spacing required between aircraft flying along a certain path. They help air traffic managers control the flow of aircraft into and out of an air traffic control facility. Miles-in-Trail can be implemented independently or in conjunction with other TMIs (e.g., a severe weather avoidance plan route, or a Playbook route). This model computes passback restrictions given the imposed constraint, the start and end times, the boundaries at where those restrictions need to be passed back, and the amount of maximum ground and airborne delay allowed.
Aeronautical Data Link and Radar Simulator (ADRS)TBMG-2570311/1/2016
Air traffic management research needs to adequately address all players, including flight crews, air traffic controllers/managers, and airline dispatchers. Interactions between the different stakeholders are crucial elements for the viability of a given concept. A simulation capable of addressing this type of distributed decision-making needs to meet several requirements in terms of fidelity, operator proficiency, and number of participants. Most research facilities and laboratories can provide a sufficient fidelity for one particular aspect, but lack in the other aspects because of budget, personnel, and proprietary constraints.
Volvo, Uber share the ride to safety with autonomy16AUTP10_0710/1/2016
The news that Volvo Cars, renowned for its safety focus, and ride-sharing company Uber, are working together to develop next generation autonomous driving (AD) cars eventually reaching full SAE Level-5 standard (no steering wheel or controls), may bring comfort to those who are scared, skeptical or just scorn the advent of being driven by such radical robotics. But this latest development sees a further step to AD being taken in parallel with Volvo's avowed intent that no one traveling in its new models from 2020 onwards will be killed or seriously injured. That bold statement was first uttered in 2007, presaging the introduction or development of a plethora of safety features that the automaker believes will enable it to achieve its target.
Birch, Stuart
Prediction formula of Aerodynamic Drag Reduction in Multiple-Vehicle Platooning Based on Wake Analysis and On-Road Experiments2016-01-15964/5/2016
An experimental study on reducing aerodynamic drag and improving fuel economy through vehicle platooning was conducted to develop an Intelligent Transport System (ITS) with good fuel economy of the entire vehicle-based transportation society. The objectives of the present study are to achieve a simple and quick approach to estimating the aerodynamic drag reduction rates of vehicle platooning. This paper reports the prediction formula, including the conditions of various types of vehicles in multiple-vehicle platooning, based on the power law of a free turbulent axisymmetric wake and on-road experimental results. Note, the prediction formula in this study does not fully include the effect of various type of wake deficit patterns due to rear shape of vehicle and atmospheric wind. Therefore, continuous study is needed to examine the applicable limit.
Tadakuma, Kenji, Doi, Tomoyuki, Shida, Mitsuhisa, Maeda, Kazuhiro
Challenges in Autonomous Vehicle Testing and Validation2016-01-01284/5/2016
Software testing is all too often simply a bug hunt rather than a well-considered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles. This paper identifies five major challenge areas in testing according to the V model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and fail-operational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively relaxed operational scenarios, use of a monitor/actuator pair architecture to separate the most complex autonomy functions from simpler safety functions, and fault injection as a way to perform more efficient edge case testing. While significant challenges remain in safety-certifying the type of algorithms that provide high-level autonomy themselves, it seems within reach to instead architect the system and its accompanying design process to be able to employ existing software safety approaches.
Koopman, Philip, Wagner, Michael
Generation and Usage of Virtual Data for the Development of Perception Algorithms Using Vision2016-01-01704/5/2016
Camera data generated in a 3D virtual environment has been used to train object detection and identification algorithms. 40 common US road traffic signs were used as the objects of interest during the investigation of these methods. Traffic signs were placed randomly alongside the road in front of a camera in a virtual driving environment, after the camera itself was randomly placed along the road at an appropriate height for a camera located on a vehicle’s rear view mirror. In order to best represent the real world, effects such as shadows, occlusions, washout/fade, skew, rotations, reflections, fog, rain, snow and varied illumination were randomly included in the generated data. Images were generated at a rate of approximately one thousand per minute, and the image data was automatically annotated with the true location of each sign within each image, to facilitate supervised learning as well as testing of the trained algorithms. A deep convolutional neural network was built using 8 hidden layers, 1.5 million free parameters, and 250,000 neurons, with unique configurations optimal for traffic sign classification. This network was then trained using the above mentioned dataset. A high cross-validation accuracy of 98% with stable k-fold validation energy was achieved. This network, trained using virtual images, was then tested on real-world images with promising results, and the network was able to consistently classify signs that appear much smaller and farther away than those in the images it was trained on. The algorithm also attempted to classify signs for which it had not been trained, and predictably classified such signs using the most similar label.
Nariyambut Murali, Vidya, Micks, Ashley, Goh, Madeline J., Liu, Dongran
Real Time Drivable Surface Determination Based on Stereo Vision2016-01-01694/5/2016
For any autonomous vehicle, understanding which area around the vehicle is free or drivable is a key component. It is important to find road boundaries such as ditches, curbs or guard rails. Finding small objects on the road, that might be blocking the vehicle path, is also critical. Most prototypes for autonomous vehicles feature laser scanners for this purpose. We propose a stereo vision based system as redundancy or as a cost efficient replacement for laser scanners in the application of drivable surface determination. The system generates a detailed map that indicates which area in front of the vehicle that is considered to be drivable and non-drivable. The base for this map is a dense 3D point cloud generated from the stereo vision system. The left and right images are used to create a disparity image which is then translated into a 3D point cloud. The 3D points are used to generate a detailed elevation grid of the observed area. The gradient of this grid is then used for the judgement of drivable/non-drivable. The 3D point cloud and the drivability map is generated in real time at 22 Hz on production intent hardware. We demonstrate the performance on a variety of use cases. We show that stereo vision is a strong candidate to replace the laser scanners used in many autonomous driving applications. At the same time our stereo vision system features many other applications, such as EuroNCAP AEB, lane tracking and traffic sign recognition.
Eidehall, Andreas, Askling, Joel, Spies, Hagen
Highway Sensor Deployment Gives Valuable Data to ‘Connected’ DriversTBMG-2334111/1/2015
In an effort to improve traffic flow, driver safety, and asset management, the Michigan Department of Transportation (DOT) has installed 17 sensors on a 50-mile stretch of one of the state’s busy Interstate highways. The “connected corridor” deployment will provide useful data for drivers of cars equipped with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technology.
A Compressed Sensing and Sparsity Based Approach for Estimating an Equivalent NIR Image from a RGB Image2015-01-03104/14/2015
Camera sensors that are made of silicon photodiodes and used in ordinary digital cameras are sensitive to visible as well as Near-Infrared (NIR) wavelength. However, since the human vision is sensitive only in the visible region, a hot mirror/infrared blocking filter is used in cameras. Certain complimentary attributes of NIR data are, therefore, lost in this process of image acquisition. However, RGB and NIR images are captured entirely in two different spectra/wavelengths; thus they retain different information. Since NIR and RGB images compromise complimentary information, we believe that this can be exploited for extracting better features, localization of objects of interest and in multi-modal fusion. In this paper, an attempt is made to estimate the NIR image from a given optical image. Using a normal optical camera and based on the compressed sensing framework, the NIR data estimation is formulated as an image recovery problem. The NIR data is considered as missing pixel information and its approximation is done during the image recovery phase. Thus, for a given optical image, with NIR data being considered as missing information, the recovered NIR data gives the corresponding NIR image. The motivation behind using compressed sensing for NIR estimation is that, it uses a ‘Dictionary Learning Technique’ which is capable of retaining a linear relationship between the color image feature values with NIR data. Using this proposed method, we have been able to estimate NIR images directly from optical images with reconstructed PSNR values ranging from 10 to 20.5 dbs. Visual examination of the estimated data also concurs that there is a good match between the estimated and original NIR images. In the automotive domain, the proposed method would help in a myriad of ADAS applications that use optical cameras viz. night time pedestrian detection, collision avoidance, traffic sign recognition etc.
Danymol, R, Kutty, Krishnan
Target Population for Intersection Advanced Driver Assistance Systems in the U.S.2015-01-14084/14/2015
Intersection crashes are a frequent and dangerous crash mode in the U.S. Emerging Intersection Advanced Driver Assistance Systems (I-ADAS) aim to assist the driver to mitigate the consequences of vehicle-to-vehicle crashes at intersections. In support of the design and evaluation of such intersection assistance systems, characterization of the road, environment, and drivers associated with intersection crashes is necessary. The objective of this study was to characterize intersection crashes using nationally representative crash databases that contained all severity, serious injury, and fatal crashes. This study utilized four national crash databases: the National Automotive Sampling System, General Estimates System (NASS/GES); the NASS Crashworthiness Data System (CDS); and the Fatality Analysis Reporting System (EARS) and the National Motor Vehicle Crash Causation Survey (NMVCCS). Straight Crossing Path (SCP), Left Turn Across Path Opposite Direction (LTAP/OD), and Left Turn Across Path Lateral Direction (LTAP/LD) made up 78% to 98% of all crossing path crashes. Furthermore, between 73% and 95% of these top three crossing path scenarios occurred at intersections. The analysis in this paper, therefore, focused on SCP, LTAP/OD, and LTAP/LD crashes at intersections, referred to as simply intersection crashes for the remainder of this summary. This paper quantified traffic control devices, speed limits, environmental conditions, alcohol involvement, and driver age in intersection crashes. Using the additional driver and crash contributing data included in the NMVCCS data, this paper also quantified critical reason for crashes, maneuvers approaching the intersection and avoidance maneuvers in intersection crashes. The results of this study are crucial for the design and evaluation of I-ADAS.
Kusano, Kristofer D., Gabler, Hampton C.
High Speed Optimal Yaw Stability of Tractor-Semitrailers with Active Trailer Steering2014-01-00934/1/2014
Most tractor-semitrailers are fitted with multi-axle trailers which cannot be actively steered, and such vehicles with an articulated configuration are inclined to exhibit instability such as trailer swing, jack-knifing, and rollover at high speed. Proposed in this paper is an optimal control of the yaw stability of tractor-semitrailers at high speed by applying an active trailer's steering angle. An optimal control algorithm is designed by employing a 3-DOF vehicle model in the yaw plane. The optimal linear quadratic regulator (LQR) approach is used with a cost function including sideslip angles, yaw rates of both tractor and trailer, and trailer's steering angle. The yaw stability at the high speed is also quantified by the dynamic performance measurements of lateral path deviation, hitch angle and rearward amplification (RA). The algorithm is evaluated by co-simulations using TruckSim and Matlab/Simulink softwares. Simulation results under double lane change maneuvers show that trailer swing and jack-knifing are suppressed with a small path-tracking error and it is concluded that the optimal control of semi-trailer steering can improve the yaw stability at high speed.
Lin, Xiaomin, Ding, Nenggen, Xu, Guoyan, Gao, Feng
Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions2013-01-23019/17/2013
When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required.
Wang, Yao, Grabbe, Shon
Items per page:
1 – 50 of 130