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Viewing 1 to 30 of 89
2017-07-10
Technical Paper
2017-28-1938
Shyam Sunder Manivannan, Gopkumar Kuttikrishnan, Rajesh Siva, Janarthanan C, G A Ramadass
Abstract The hybrid robot will be a battery operated four wheel drive vehicle with a rigid chassis for all terrain operation. The vehicle will be suited for various payloads based on applications with geological, atmospheric sensors and buried object identification at a depth of 8 to 100 m., etc. The vehicle will be remotely controlled through a RF signal, allows it to maneuver up to 5 km. The novelty of the design, is its capability for all terrain and ease of trafficability based on skid steering, self-alignment of sensors and vehicle traction in spite of possible inverted conditions and the vehicle can travel from land, snow, water and vice versa. The vehicle could be deployed for surveying coastline of water bodies, borderlines and also be extensively used in polar region for studying glacier aging and as advance vehicle for the convoys and polar mapping.
2017-03-28
Technical Paper
2017-01-0068
Pablo Sauras-Perez, Andrea Gil, Jasprit Singh Gill, Pierluigi Pisu, Joachim Taiber
Abstract In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.
2017-03-28
Technical Paper
2017-01-0067
Wei Han, Xinyu Zhang, Jialun Yin, Yutong Li, Deyi Li
Abstract Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.
2017-03-28
Technical Paper
2017-01-0070
Longxiang Guo, Sagar Manglani, Xuehao Li, Yunyi Jia
Abstract Autonomous driving technologies can provide better safety, comfort and efficiency for future transportation systems. Most research in this area has mainly been focused on developing sensing and control approaches to achieve various autonomous driving functions. Very little of this research, however, has studied how to efficiently handle sensing exceptions. A simple exception measured by any of the sensors may lead to failures in autonomous driving functions. The autonomous vehicles are then supposed to be sent back to manufacturers for repair, which takes both time and money. This paper introduces an efficient approach to make human drivers able to online teach autonomous vehicles to drive under sensing exceptions. A human-vehicle teaching-and-learning framework for autonomous driving is proposed and the human teaching and vehicle learning processes for handling sensing exceptions in autonomous vehicles are designed in detail.
2017-03-28
Technical Paper
2017-01-0069
Venkatesh Raman, Mayur Narsude, Damodharan Padmanaban
Abstract This manuscript compares window-based data imputation approaches for data coming from connected vehicles during actual driving scenarios and obtained using on-board data acquisition devices. Three distinct window-based approaches were used for cleansing and imputing the missing values in different CAN-bus (Controller Area Network) signals. Lengths of windows used for data imputation for the three approaches were: 1) entire time-course for each vehicle ID, 2) day, and 3) trip (defined as duration between vehicle's ignition statuses ON to OFF). An algorithm for identification of ignition ON and OFF events is also presented, since this signal was not explicitly captured during the data acquisition phase. As a case study, these imputation techniques were applied to the data from a driver behavior classification experiment.
2017-03-28
Technical Paper
2017-01-0059
Barbaros Serter, Christian Beul, Manuela Lang, Wiebke Schmidt
Abstract Today, highly automated driving is paving the road for full autonomy. Highly automated vehicles can monitor the environment and make decisions more accurately and faster than humans to create safer driving conditions while ultimately achieving full automation to relieve the driver completely from participating in driving. As much as this transition from advanced driving assistance systems to fully automated driving will create frontiers for re-designing the in-vehicle experience for customers, it will continue to pose significant challenges for the industry as it did in the past and does so today. As we transfer more responsibility, functionality and control from human to machine, technologies become more complex, less transparent and making constant safe-guarding a challenge. With automation, potential misuse and insufficient system safety design are important factors that can cause fatal accidents, such as in TESLA autopilot incident.
2017-03-28
Technical Paper
2017-01-0114
Jorge De-J. Lozoya Santos, J. C. Tudon-Martinez
Abstract The project consists on the mechanical and electronic instrumentation of an existing vehicle (built at Universidad de Monterrey for the SAE Supermileage Competition) to be able to control its steering, braking and throttle systems “by wire”. Insight to the stages of turning the vehicle into an autonomous one is presented. This includes identification of the current mechanical properties, choosing adequate components and the use of a simulation to allow early work on the software involving cameras and motors to provide autonomy to the vehicle. Using software in the loop methodology mathematical models of the dynamics of the vehicle are run in Simulink and update the position and orientation of the 3D model of the vehicle in V-REP, a robot simulator.
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
Technical Paper
2017-01-0117
Raja Sekhar Dheekonda, Sampad Panda, Md Nazmuzzaman khan, Mohammad Hasan, Sohel Anwar
Accuracy in detecting a moving object is critical to autonomous driving or advanced driver assistance systems (ADAS). By including the object classification from multiple sensor detections, the model of the object or environment can be identified more accurately. The critical parameters involved in improving the accuracy are the size and the speed of the moving object. All sensor data are to be used in defining a composite object representation so that it could be used for the class information in the core object’s description. This composite data can then be used by a deep learning network for complete perception fusion in order to solve the detection and tracking of moving objects problem. Camera image data from subsequent frames along the time axis in conjunction with the speed and size of the object will further contribute in developing better recognition algorithms.
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
2017-01-0104
Maryam Moosaei, Yi Zhang, Ashley Micks, Simon Smith, Madeline J. Goh, Vidya Nariyambut Murali
Abstract 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.
2017-03-28
Technical Paper
2017-01-0103
Thomas Beyerl, Bernard Ibru, Charvi Popat, Deborah Ojo, Alexander Bakus, Jessica Elder, Valentin Soloiu
Abstract Autonomous vehicles must possess the capability to navigate complex intersections, which do not conform to typical models. Such intersections may have multiple roadways of different classes, highly acute angles, or unique multi-modal combinations. These may include railway grade crossings, bicycle lanes, or unique signal arrangements. Conventional navigation systems, which gather data from the surrounding area then plan a path through the collected data require faultless and complex analysis of extremely unstructured environments. The vehicle must then avoid obstacles as well as successfully navigate the intersection with extremely low tolerance for error. Computer decision making challenges can arise from this method of navigation, especially when interacting with non-autonomous vehicles.
2017-03-28
Journal Article
2017-01-0111
Santhosh Tamilarasan, Levent Guvenc
Abstract 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.
2017-03-28
Technical Paper
2017-01-0108
Zaydounr Y. Rawashdeh, Trong-Duy Nguyen, Anoop Pottammal, Rajesh Malhan
Abstract In this work, Dedicated Short Range Communication (DSRC) capabilities combined with classical autonomous vehicles’ on-board sensors (Camera) are used to trigger a Comfortable Emergency Brake (CEB) for urban traffic light intersection scenario. The system is designed to achieve CEB in two phases, the Automated Comfortable Brake (ACB) and the full stop Automated Emergency Brake (AEB). The ACB is triggered first based on the content of the Signal Phase and Timing (SPaT) / Map data (MAP) messages received from the Road Side Unit (RSU) at larger distances. And, once the traffic light becomes in the detection field of view of the camera, the output of the Camera-based Traffic Light Detection (TLD) and recognition software is fused with the SPaT/MAP content to decide on triggering the full stop AEB. In the automated vehicle, the current traffic light color and duration received in the SPaT message is parsed; and compared with the TLD output for color matching.
2017-03-28
Technical Paper
2017-01-0081
Majid Majidi, Majid Arab, Vahid Tavoosi
Abstract In this research, an optimal real-time trajectory planning method is proposed for autonomous ground vehicles in case of overtaking a moving obstacle. When an autonomous vehicle detects a moving vehicle ahead of it in a proper speed and distance and the braking is not efficient due to the lost of its kinematic energy, the autonomous vehicle decides to overtake the obstacle by performing a double lane-change maneuver. A two-phase nonlinear optimal problem is developed for generating the path for the overtaking maneuver. The cost function of the first phase is defined in such a way that the vehicle approaches the moving obstacle as close as possible. Besides, the cost function of the second phase is defined as the minimization of the sum of the vehicle lateral deviation from the reference path and the rate of steering angle during the overtaking maneuver while the lateral acceleration of the vehicle does not exceed a safe limit.
2017-03-28
Technical Paper
2017-01-0071
Vahid Taimouri, Michel Cordonnier, Kyoung Min Lee, Bryan Goodman
Abstract While operating a vehicle in either autonomous or occupant piloted mode, an array of sensors can be used to guide the vehicle including stereo cameras. The state-of-the-art distance map estimation algorithms, e.g. stereo matching, usually detect corresponding features in stereo images, and estimate disparities to compute the distance map in a scene. However, depending on the image size, content and quality, the feature extraction process can become inaccurate, unstable and slow. In contrast, we employ deep convolutional neural networks, and propose two architectures to estimate distance maps from stereo images. The first architecture is a simple and generic network that identifies which features to extract, and how to combine them in a multi-resolution framework.
2017-03-28
Technical Paper
2017-01-0072
Yang Zheng, Navid Shokouhi, Amardeep Sathyanarayana, John Hansen
Abstract With the embedded sensors – typically Inertial Measurement Units (IMU) and GPS, the smartphone could be leveraged as a low-cost sensing platform for estimating vehicle dynamics. However, the orientation and relative movement of the smartphone inside the vehicle yields the main challenge for platform deployment. This study proposes a solution of converting the smartphone-referenced IMU readings into vehicle-referenced accelerations, which allows free-positioned smartphone for the in-vehicle dynamics sensing. The approach is consisted of (i) geometry coordinate transformation techniques, (ii) neural networks regression of IMU from GPS, and (iii) adaptive filtering processes. Experiment is conducted in three driving environments which cover high occurrence of vehicle dynamic movements in lateral, longitudinal, and vertical directions. The processing effectiveness at five typical positions (three fixed and two flexible) are examined.
2017-03-28
Technical Paper
2017-01-0075
Shinya Kitayama, Toshiyuki Kondou, Hirokazu Ohyabu, Masaaki Hirose, Haneda Narihiro, Ryuta Maeda
Abstract In the future, autonomous vehicles will be realized. It is assumed that traffic accidents will be caused by the overconfidence to the autonomous driving system and the lack of communication between the vehicle and the pedestrian. We propose that one of the solutions is a display system to give the information the state of vehicle to pedestrians. In this paper, we studied how the information influences the motion of pedestrians. The vehicle gives the information, which is displayed on road by using of color light (red, yellow and blue), of the collision risk determined by the TTC (Time to Collision). The pedestrian is ordered to cross the road in several cases of the TTC. In the presence of the TTC information, the number of the pedestrians, who did not cross the road in the case of short TTC (red light is displayed), increased from 52% to 67%. It is cleared that the pedestrians determined whether they crossed the road or not by the information effectively.
2017-03-28
Technical Paper
2017-01-0078
Alexander Katriniok, Peter Kleibaum, Christian Ress, Lutz Eckstein
Abstract Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.
2017-03-28
Technical Paper
2017-01-0401
Ye Yuan, Junzhi Zhang, Yutong Li, Chen Lv
Abstract As the essential of future driver assistance system, brake-by-wire system is capable of performing autonomous intervention to enhance vehicle safety significantly. Regenerative braking is the most effective technology of improving energy consumption of electrified vehicle. A novel brake-by-wire system scheme with integrated functions of active braking and regenerative braking, is proposed in this paper. Four pressure-difference-limit valves are added to conventional four-channel brake structure to fulfill more precise pressure modulation. Four independent isolating valves are adopted to cut off connections between brake pedal and wheel cylinders. Two stroke simulators are equipped to imitate conventional brake pedal feel. The operation principles of newly developed system are analyzed minutely according to different working modes. High fidelity models of subsystems are built in commercial software MATLAB and AMESim respectively.
2017-03-28
Technical Paper
2017-01-1672
Siddartha Khastgir, Gunwant Dhadyalla, Stewart Birrell, Sean Redmond, Ross Addinall, Paul Jennings
Abstract The advent of Advanced Driver Assistance Systems (ADAS) and automated driving has offered a new challenge for functional verification and validation. The explosion of the test sample space for possible combinations of inputs needs to be handled in an intelligent manner to meet cost and time targets for the development of such systems. This paper addresses this research gap by using constrained randomization techniques for the creation of the required test scenarios and test cases. Furthermore, this paper proposes an automated constrained randomized test scenario generation framework for testing of ADAS and automated systems in a driving simulator setup. The constrained randomization approach is deployed at two levels: 1) test scenario randomization 2) test case randomization.
2017-03-28
Technical Paper
2017-01-1683
Adit Joshi
Software for autonomous vehicles is highly complex and requires vast amount of vehicle testing to achieve a certain level of confidence in safety, quality and reliability. According to the RAND Corporation, a 100 vehicle fleet running 24 hours a day 365 days a year at a speed of 40 km/hr, would require 17 billion driven kilometers of testing and take 518 years to fully validate the software with 95% confidence such that its failure rate would be 20% better than the current human driver fatality rate [1]. In order to reduce cost and time to accelerate autonomous software development, Hardware-in-the-Loop (HIL) simulation is used to supplement vehicle testing. For autonomous vehicles, path following controls are an integral part for achieving lateral control. Combining the aforementioned concepts, this paper focuses on a real-time implementation of a path-following lateral controller, developed by Freund and Mayr [2].
2017-03-28
Technical Paper
2017-01-1591
Haotian Cao, Xiaolin Song, Zhi Huang
Abstract Generally speaking, lateral steering control method which ensures a good performance in tracking quality and handle quality simultaneously for autonomous vehicle is a changeling task. In order to keep the vehicle to stay safe when facing with severe situations such as an emergency lane change, a switched MPC lateral steering controller, which is on the basis of the stability feature of the vehicle, is presented in this paper. First, a MPC steering controller based on the 3DOF nonlinear vehicle model is derived, a comparative study of different vehicle models for MPC prediction are made. It proves that the presented MPC controller based on 3DOF nonlinear vehicle model possesses an advantage of balancing the conflicts between the tracking quality and handling quality of the vehicle.
2017-03-28
Journal Article
2017-01-1589
Giampiero Mastinu, Fabio Della Rossa, Massimiliano Gobbi, Giorgio Previati
Abstract The paper deals with the bifurcation analysis of a simple mathematical model describing an automobile running on an even surface. Bifurcation analysis is adopted as the proper procedure for an in-depth understanding of the stability of steady-state motion of cars (either cornering or running straight ahead). The aim of the paper is providing the fundamental information for inspiring further studies on vehicle dynamics with or without a human driver. The considered mechanical model of the car has two degrees of freedom, nonlinear tire characteristics are included. A simple driver model is introduced. Experimental validations of the model are produced. As a first step, bifurcation analysis is performed without driver (fixed control). Ten different combinations of front and rear tire characteristics (featuring understeer or oversteer automobiles) are considered. Steering angle and speed are varied. Many different dynamical behaviors of the model are found.
2017-03-28
Technical Paper
2017-01-1585
Renxie Zhang, Lu Xiong, Zhuoping Yu, Wei Liu
Abstract A dynamic controller is designed for unmanned skid-steering vehicle. The vehicle speed is controlled through driving torque of engine to achieve the desired vehicle speed and the steering is controlled through hydraulic braking on each side of the vehicle to achieve the desired yaw rate. Contrary to the common approaches by considering non-holonomic constraints, tire slip and saturation of actuators torque influencing the driving and braking are considered, based on the analysis of vehicle dynamic model and nonlinear tire model. Hence, with conditional integrators, the dynamic controller overcoming integral saturation is designed to ensure the accurate tracking for desired signals under influence of tire forces and constraint of actuators. In addition, the exponential kind filter is utilized to enhance the ability of smoothing noise of wheel speed. To perform small radius cornering maneuvers, a dynamic control strategy for steering when vehicle speed is zero is also designed.
2017-03-28
Journal Article
2017-01-1597
Christoforos Chatzikomis, Aldo Sorniotti, Patrick Gruber, Matthew Bastin, Raja Mazuir Shah, Yuri Orlov
Abstract Electric vehicles with multiple motors permit continuous direct yaw moment control, also called torque-vectoring. This allows to significantly enhance the cornering response, e.g., by extending the linear region of the vehicle understeer characteristic, and by increasing the maximum achievable lateral acceleration. These benefits are well documented for human-driven cars, yet limited information is available for autonomous/driverless vehicles. In particular, over the last few years, steering controllers for automated driving at the cornering limit have considerably advanced, but it is unclear how these controllers should be integrated alongside a torque-vectoring system. This contribution discusses the integration of torque-vectoring control and automated driving, including the design and implementation of the torque-vectoring controller of an autonomous electric vehicle for a novel racing competition.
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
2017-01-1401
Trong-Duy Nguyen, Joseph Lull, Satish Vaishnav
Abstract In this paper, a method of improving the 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 the driver side and the other in the passenger side. Perspective of MPCS varies depending on the width of vehicle type in which MPCS is installed. To increase perspective, we use the 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 the 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
2017-01-1441
Heungseok Chae, Kyong Chan Min, Kyongsu Yi
Abstract This paper describes design and evaluation of a driving mode decision and lane change control algorithm of automated vehicle in merge situations on highway intersection. For the development of a highly automated driving control algorithm in merge situation, driving mode change from lane keeping to lane change is necessary to merge appropriately. In a merge situation, the driving objective is slightly different to general driving situation. Unlike general situation, the lane change should be completed in a limited travel distance in a merge situation. Merge mode decision is determined based on surrounding vehicles states and remained distance of merge lane. In merge mode decision algorithm, merge availability and desired merge position are decided to change lane safely and quickly. Merge availability and desired merge position are based on the safety distance that considers relative velocity and relative position of subject and surrounding vehicles.
2017-03-28
Journal Article
2017-01-1216
Edward C. Fontana, Rick Barnett, Robert Catalano, James Harvey, Jiacheng He, George Ottinger, John Steel
Abstract Electric cars can help cities solve air quality problems, but drivers who live in apartments have no convenient way to charge daily, absent the well-controlled private garages where most electric vehicles (EVs) are currently charged each night. Environmentally robust, hands-free, inductive chargers would be ideal, but energy efficiency suffers. We asked whether the precise parking alignment provided by self-driving cars could be used to provide convenient inductive charging with improved charging efficiencies. To answer this question, we split an inductor-inductor-capacitor (LLC) battery charger at the middle of the isolation transformer. The power factor correction, tank elements, and transformer primary windings are stationary, while the transformer secondary, rectifiers, and battery control logic are on the vehicle. The transformer is assembled each time the EV parks.
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