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2017-03-28
Technical Paper
2017-01-0433
Yang Xing, Chen Lv, Wang Huaji, Hong Wang, Dongpu Cao
Abstract Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.
2017-03-28
Technical Paper
2017-01-0432
Bing Zhu, Zhipeng Liu, Jian Zhao, Weiwen Deng
Abstract Adaptive cruise control system with lane change assistance (LCACC) is a novel advanced driver assistance system (ADAS), which enables dual-target tracking, safe lane change, and longitudinal ride comfort. To design the personalized LCACC system, one of the most important prerequisites is to identify the driver’s individualities. This paper presents a real-time driver behavior characteristics identification strategy for LCACC system. Firstly, a driver behavior data acquisition system was established based on the driver-in-the-loop simulator, and the behavior data of different types of drivers were collected under the typical test condition. Then, the driver behavior characteristics factor Ks we proposed, which combined the longitudinal and lateral control behaviors, was used to identify the driver behavior characteristics. And an individual safe inter-vehicle distances field (ISIDF) was established according to the identification results.
2017-03-28
Technical Paper
2017-01-1382
Michelle L. Reyes, Cheryl A. Roe, Ashley B. McDonald, Julia E. Friberg, Daniel V. McGehee
Abstract Advanced driver assistance systems (ADAS) show tremendous promise for increasing safety on our roadways. However, while these technologies are rapidly infiltrating the American passenger vehicle market, many consumers have little to no experience or knowledge of them prior to getting behind the wheel. The Technology Demonstration Study was conducted to evaluate how the ways in which drivers learn about ADAS affect their perceptions of the technologies. This paper investigates drivers’ knowledge of the purpose, function, and limitations of the advanced driver assistance technology of adaptive cruise control (ACC), along with ratings of perceived usefulness, apprehension, and effort required to learn to use ACC.
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
2017-01-1409
Markus Schratter, Susie Cantu, Thomas Schaller, Peter Wimmer, Daniel Watzenig
Abstract Highly Automated Driving (HAD) opens up new middle-term perspectives in mobility and is currently one of the main goals in the development of future vehicles. The focus is the implementation of automated driving functions for structured environments, such as on the motorway. To achieve this goal, vehicles are equipped with additional technology. This technology should not only be used for a limited number of use cases. It should also be used to improve Active Safety Systems during normal non-automated driving. In the first approach we investigate the usage of machine learning for an autonomous emergency braking system (AEB) for the active pedestrian protection safety. The idea is to use knowledge of accidents directly for the function design. Future vehicles could be able to record detailed information about an accident. If enough data from critical situations recorded by vehicles is available, it is conceivable to use it to learn the function design.
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
2017-01-1402
SeHwan Kim, Junmin Wang, Dennis Guenther, Gary Heydinger, Joshua Every, M. Kamel Salaani, Frank Barickman
Abstract The rapid development of driver assistance systems, such as lane-departure warning (LDW) and lane-keeping support (LKS), along with widely publicized reports of automated vehicle testing, have created the expectation for an increasing amount of vehicle automation in the near future. As these systems are being phased in, the coexistence of automated vehicles and human-driven vehicles on roadways will be inevitable and necessary. In order to develop automated vehicles that integrate well with those that are operated in traditional ways, an appropriate understanding of human driver behavior in normal traffic situations would be beneficial. Unlike many research studies that have focused on collision-avoidance maneuvering, this paper analyzes the behavior of human drivers in response to cut-in vehicles moving at similar speeds. Both automated and human-driven vehicles are likely to encounter this scenario in daily highway driving.
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
Technical Paper
2017-01-0429
Michael Holland, Jonathan Gibb, Kacper Bierzanowski, Stuart Rowell, Bo Gao, Chen Lv, Dongpu Cao
Abstract This paper outlines the procedure used to assess the performance of a Lane Keeping Assistance System (LKAS) in a virtual test environment using the newly developed Euro NCAP Lane Support Systems (LSS) Test Protocol, version 1.0, November 2015 [1]. A tool has also been developed to automate the testing and analysis of this test. The Euro NCAP LSS Test defines ten test paths for left lane departures and ten for right lane departures that must be followed by the vehicle before the LKAS activates. Each path must be followed to within a specific tolerance. The vehicle control inputs required to follow the test path are calculated. These tests are then run concurrently in the virtual environment by combining two different software packages. Important vehicle variables are recorded and processed, and a pass/fail status is assigned to each test based on these values automatically.
2017-03-28
Technical Paper
2017-01-1638
Felix Gow, Lifeng Guan, Jooil Park
Abstract Tire Pressure Monitoring System (TPMS) sensor measures air pressure and temperature in the tire and transmits tire information as wireless messages to TPMS central unit which consists of Radio Frequency (RF) receiver. TPMS central unit needs to determine the exact sensor locations (e.g. Front Left, Front Right, Rear Left or Rear Right) in order to correctly identify the location of the tire with pressure out of the desired range. The identified tire with abnormal pressure is highlighted on dash board in the car. Thus, determination of the location of a particular tire made automatically by the TPMS system itself or tire localization is required. TPMS tire localization is implemented currently in several methods. A new method is proposed in this paper. The proposed method uses at least two RF transceivers as repeaters. Each transceiver receives wireless messages (eg.
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
2017-01-0036
Michael Hafner, John Bales
Abstract We introduce a controller designed to stop a vehicle smoothly and accurately at a specified distance target, while being robust to unmeasured disturbances. This controller has a wide range of applications in instances where low speed longitudinal control of a vehicle is desired. Controller design was validated in a simulation using an ideal vehicle model based on first principles. Real world testing and tuning was performed on a full-size pickup truck to demonstrate controller performance.
2017-03-28
Technical Paper
2017-01-1555
Mirosław Jan Gidlewski, Krystof JANKOWSKI, Andrzej MUSZYŃSKI, Dariusz ŻARDECKI
Abstract Lane change automation appears to be a fundamental problem of vehicle automated control, especially when the vehicle is driven at high speed. Selected relevant parts of the recent research project are reported in this paper, including literature review, the developed models and control systems, as well as crucial simulation results. In the project, two original models describing the dynamics of the controlled motion of the vehicle were used, verified during the road tests and in the laboratory environment. The first model - fully developed (multi-body, 3D, nonlinear) - was used in simulations as a virtual plant to be controlled. The second model - a simplified reference model of the lateral dynamics of the vehicle (single-body, 2D, linearized) - formed the basis for theoretical analysis, including the synthesis of the algorithm for automatic control. That algorithm was based on the optimal control theory.
2017-03-28
Technical Paper
2017-01-1653
Jon Barton Shields, Jörg Huser, David Gell
Abstract This paper discusses the merits, benefits and usage of autonomous key management (with implicit authentication) (AKM) solutions for securing ECU-to-ECU communication within the connected vehicle and IoT applications; particularly for transmissions between externally exposed, edge ECU sensors connected to ECUs within the connected vehicle infrastructure. Specific benefits addressed include reductions of communication latency, implementation complexity, processing power and energy consumption. Implementation issues discussed include provisioning, key rotation, synchronization, re-synchronization, digital signatures and enabling high entropy.
2017-03-28
Technical Paper
2017-01-0024
Yuto Imanishi, Naoyuki Tashiro, Yoichi Iihoshi, Takashi Okada
Abstract In recent years, improvement of in-use fuel economy is required with tightening of exhaust emission regulation. We assume that one of the most effective solutions is ACC (Adaptive Cruise Control), which can control a powertrain accurately more than a driver. We have been developing a fuel saving ADAS (Advanced Driver Assistance System) application named “Sailing-ACC”. Sailing-ACC system uses sailing stop technology which stops engine fuel injection, and disengages a clutch coupling a transmission when a vehicle does not need acceleration torque. This system has a potential to greatly improve fuel efficiency. In this paper, we present a predictive powertrain state switching algorithm using external information (route information, preceding vehicle information). This algorithm calculates appropriate switching timing between a sailing stop mode and an acceleration mode to generate a “pulse-and-glide” pattern.
2017-03-28
Technical Paper
2017-01-0025
Takayuki Kitamura, Naotsugu Shimizu, Yasuyuki Miyake
Abstract In the last decade, radar-based Advanced Driver Assistance Systems (ADAS) have improved safety of transportation. Today, the standardization of ADAS established by New Car Assessment Program (NCAP) is expected to expand its market globally. One of the key technologies of ADAS is the rear-side monitoring system such as Blind Spot Warning (BSW) and Closing Vehicle Warning (CVW). It is required to expand its detection range so that it can monitor not only nearside targets for BSW, but farther targets for CVW. These applications can be achieved using two radar sensors installed at rear-side corner of the vehicle. However, the expanded detection range causes undesirable target detections and decreases target recognition performance. In this paper, a novel solution to improve the performance using DCMP(Directional-Constrained Minimization of Power)-based Beamspace technology using Two-frequency continuous wave (2FCW also known as FSK) is introduced.
2017-03-28
Technical Paper
2017-01-0027
Li Xu, Eric Tseng, Thomas Pilutti, Steven Schondorf
Abstract In the current Ford Pro-Trailer Backup Assist (TBA) system, trailer hitch angle is determined utilizing the reverse camera of the vehicle. In addition to being sensitive to environmental factors such as lighting conditions and occlusion, the vision-based approach is difficult to be applied to gooseneck or fifth wheel trailers. In this paper, a yaw rate based hitch angle observer is proposed as an alternative sensing solution for TBA. Based on the kinematic model of the vehicle-trailer, an instantaneous hitch angle is first derived by utilizing vehicle yaw rate, trailer yaw rate, vehicle velocity and vehicle/trailer parameters provided by the TBA system. Due to signal errors and parameter uncertainties, this instantaneous hitch angle may be noisy, especially at lower vehicle speed.
2017-03-28
Technical Paper
2017-01-0030
Shunsuke Kogure, Takashi Kato, Shin Osuga
Abstract With the improved safety performance of vehicles, the number of accidents has been decreasing. However, accidents due to driver distraction still occur, which means that there is a high need to determine whether a driver is properly looking at the surroundings. Meanwhile, with the trend toward partial automatic driving of vehicles in recent years, it is also urgently required that the state of the driver be grasped. Even if automatic driving is not installed, it is desired that the state of the driver be grasped and an application for control be performed depending on the state of the driver. Under these circumstances, we have built an algorithm that determines of the direction a driver is looking, to make a basic determination of whether or not the driver is in a state suitable for safe driving of the vehicle.
2017-03-28
Technical Paper
2017-01-0028
Xin Li, Weiwen Deng
Abstract This paper proposes a Real-Time Estimation of Radar Cross Section for ADAS Simulation, aimed to enable math-based virtual development and test of ADAS. The electromagnetic scattering mechanism is firstly analyzed with targets to be typical objects in traffic. Then a geometric model is developed, in which the object surfaces are divided into multiple scattering zones corresponding to different scattering mechanism. According to different surface curvature radius and scattering mechanism, the scattering zones are approximately equivalent to plane, cylinder, sphere and so on. Using the ARD model based on an improved physical optics and diffraction theory, RCS value of a zone is estimated. Then the RCS of the object surface is obtained by vector superposition of all zones. Some typical simulation comparisons are carried out, which proves the practicability of our method.
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
2017-01-0031
Mohamed Benmimoun
Abstract In the last years various advanced driver assistance systems (ADAS) have been introduced on the market. More highly advanced functions up to automated driving functions are currently under research. By means of these functions partly automated driving in specific situations is already or will be realized soon, e.g. traffic jam assist. Besides the technical challenges to develop such automated driving functions for complex situations, e.g. construction or intersection areas, new approaches for the evaluation of these functions under different driving conditions are necessary, in order to assess the benefits and identify potential weaknesses. Classical approaches for evaluation and market sign off will require an extensive testing, which results in high costs and time demands. Therefore the classical approaches are hardly feasible taking into account higher levels of support and automation. Today the final sign-off requires a high amount of real world tests.
2017-03-28
Technical Paper
2017-01-0035
Binyu Mei, Xuexun Guo, Gangfeng Tan, Yongbing Xu, Mengying Yang
Abstract Vehicle speed is an important factor to driving safety, which is directly related to the stability and braking performance of the vehicle. Besides, the precise measurement of the vehicle speed is the basis of some vehicle active safety systems. Even in the future intelligent transportation, high quality speed information will also play an important role. The commonly used vehicle speed measurement techniques are based on the wheel speed sensors, which are not accurate, especially when the wheels’ slip rate is not equal to zero. Focusing on these issues, image matching technology has been used to measure the vehicle speed in this paper. The image information of the road in the front of the vehicle is collected, and the pixel displacement of the vehicle is calculated by the matching system, thus accurately vehicle speed can be obtained. Compared with conventional speed measure technology, it has the advantages of wide measuring range, and high accuracy.
2017-03-28
Technical Paper
2017-01-0039
Toshiya Hirose, Yasufumi Ohtsuka, Masato Gokan
Abstract A vehicle-to-vehicle communication system (V2V) sends and receives vehicle information by wireless communication and assists safe driving. The present study investigated the activation timings of collision information support, collision caution support, and collision warning support provided by a V2V in an experiment using a driving simulator for four situations of (1) assistance in braking, (2) assistance in accelerating, (3) assistance in making a right turn, and (4) assistance in making a left turn at a blind intersection. The four situations are common scenarios of traffic accidents in Japan. Safety margins for collision information support and collision warning support were the time required for the driver to fully apply the brake pedal, while the safety margin for collision caution support was the time required for the driver to begin applying the brake pedal. The study investigated the effects of adding safety margins to standard activation timings.
2017-03-28
Technical Paper
2017-01-0040
Michael Hafner, Thomas Pilutti
Abstract We propose a steering controller for automated trailer backup, which can be used on tractor-trailer configurations including fifth wheel campers and gooseneck style trailers. The controller steers the trailer based on real-time driver issued trailer curvature commands. We give a stability proof for the hierarchical control system, and demonstrate robustness under a specific set of modeling errors. Simulation results are provided along with experimental data from a full-size pickup truck and 5th wheel trailer.
2017-03-28
Technical Paper
2017-01-0038
Corwin Stout, Milos Milacic, Fazal Syed, Ming Kuang
Abstract In recent years we have witnessed increased discrepancy between fuel economy numbers reported in accordance with EPA testing procedures and real world fuel economy reported by drivers. The debates range from needs for new testing procedures to the fact that driver complaints create one-sided distribution; drivers that get better fuel economy do not complain about the fuel economy, but only the ones whose fuel economy falls short of expectations. In this paper, we demonstrate fuel economy improvements that can be obtained if the driver is properly sophisticated in the skill of driving. Implementation of SmartGauge with EcoGuide into the Ford C-MAX Hybrid in 2013 helped drivers improve their fuel economy on hybrid vehicles. Further development of this idea led to the EcoCoach that would be implemented into all future Ford vehicles.
2017-03-28
Technical Paper
2017-01-0037
Xianyao Ping, Gangfeng Tan, Yahui Wu, Binyu Mei, Yuxin Pang
Abstract The drivers' hysteretic perception to surrounding environment will affect vehicular fuel economy, especially for the heavy-duty vehicles driving under complex conditions and long distance in mountainous areas. Unreasonable acceleration or deceleration on the slope will increase the fuel consumption. Improving the performance of the engine and the transmission system has limited energy saving potential, and most fuel-efficient driving assistant systems don't consider the road conditions. The main purpose of this research is to introduce an economic driving scheme with consideration of the prestored slope information in which the vehicle speed in mountainous slopes is reasonably planned to guide the driver's behavior for reduction of the fuel consumption. Economic driving optimization algorithm with low space dimension and fast computation speed is established to plan accurate and real-time economic driving scheme.
2017-03-28
Technical Paper
2017-01-0043
Michael Smart, Satish Vaishnav, Steven Waslander
Abstract Robust lane marking detection remains a challenge, particularly in temperate climates where markings degrade rapidly due to winter conditions and snow removal efforts. In previous work, dynamic Bayesian networks with heuristic features were used with the feature distributions trained using semi-supervised expectation maximization, which greatly reduced sensitivity to initialization. This work has been extended in three important respects. First, the tracking formulation used in previous work has been corrected to prevent false positives in situations where only poor RANSAC hypotheses were generated. Second, the null hypothesis is reformulated to guarantee that detected hypotheses satisfy a minimum likelihood. Third, the computational requirements have been greatly reduced by computing an upper bound on the marginal likelihood of all part hypotheses upon generation and rejecting parts with an upper bound less likely than the null hypothesis.
2017-03-28
Technical Paper
2017-01-0044
Roman Schmied, Gunda Obereigner, Harald Waschl
Abstract In the field of advanced driver assistance systems (ADAS) the capability to accurately estimate and predict the driving behavior of surrounding traffic participants has shown to enable significant improvements of the respective ADAS in terms of economy and comfort. The interaction between the different participants can be an important aspect. One example for this interaction is the car following behavior in dense urban traffic situations. There are different phenomenological or psychological models of human car following which also consider variations between different participants. Unfortunately, these models can seldom be applied for control directly or prediction in vehicle applications. A different way is to follow a control oriented approach by modeling the human as a time delay controller which tracks the inter-vehicle distance. The parameters are typically chosen based on empirical rules and do not consider variations between drivers.
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
2017-01-0042
David Andrade, Rodrigo Adamshuk, William Omoto, Felipe Franco, João Henrique Neme, Sergio Okida, Angelo Tusset, Rodrigo Amaral, Artur Ventura, Max Mauro Dias Santos
Abstract The continuous growth of market for Advanced Driver Assistance Systems based on image processing features leads to the advance of the applied techniques, increasing thus the driving safety. Mostly of the edge detection algorithms are traditional approaches, and to achieve improvements it is necessary to combine different methods. The purpose of this work is to implement a strategy for road lanes detection using the traditional Canny operator. Oriented filters are used to remove unnecessary information and vehicle’s yaw rate signal is used to adaptively correct the filter orientation according to the lane boundaries directions. In sequence, morphological filters using dilation and analysis of connected components are applied in order to remove the noise components of the edge detection stage.
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