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Viewing 1 to 30 of 542
2017-06-05
Technical Paper
2017-01-1778
Enrico Galvagno, Antonio Tota, Mauro Velardocchia, Alessandro Vigliani
Abstract This paper explores the potentiality of reducing noise and vibration of a vehicle transmission thanks to powertrain control integration with active braking. Due to external disturbances, coming from the driver, e.g. during tip-in / tip-out maneuvers, or from the road, e.g. crossing a speed bump or driving on a rough road, the torsional backlashes between transmission rotating components (gears, synchronizers, splines, CV joints), may lead to NVH issues known as clonk. This study initially focuses on the positive effect on transmission NVH performance of a concurrent application of a braking torque at the driving wheels and of an engine torque increase during these maneuvers; then a powertrain/brake integrated control strategy is proposed. The braking system is activated in advance with respect to the perturbation and it is deactivated immediately after to minimize losses.
2017-05-30
Technical Paper
2017-01-5002
James Bradley Skarie
Abstract Antilock braking systems (ABS) are inherently limited by the static coefficient of friction (µ) between a vehicle’s tires and the road surface. This paper explores a unique active safety concept, Integrated Coefficient Enhancement (ICE), which works to improve ABS well beyond their present limits. The ICE concept was developed using a basic physics principle: to change µ between two surfaces, at least one of the surfaces must be altered in some way. By quickly deploying a specially designed tractive medium (TM) to aid in directional stability and braking, hazardous situations can be greatly mitigated. This paper describes the features and testing results of this TM and its aerodynamic-mechanical-electronic deployment apparatus. Under all slippery road conditions tested, the developed TM mitigated skidding, with improvements that ranged from 20% to several hundred percent, depending on conditions and deployment rates.
2017-03-28
Technical Paper
2017-01-0091
Songyao Zhou, Gangfeng Tan, Kangping Ji, Renjie Zhou, Hao Liu
Abstract The mountainous roads are rugged and complex, so that the driver can not make accurate judgments on dangerous road conditions. In addition, most heavy vehicles have characteristics of large weight and high center of gravity. The two factors above have caused most of the car accidents in mountain areas. A research shows that 90% of car accidents can be avoided if drivers can respond within 2-3 seconds before the accidents happen. This paper proposes a speed warning scheme for heavy-duty vehicle over the horizon in mountainous area, which can give the drivers enough time to respond to the danger. In the early warning aspect, this system combines the front road information, the vehicle characteristics and real-time information obtained from the vehicle, calculates and forecasts the danger that may happen over the horizon ahead of time, and prompts the driver to control the vehicle speed.
2017-03-28
Technical Paper
2017-01-0096
Valentin Soloiu, Bernard Ibru, Thomas Beyerl, Tyler Naes, Charvi Popat, Cassandra Sommer, Brittany Williams
Abstract An important aspect of an autonomous vehicle system, aside from the crucial features of path following and obstacle detection, is the ability to accurately and effectively recognize visual cues present on the roads, such as traffic lanes, signs and lights. This ability is important because very few vehicles are autonomously driven, and must integrate with conventionally operated vehicles. An enhanced infrastructure has yet to be available solely for autonomous vehicles to more easily navigate lanes and intersections non-visually. Recognizing these cues efficiently can be a complicated task as it not only involves constantly gathering visual information from the vehicle’s surroundings, but also requires accurate real time processing. Ambiguity of traffic control signals challenges even the most advanced computer decision making algorithms. The vehicle then must keep a predetermined position within its travel lane based on its interpretation of its surroundings.
2017-03-28
Technical Paper
2017-01-0107
Arvind Jayaraman, Ashley Micks, Ethan Gross
Abstract Recreating traffic scenarios for testing autonomous driving in the real world requires significant time, resources and expense, and can present a safety risk if hazardous scenarios are tested. Using a 3D virtual environment to enable testing of many of these traffic scenarios on the desktop or cluster significantly reduces the amount of required road tests. In order to facilitate the development of perception and control algorithms for level 4 autonomy, a shared memory interface between MATLAB, Simulink, and Unreal Engine 4 can send information (such as vehicle control signals) back to the virtual environment. The shared memory interface conveys arbitrary numerical data, RGB image data, and point cloud data for the simulation of LiDAR sensors.
2017-03-28
Technical Paper
2017-01-0110
Hao Sun, Weiwen Deng, Chen Su, Jian Wu
Abstract The ability to recognize traffic vehicles’ lane change maneuver lays the foundation for predicting their long-term trajectories in real-time, which is a key component for Advanced Driver Assistance Systems (ADAS) and autonomous automobiles. Learning-based approach is powerful and efficient, such approach has been used to solve maneuver recognition problems of the ego vehicles on conventional researches. However, since the parameters and driving states of the traffic vehicles are hardly observed by exteroceptive sensors, the performance of traditional methods cannot be guaranteed. In this paper, a novel approach using multi-class probability estimates and Bayesian inference model is proposed for traffic vehicle lane change maneuver recognition. The multi-class recognition problem is first decomposed into three binary problems under error correcting output codes (ECOC) framework.
2017-03-28
Technical Paper
2017-01-0113
Vaclav Jirovsky
Abstract Today's vehicles are being more often equipped with systems, which are autonomously influencing the vehicle behavior. More systems of the kind and even fully autonomous vehicles in regular traffic are expected by OEMs in Europe around year 2025. Driving is highly multitasking activity and human errors emerge in situations, when he is unable to process and understand the essential amount of information. Future autonomous systems very often rely on some type of inter-vehicular communication. This shall provide the vehicle with higher amount of information, than driver uses in his decision making process. Therefore, currently used 1-D quantity TTC (time-to-collision) will become inadequate. Regardless the vehicle is driven by human or robot, it’s always necessary to know, whether and which reaction is necessary to perform. Adaptable autonomous vehicle systems will need to analyze the driver’s situation awareness level.
2017-03-28
Technical Paper
2017-01-0116
Ankit Goila, Ambarish Desai, Feng Dang, Jian Dong, Rahul Shetty, Rakesh Babu Kailasa, Mahdi Heydari, Yang Wang, Yue Sun, Manikanta Jonnalagadda, Mohammed Alhasan, Hanlong Yang, Katherine R. Lastoskie
ADAS features development involves multidisciplinary technical fields, as well as extensive variety of different sensors and actuators, therefore the early design process requires much more resources and time to collaborate and implement. This paper will demonstrate an alternative way of developing prototype ADAS concept features by using remote control car with low cost hobby type of controllers, such as Arduino Due and Raspberry Pi. Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition. In this paper, we demonstrate that low cost frame work can be used for the high level concept algorithm architecture, development, and potential operation, as well as high level base testing of various features and functionalities. The developed RC vehicle can be used as a prototype of the early design phase as well as a functional safety testing bench.
2017-03-28
Technical Paper
2017-01-0045
Guirong Zhuo, Cheng Wu, Fengbo Zhang
Abstract Vehicle active collision avoidance includes collision avoidance by braking and by steering. However, both of these two methods have their limitations. Therefore, it is significant to establish the feasible region of active collision avoidance to choose the optimal way to avoid traffic accidents. This paper focuses on the steering control of an autonomous vehicle to track the planned trajectory and to perform an emergency collision avoidance maneuver. Meanwhile, the collision avoidance effect of steering control is compared with that of braking control. The path tracking controller is designed by hierarchical control structure. The upper controller includes model predictive control allocation and speed controller, and the lower is designed by weighted least-squares control allocation for torque allocation. Besides, seven order polynomial is used for path planning.
2017-03-28
Technical Paper
2017-01-0032
Wei Yang, Ling Zheng, Yinong Li, Yue Ren, Yusheng Li
Abstract This paper proposed a two-section trajectory planning algorithm. In this trajectory planning, sigmoid function is adopted to fit two tangent arcs to meet limited parking spaces by reducing the radius of turning. Then the transverse preview model is established and the path tracking errors including distance error and angle error are estimated. The weight coefficient is considered to distribute the impact factor of traverse distance error or traverse angle error in the total error. The fuzzy controller is designed to track the two-section trajectory in autonomous intelligent parking system. The fuzzy controller is developed due to its real-time and robustness in the parking process. Traverse errors and its first-order derivative are selected as input variables and the outer wheel steering angle is selected as the output variable in fuzzy controller. They are also divided into seven fuzzy sets. Finally, forty rules are decided to achieve effective trajectory tracking.
2017-03-28
Technical Paper
2017-01-0041
Shengguang Xiong, Gangfeng Tan, Xuexun Guo, Longjie Xiao
Abstract Automotive Front Lighting System(AFS) can receive the steering signal and the vehicular speed signal to adjust the position of headlamps automatically. AFS will provide drivers more information of front road to protect drivers safe when driving at night. AFS works when there is a steering signal input. However, drivers often need the front road's information before they turn the steering wheel when vehicles are going to go through a sharp corner, AFS will not work in such a situation. This paper studied how to optimize the working time of AFS based on GIS (Geographic Information System) and GPS(Geographic Information System) to solve the problem. This paper analyzed the process of the vehicle is about to go through a corner. Low beams and high beams were discussed respectively.
2017-03-28
Technical Paper
2017-01-1730
Gridsada Phanomchoeng, Sunhapos Chantranuwathana
Abstract Nowadays, the tendency of people using bicycles as the way of transportation has increased as well as the tendency of the bicycle accidents. According to the research of National Highway Traffic Safety Administration (NHTSA), National Survey on Bicyclist and Pedestrian Attitude and Behavior, the major root causes of bicycle accidents are from the road surface condition. Thus, this work has developed the system to detect the road surface condition. The system utilizes the laser and camera to measure the height of road. Then, with the information of the road height and bicycle speed, the road surface condition can be classified into 3 categories due to severe condition of the road. For the secure road, cyclists could safely ride on it. For the warning road, cyclists need to slow down the speed. Lastly, for the dangerous road, cyclists have to stop their bicycles.
2017-03-28
Technical Paper
2017-01-1399
Bin Wu, Xichan Zhu, Jianping Shen, Xuejun Cang, Lin li
Abstract A driver steering model for emergency lane change based on the China naturalistic driving data is proposed in this paper. The steering characteristic of three phases is analyzed. Using the steering primitive fitting by Gaussian function, the steering behaviors in collision avoidance and lateral movement phases can be described, and the stabilization steering principle of yaw rate null is found. Based on the steering characteristic, the near and far aim point used in steering phases is analyzed. Using the near and far aim point correction model, a driver steering model for emergency lane change is established. The research results show that the driver emergency steering model proposed in this paper performs well when explaining realistic steering behavior, and this model can be used in developing the ADAS system.
2017-03-28
Technical Paper
2017-01-1400
Keyu Qian, Gangfeng Tan, Renjie Zhou, Binyu Mei, Wanyang XIA
Abstract Downhill mountain roads are the accident prone sections because of their complexity and variety. Drivers rely more on driving experience and it is very easy to cause traffic accidents due to the negligence or the judgment failure. Traditional active safety systems, such as ABS, having subjecting to the driver's visual feedback, can’t fully guarantee the downhill driving safety in complex terrain environments. To enhance the safety of vehicles in the downhill, this study combines the characteristics of vehicle dynamics and the geographic information. Thus, through which the drivers could obtain the safety speed specified for his/her vehicle in the given downhill terrains and operate in advance to reduce traffic accidents due to driver's judgment failure and avoid the brake overheating and enhance the safety of vehicles in the downhill.
2017-03-28
Technical Paper
2017-01-1406
Changliu Liu, Jianyu Chen, Trong-Duy Nguyen, Masayoshi Tomizuka
Abstract Road safety is one of the major concerns for automated vehicles. In order for these vehicles to interact safely and efficiently with the other road participants, the behavior of the automated vehicles should be carefully designed. Liu and Tomizuka proposed the Robustly-safe Automated Driving system (ROAD) which prevents or minimizes occurrences of collisions of the automated vehicle with other road participants while maintaining efficiency. In this paper, a set of design principles are elaborated as an extension of the previous work, including robust perception and cognition algorithms for environment monitoring and high level decision making and low level control algorithms for safe maneuvering of the automated vehicle.
2017-03-28
Technical Paper
2017-01-1407
Helene G. Moorman, Andrea Niles, Caroline Crump, Audra Krake, Benjamin Lester, Laurene Milan, Christy Cloninger, David Cades, Douglas Young
Abstract Lane Departure Warning (LDW) systems, along with other types of Advanced Driver Assistance Systems (ADAS), are becoming more common in passenger vehicles, with the general aim of improving driver safety through automation of various aspects of the driving task. Drivers have generally reported satisfaction with ADAS with the exception of LDW systems, which are often rated poorly or even deactivated by drivers. One potential contributor to this negative response may be an increase in the cognitive load associated with lane-keeping when LDW is in use. The present study sought to examine the relationship between LDW, lane-keeping behavior, and concurrent cognitive load, as measured by performance on a secondary task. Participants drove a vehicle equipped with LDW in a demarcated lane on a closed-course test track with and without the LDW system in use over multiple sessions.
2017-03-28
Technical Paper
2017-01-1408
Satoshi Kozai, Yoshihiko Takahashi, Akihiro Kida, Takayuki Hiromitsu, Shinji Kitaura, Sadamasa Sawada, Gladys Acervo, Marius Ichim
Abstract A Rear Cross Traffic Auto Brake (RCTAB) system has been developed that uses radar sensors to detect vehicles approaching from the right or left at the rear of the driver’s vehicle, and then performs braking control if the system judges that a collision may occur. This system predicts the intersecting course of approaching vehicles and uses the calculated time-to-collision (TTC) to control the timing of automatic braking with the aim of helping prevent unnecessary operation while ensuring system performance.
2017-03-28
Journal Article
2017-01-0118
Yang Wang, Ankit Goila, Rahul Shetty, Mahdi Heydari, Ambarish Desai, Hanlong Yang
Regarding safety, obstacle avoidance has been considered as one of the most important features among ADAS systems for ground vehicles. However, the implementation of obstacle avoidance functions to commercial vehicles are still under progress. In this paper, we demonstrate a complete process of obstacle avoidance strategy for unmanned ground vehicle and implement the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was used to detect the obstacles on the fore-path. Based on the measured LIDAR data, an optimized path is automatically generated with accommodation of current car position, obstacle locations, car operation capability and global environmental restrictions. The path planning is updated in real time while new or changing obstacles being detected. This algorithm is validated by the simulation results with the RC car. The comparison will be discussed at the end of this paper.
2017-03-28
Journal Article
2017-01-0418
Gregory McCann, Prashant Khapane
Abstract An increase in data measurement and recording within vehicles has allowed Anti-lock Braking Systems (ABS) to monitor a vehicle’s dynamic behavior in far more detail. This increased monitoring helps to improve vehicle response in scenarios such as braking whilst cornering and braking on uneven surfaces. The Durability and Robustness (D&R) CAE department within Jaguar Land Rover discovered that the lack of a complex ABS system in virtual vehicle models was contributing to poor lateral and longitudinal loads correlation throughout the suspension and mounting systems. D&R CAE started a project to incorporate Continental’s ABS system, provided by ‘©Continental AG’ for physical JLR vehicles, into SIMPACK virtual vehicles by means of a co-simulation (2017 n.d.). The work involved collaboration between 3 departments in Jaguar Land Rover and ultimately led to implementation of the ABS into the JLR standard automotive virtual database.
2017-01-10
Technical Paper
2017-26-0007
Siva Murugesan, Vishakha S Bhagat, B V Shamsundara, Abhay Mannikar
Abstract In year 2015, 17 people were killed every hour by road accidents in India [1]. The occurrence of road accidents is observed to be higher during night, when visibility is at its lowest. The two factors which affect visibility are insufficient illumination and glare caused by the oncoming traffic. The Adaptive Front Lighting System [AFS] is an active safety feature which addresses these problems by employing specific lighting modes for Town, Country, Expressway conditions and automatic switching between Driving Beam and Passing Beam whenever required. Matrix of LEDs or a Projector with an actuator or a combination of both is employed in achieving different Lighting modes. The projector based AFS module is preferred for implementing the AFS control logic for passing beam owing to its economic cost.
2016-09-27
Journal Article
2016-01-8011
Kevin Grove, Jon Atwood, Myra Blanco, Andrew Krum, Richard Hanowski
Abstract This study evaluated the performance of heavy vehicle crash avoidance systems (CASs) by collecting naturalistic driving data from 150 truck tractors equipped with Meritor WABCO OnGuardTM or Bendix® Wingman® AdvancedTM products. These CASs provide drivers with audio-visual alerts of potential conflicts, and can apply automatic braking to mitigate or prevent a potential collision. Each truck tractor participated for up to one year between 2013 and 2015. Videos of the forward roadway and drivers’ faces were collected along with vehicle network data while drivers performed their normal duties on revenue-producing routes. The study evaluated the performance of CAS activations by classifying them into three categories based on whether a valid object was being tracked and whether drivers needed to react immediately.
2016-09-20
Journal Article
2016-01-1976
Kiran Thupakula, Adishesha Sivaramasastry, Srikanth Gampa
Abstract Aviation safety is one of the key focus areas of the aerospace industry as it involves safety of passengers, crew, assets etc. Due to advancements in technology, aviation safety has reached to safest levels compared to last few decades. In spite of declining trends in in-air accident rate, ground accidents are increasing due to ever increasing air traffic and human factors in the airport. Majority of the accidents occur during initial and final phases of the flight. Rapid increase in air traffic would pose challenge in ensuring safety and best utilization of Airports, Airspace and assets. In current scenario multiple systems like Runway Debris Monitoring System, Runway Incursion Detection System, Obstacle avoidance system and Traffic Collision Avoidance System are used for collision prediction and alerting in airport environment. However these approaches are standalone in nature and have limitations in coverage, performance and are dependent on onboard equipment.
2016-04-05
Journal Article
2015-01-9152
André Lundkvist, Arne Nykänen, Roger Johnsson
Abstract Many of the information systems in cars require visual attention, and a way to reduce both visual and cognitive workload could be to use sound. An experiment was designed in order to determine how driving and secondary task performance is affected by the use of information sound signals and their spatial positions. The experiment was performed in a driving simulator utilizing Lane Change Task as a driving scenario in combination with the Surrogate Reference Task as a secondary task. Two different signal sounds with different spatial positions informed the driver when a lane change should be made and when a new secondary task was presented. Driving performance was significantly improved when both signal sounds were presented in front of the driver. No significant effects on secondary task performance were found. It is recommended that signal sounds are placed in front of the driver, when possible, if the goal is to draw attention forward.
2016-04-05
Technical Paper
2016-01-0114
Chris Schwarz, Timothy Brown, John Lee, John Gaspar, Julie Kang
Abstract Distracted driving remains a serious risk to motorists in the US and worldwide. Over 3,000 people were killed in 2013 in the US because of distracted driving; and over 420,000 people were injured. A system that can accurately detect distracted driving would potentially be able to alert drivers, bringing their attention back to the primary driving task and potentially saving lives. This paper documents an effort to develop an algorithm that can detect visual distraction using vehicle-based sensor signals such as steering wheel inputs and lane position. Additionally, the vehicle-based algorithm is compared with a version that includes driving-based signals in the form of head tracking data. The algorithms were developed using machine learning techniques and combine a Random Forest model for instantaneous detection with a Hidden Markov model for time series predictions.
2016-04-05
Technical Paper
2016-01-0113
William Buller, Rini Sherony, Brian Wilson, Michelle Wienert
Abstract Based on RADAR and LiDAR measurements of deer with RADAR and LiDAR in the Spring and Fall of 2014 [1], we report the best fit statistical models. The statistical models are each based on time-constrained measurement windows, termed test-points. Details of the collection method were presented at the SAE World Congress in 2015. Evaluation of the fitness of various statistical models to the measured data show that the LiDAR intensity of reflections from deer are best estimated by the extreme value distribution, while the RCS is best estimated by the log-normal distribution. The value of the normalized intensity of the LiDAR ranges from 0.3 to 1.0, with an expected value near 0.7. The radar cross-section (RCS) varies from -40 to +10 dBsm, with an expected value near -14 dBsm.
2016-04-05
Technical Paper
2016-01-0124
Andrew Scott Alden, Brian Mayer, Patrick Mcgowen, Rini Sherony, Hiroyuki Takahashi
Abstract Animal-vehicle collision (AVC) is a significant safety issue on American roads. Each year approximately 1.5 million AVCs occur in the U.S., the majority of them involving deer. The increasing use of cameras and radar on vehicles provides opportunities for prevention or mitigation of AVCs, particularly those involving deer or other large animals. Developers of such AVC avoidance/mitigation systems require information on the behavior of encountered animals, setting characteristics, and driver response in order to design effective countermeasures. As part of a larger study, naturalistic driving data were collected in high AVC incidence areas using 48 participant-owned vehicles equipped with data acquisition systems (DAS). Continuous driving data including forward video, location information, and vehicle kinematics were recorded. The respective 11TB dataset contains 35k trips covering 360K driving miles.
2016-04-05
Technical Paper
2016-01-0123
Mostafa Anwar Taie, Mohamed ElHelw
Abstract The evaluation of Advanced Driver Assistance Systems (ADAS including driver assistance and active safety) has increasing interest from authorities, industry and academia. AsPeCSS active safety project concludes that good results in a laboratory test for active safety system design does not necessarily equate to an effective system in real traffic conditions. Moreover, many ADAS assessment projects and standards require physical testing on test tracks (dummy vehicles, pedestrian mannequins…), which are expensive and limit testing capabilities. This research presents a conceptual framework for on-board evaluation (OBE) of ADAS, which can be used as a cost effective evaluation in real-life traffic conditions. OBE shall monitor, record, analyze and report both internal behavior and external environment (external objects list and video stream) of ADAS under evaluation (ADASUE).
2016-04-05
Journal Article
2016-01-0149
Mehdi Jalalmaab, Mohammad Pirani, Baris Fidan, Soo Jeon
In this paper, a consensus framework for cooperative parameter estimation within the vehicular network is presented. It is assumed that each vehicle is equipped with a dedicated short range communication (DSRC) device and connected to other vehicles. The improvement achieved by the consensus for parameter estimation in presence of sensor’s noise is studied, and the effects of network nodes and edges on the consensus performance is discussed. Finally, the simulation results of the introduced cooperative estimation algorithm for estimation of the unknown parameter of road condition is presented. It is shown that due to the faster dynamic of network communication, single agents’ estimation converges to the least square approximation of the unknown parameter properly.
2016-04-05
Technical Paper
2016-01-0150
Felix Pistorius, Andreas Lauber, Johannes Pfau, Alexander Klimm, Juergen Becker
Abstract Various algorithms such as emergency brake or crash warning using V2X communication have been published recently. For such systems hard real-time constraints have to be satisfied. Therefore latency needs to be minimized to keep the message processing delay below a certain threshold. Existing V2X systems based on the IEEE 1609 and SAE J2735 standards implement most message processing in software. This means the latency of these systems strongly depends on the CPU load as well as the number of incoming messages per time. According to safety constraints all messages of nearby vehicles have to be processed, whereby no prediction of the message importance can be given without analyzing the message content. Regarding the aforementioned requirements we propose a novel architecture that optimizes latency to satisfy the hard real-time constraints for V2X messages.
2016-04-05
Technical Paper
2016-01-1667
Long Chen, Shuwei Zhang, Mingyuan Bian, Yugong Luo, Keqiang Li
Abstract As a typical parameter of the road-vehicle interface, the road friction potential acts an important factor that governs the vehicle motion states under certain maneuvering input, which makes the prior knowledge of maximum road friction capacity crucial to the vehicle stability control systems. Since the direct measure of the road friction potential is expensive for vehicle active safety system, the evaluation of this variable by cost effective method is becoming a hot issue all these years. A ‘wheel slip based’ maximum road friction coefficient estimation method based on a modified Dugoff tire model for distributed drive electric vehicles is proposed in this paper. It aims to evaluate the road friction potential with vehicle and wheel dynamics analyzing by using standard sensors equipped on production vehicle, and fully take the advantage of distributed EV that the wheel drive torque and rolling speed can be obtained accurately.
Viewing 1 to 30 of 542