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2017-04-11
Book
This is the electronic format of the Journal.
2017-03-28
Technical Paper
2017-01-1379
Yilu Murphey, Dev S. Kochhar, Yongquan Xie, Benjamin Pollatz, Rahul Kulkarni, Yifu Liu, Paul Watta
Drivers often engage in secondary in-vehicle activity that is not related to vehicle control because they believe they can do so safely. Often, it may be to relieve the monotony of driving. Interest is growing to understand and measure a driver’s workload, and design vehicle functionality to accommodate a driver’s perceived, rather than actual, workload. An accurate and real-time variant measure of driver workload that is personalized to an individual driver could be useful in the design of vehicle functionality that can be invoked and brought to the foreground when necessary, or placed in the background when not necessary. In autonomous vehicles where a driver is present as part of the HMI (human-machine interface), this structure could be helpful to better understand the transition from automated to manual driving mode, and vice versa. In this study, the measurement of perceived workload, and its inherent ‘personalized’ connotation was investigated.
2017-03-28
Technical Paper
2017-01-1405
Tzu-Sung Wu, Min-Shiu hsieh PhD, Po-Hsiang Liao, Ping-Min Hsu
Autonomous Emergency Braking Systems (AEBS) usually contain radar, (stereo) camera and/or LiDAR-based technology to identify potential collision partners ahead of the car, such that to warn the driver or automatically brake to avoid or mitigate a crash. The advantage of camera is less cost: however, is inevitable to face the defects of cameras in AEBS, that is, the image recognition cannot perform good accuracy in the poor or over-exposure light condition. Therefore, the compensation of other sensors is of importance. Motivated by the improvement of false detection, we propose a Pedestrian-and-Vehicle Recognition (PVR) algorithm based on radar to apply to AEBS. The PVR employs the radar cross section (RCS) and standard deviation of width of obstacle to determine whether a threshold value of RCS and standard deviation of width of the pedestrian and vehicle is crossed, and to identity that the objective is a pedestrian or vehicle, respectively.
2017-03-28
Technical Paper
2017-01-0032
Wei Yang, Ling zheng, Yinong Li, Yue Ren, Yusheng Li
Aiming at the automatic parking system to discontinuous problems, the Sigmoid function is adopted to fit the two section parking path. The transverse preview model is established and the path tracking error is estimated. Then the preview fuzzy control algorithm is adopted to track the ideal path. Finally, PreScan virtual simulation environment is established and the information of parking spaces is obtained by ultrasonic sensors. Research results show that the coefficient of determination can reach over 0.99 between the Sigmoid function and the two-section parking path. Based on the preview fuzzy control, the car can track the planning path successfully and park into parking spaces.
2017-03-28
Technical Paper
2017-01-0045
Guirong Zhuo, Cheng Wu, Fengbo Zhang
Vehicle active collision avoidance includes collision avoidance by braking and by steering, however both of these two methods have their limitations. When the vehicle’s speed is high or road adhesion coefficient is small, critical braking distance is long by braking to avoid collision, and collision avoidance by steering is restricted to the vehicle driving condition on the side lane. Therefore, it is significant to establish the feasible region of active collision avoidance to choose the optimal way to avoid traffic accidents. Model predictive control (MPC), as an optimized method, not only makes the control input of current time to achieve the best, but also can achieve the optimal control input in a future time.
2017-03-28
Technical Paper
2017-01-0110
Hao Sun, Weiwen Deng, Chen Su, Jian Wu
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
2017-01-0096
Valentin Soloiu, Bernard Ibru, Thomas Beyerl, Tyler Naes, Charvi Popat, Cassandra Sommer, Brittany Williams
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 on the road 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 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
2017-01-1399
Bin Wu, Xichan Zhu, Lin li, xuejun cang, jianping shen
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
2017-01-0118
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 has implemented the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was employed to detect the obstacles on the fore-path. Based on the measured radar data, an optimized path would be 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. The Arduino provides required control inputs to the RC Car to follow the pre-planned path and self-positioned by the observed obstacles data.
2017-03-28
Technical Paper
2017-01-0041
Shengguang Xiong, Gangfeng Tan, Xuexun Guo, Longjie Xiao
Automotive Front Lighting System (AFS) can receive the steering signal and the vehicle speed signal to automatically adjust the position of the headlamps light's body. AFS will provide drivers more information of the 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 round a sharp corner, AFS will not work in such a situation. In order to solve this problem, this paper studied how to foresight the front road and optimize the working time of AFS based on GIS (Geographic Information System) and GPS (Geographic Information System). This paper built the model of the vehicle steering characteristics with the relationship between the headlamp steering lighting and the angle of the steering wheel based on the follow-up steering law of headlamps of AFS.
2017-03-28
Technical Paper
2017-01-1408
Satoshi Kozai, Yoshihiko Takahashi, Akihiro Kida, Takayuki Hiromitsu, Shinji Kitaura, Sadamasa Sawada, Gladys Acervo, Marius Ichim
The goal of both automakers and vehicle users is to minimize the negative impacts of vehicles on society, such as traffic accidents, not only on the road but parking area, optimizing the enjoyment of using a car, comfort, and usability. To realize this, we have already provided automatic brake system (ICS) for static obstacles in parking area. We have also developed the Rear Cross Traffic Auto Brake (RCTAB) system, which detects a vehicle approaching from the sides when backing out of a parking area. We decided RCTAB system specifications based on two information “Approaching vehicle speed in parking area” and “Maximum backing speed”. RCTAB system structure consists of Radar which shared with “Blind Spot Monitor” and ECU which shared with “ICS Computer”. The radar detects the approaching vehicle. The ICS Computer judge Collision prediction and request “Braking Force” and “Driving Force” to Brake and Engine Computer.
2017-03-28
Technical Paper
2017-01-1401
Trong-Duy Nguyen, Joseph Lull, Satish Vaishnav
In this paper, a method of improving automated vehicle’s perception using a multi-pose camera system (MPCS) is presented. The proposed MPCS is composed of two identical colored and high frame-rate cameras: one installed in driver side and the other in passenger side. Perspective of MPCS varies depending on the width of vehicle type in which MPCS is installed. To increase perspective, we use maximum width of the host vehicle as camera to camera distance for the MPCS. In addition, angular positions of the two cameras in MPCS are controlled by two separate electric motor-based actuators. Steering wheel angle, which is available from vehicle Controller Area Network (CAN) messages, is used to supply information to the actuators to synchronize MPCS camera positions with the host vehicle steering wheel.
2017-03-28
Technical Paper
2017-01-0113
Vaclav Jirovsky
Today's vehicles are being more often equipped with systems, which are autonomously influencing the vehicle behavior. The close future is awaiting more systems of the kind and even significant penetration of fully autonomous vehicles in regular traffic is expected by OEMs in Europe around year 2025. The driving is highly multitasking activity and human errors emerge in situations, when he is not able 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 similar or higher amount of information, than driver uses in his decision making process. Therefore, currently used, and debatable, 1-D quantity TTC (time-to-collision) will definitely 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.
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.
2016-07-06
WIP Standard
J224
The purpose and scope of this SAE Recommended Practice is to provide a basis for classification of the extent of vehicle deformation caused by vehicle accidents on the highway. It is necessary to classify collision contact deformation (as opposed to induced deformation) so that the accident deformation may be segregated into rather narrow limits. Studies of collision deformation can then be performed on one or many data banks with assurance that the data under study are of essentially the same type. The seven-character code is also an expression useful to persons engaged in automobile safety, to describe appropriately a field-damaged vehicle with conciseness in their oral and written communications. Although this classification system was established primarily for use by professional teams investigating accidents in depth, other groups may also find it useful.
2016-05-20
Book
This is the electronic format of the Journal.
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
2016-01-0124
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
2016-01-0150
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
2016-01-0161
Valentin Soloiu, Imani Augusma, Deon Lucien, Mary Thomas, Roccio Alba-Flores
Abstract This study presents the design and development of a vehicle platform with intelligent sensors that has the capabilities to drive independently and cooperatively on roads. An integrated active safety system has been designed to optimize the human senses using ultrasonic infrared sensors and transmitter/receiver modules, to increase the human vision, feel and communication for increased road safety, lower congestion rates, and decrease CO2 emissions. Ultrasonic sensors mounted on the platform, emitted longitudinal 40 kHz waves and received echoes of these sound waves when an object was within its direction. The duration was converted to a distance measurement to detect obstacles as well as using distance measurement threshold values to implement adaptive cruise control. Infrared sensors equipped with an IR LED and a bipolar transistor detected a change in light intensity to identify road lanes.
2016-04-05
Technical Paper
2016-01-1454
Libo Dong, Stanley Chien, Jiang-Yu Zheng, Yaobin Chen, Rini Sherony, Hiroyuki Takahashi
Abstract Pedestrian Automatic Emergency Braking (PAEB) for helping avoiding/mitigating pedestrian crashes has been equipped on some passenger vehicles. Since approximately 70% pedestrian crashes occur in dark conditions, one of the important components in the PAEB evaluation is the development of standard testing at night. The test facility should include representative low-illuminance environment to enable the examination of the sensing and control functions of different PAEB systems. The goal of this research is to characterize and model light source distributions and variations in the low-illuminance environment and determine possible ways to reconstruct such an environment for PAEB evaluation. This paper describes a general method to collect light sources and illuminance information by processing large amount of potential collision locations at night from naturalistic driving video data.
2016-04-05
Technical Paper
2016-01-1453
I-Hsuan Lee, Bi-Cheng Luan
Abstract Autonomous emergency braking (AEB) systems is one of the functions of the Advanced Driver Assists System to avoid or mitigate vehicle frontal collisions. Most of the previous studies focus on two-car scenario where the host vehicle monitors the distances to the vehicles in front, and automatically applies emergency brake when a collision is imminent. The purpose of this paper is to develop an Advanced-AEB control system that mitigates collisions in a multi-car scenario by measuring the distances to the vehicles in front as well as those to the vehicles behind using the concept of impedance control. A simple gain-scheduling PI controller was designed for the host vehicle to track the reference inputs generated by the impedance control. The preliminary simulation results demonstrate that the proposed AEB is effective in mitigating the collisions in a 3-car following scenario.
2016-04-05
Technical Paper
2016-01-1446
Rini Sherony, Qiang Yi, Stanley Chien, Jason Brink, Mohammad Almutairi, Keyu Ruan, Wensen Niu, Lingxi Li, Yaobin Chen, Hiroyuki Takahashi
Abstract According to the U.S. National Highway Traffic Safety Administration, 743 pedal cyclists were killed and 48,000 were injured in motor vehicle crashes in 2013. As a novel active safety equipment to mitigate bicyclist crashes, bicyclist Pre-Collision Systems (PCSs) are being developed by many vehicle manufacturers. Therefore, developing equipment for evaluating bicyclist PCS is essential. This paper describes the development of a bicycle carrier for carrying the surrogate bicyclist in bicyclist PCS testing. An analysis on the United States national crash databases and videos from TASI 110 car naturalistic driving database was conducted to determine a set of most common crash scenarios, the motion speed and profile of bicycles. The bicycle carrier was designed to carry or pull the surrogate bicyclist for bicycle PCS evaluation. The carrier is a platform with a 4 wheel differential driving system.
2016-04-05
Technical Paper
2016-01-1447
Qiang Yi, Stanley Chien, Jason Brink, Wensen Niu, Lingxi Li, Yaobin Chen, Chi-Chen Chen, Rini Sherony, Hiroyuki Takahashi
Abstract As part of active safety systems for reducing bicyclist fatalities and injuries, Bicyclist Pre-Collision System (BPCS), also known as Bicyclist Autonomous Emergency Braking System, is being studied currently by several vehicles manufactures. This paper describes the development of a surrogate bicyclist which includes a surrogate bicycle and a surrogate bicycle rider to support the development and evaluation of BPCS. The surrogate bicycle is designed to represent the visual and radar characteristics of real bicyclists in the United States. The size of bicycle surrogate mimics the 26 inch adult bicycle, which is the most popular adult bicycle sold in the US. The radar cross section (RCS) of the surrogate bicycle is designed based on RCS measurement of the real adult sized bicycles.
2016-04-05
Technical Paper
2016-01-0147
Toshiya Hirose, Tomohiro Makino, Masanobu Taniguchi, Hidenobu Kubota
Abstract Vehicle to vehicle communication system (V2V) can send and receive the vehicle information by wireless communication, and can use as a safety driving assist for driver. Currently, it is investigated to clarify an appropriate activation timing for collision information, caution and warning in Japan. This study focused on the activation timing of collision information (Provide objective information for safe driving to the driver) on V2V, and investigated an effective activation timing of collision information, and the relationship between the activation timing and the accuracy of the vehicle position. This experiment used Driving Simulator. The experimental scenario is four situations of (1) “Assistance for braking”, (2) “Assistance for accelerating”, (3) “Assistance for right turn” and (4) “Assistance for left turn” in blind intersection. The activation timing of collision information based on TTI (Time To Intersection) and TTC (Time To Collision).
2016-04-05
Technical Paper
2016-01-1455
John Gaspar, Timothy Brown, Chris Schwarz, Susan Chrysler, Pujitha Gunaratne
Abstract In 2010, 32,855 fatalities and over 2.2 million injuries occurred in automobile crashes, not to mention the immense economic impact on our society. Two of the four most frequent types of crashes are rear-end and lane departure crashes. In 2011, rear-end crashes accounted for approximately 28% of all crashes while lane departure crashes accounted for approximately 9%. This paper documents a study on the NADS-1 driving simulator to support the development of driver behavior modeling. Good models of driver behavior will support the development of algorithms that can detect normal and abnormal behavior, as well as warning systems that can issue useful alerts to the driver. Several scenario events were designed to fill gaps in previous crash research. For example, previous studies at NADS focused on crash events in which the driver was severely distracted immediately before the event. The events in this study included a sample of undistracted drivers.
2016-04-05
Technical Paper
2016-01-1457
John M. Scanlon, Kerry Page, Rini Sherony, Hampton C. Gabler
Abstract There are over 4,500 fatal intersection crashes each year in the United States. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging active safety systems designed to detect an imminent intersection crash and either provide a warning or perform an automated evasive maneuver. The performance of an I-ADAS will depend on the ability of the onboard sensors to detect an imminent collision early enough for an I-ADAS to respond in a timely manner. One promising method for determining the earliest detection opportunity is through the reconstruction of real-world intersection crashes. After determining the earliest detection opportunity, the required sensor range, orientation, and field of view can then be determined through the simulation of these crashes as if the vehicles had been equipped with an I-ADAS.
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