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SMART HONKING

Mahindra & Mahindra, Ltd.-Priyanka Marudhavanan
  • Technical Paper
  • 2019-28-2463
To be published on 2019-11-21 by SAE International in United States
Smart Honking Keywords-Safety, Connectivity, GPS M. Priyanka, Mahindra&Mahindra, India Sai Himaja Nadimpalli, Mahindra&Mahindra,India Keywords-Honking , Infotainment , GPS Research and/or Engineering Questions/Objective: In India unnecessary vehicular honking is the main reason for noise pollution. The problem is worst at traffic signals where drivers start honking without waiting for the signal to turn green or for traffic to move. Drivers show no respect to the law that prohibits the use of horn at traffic signals and other silent zones such as areas near hospitals, schools, religious places and residential areas. Vehicular honking in cities has reached at an alarming level and contributes approximately 70% of the noise pollution in our environment.The unwanted sound can affect human health and behavior, causing annoyance, depression, hypertension, stress, hearing loss, memory loss and panic attacks. Most of the drivers try to release their frustration and tension by blowing horns, possibly due to lack of awareness regarding the negative effects of noise but most likely it is because of the lack of civic sense.. Limitations: There is a provision of sign…
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In-Vehicle Directional Audio Streaming

Aptiv Components India Pvt Ltd.-Anitha Loganathan, Vijayalakshmi kr
  • Technical Paper
  • 2019-28-2448
To be published on 2019-11-21 by SAE International in United States
In-Vehicle Infotainment has evolved greatly over years from a simple tuner based radio with a small LED display to a complex system with highly intelligent interactive HMI which can mirror the smart phone. The full-fledged entertainment features like watching videos are restricted to only rear passengers. In drive mode, drivers are limited with access to only audio to avoid driver distraction. Rear passengers and drivers are classified into different audio zones. Each of the rear passengers are equipped with headsets so that audio merging with driver zone can be avoided. This leads to passenger discomfort, as many passengers would not prefer to hook up with headset all the time. Now the automotive world is envisioned to reach fully autonomous mode where there is no driver and every passenger is interested to listen to music/video of diverse interest. The audio zones in autonomous car need not be zonified or linear. Circular audio zone can also be a good choice for autonomous cars. There are situations in autonomous cars where passenger is asleep in vehicle and hence…
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Evaluation of a Robust Haptic Interface for Semi-Autonomous Vehicles

SAE International Journal of Connected and Automated Vehicles

Clemson University, USA-Chengshi Wang, Yue Wang, John R. Wagner
  • Journal Article
  • 12-02-02-0007
Published 2019-05-15 by SAE International in United States
The advent of steer-by-wire technologies has changed the driving paradigm for drivers and vehicle autonomy. Such technologies integrate electric motors to actuate the tire-road plus human-machine interfaces. Steer-by-wire vehicles can benefit from haptic concepts through the provision of tunable force feedback, coupled with nonlinear control, to introduce lane keeping and pathway following technologies that minimize and possibly eliminate driver actions. In this article, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects investigated these haptic steering interfaces over a prescribed series of driving maneuvers through real-time data logging and post-test questionnaires. A conventional steering wheel with the robust sliding mode controller was used for all the driving events for comparison. Subjective and objective results from the tests demonstrate that the driver’s experience can be enhanced by up to 76.3% with a robotic grip steering input when compared to…
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PHEV Real World Driving Cycle Energy and Fuel and Consumption Reduction Potential for Connected and Automated Vehicles

Michigan Technological University-Darrell Robinette, Eric Kostreva, Alexandra Krisztian, Anthony Lackey, Christopher Morgan, Joshua Orlando, Neeraj Rama
Published 2019-04-02 by SAE International in United States
This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge. After completing 30 baseline drive cycles, a design for six sigma (DFSS) L18 array was designed to look at sensitivity of a range of parameters to energy consumption as related to connected and automated vehicles to target highest return on engineering development effort. The parameters explored in the DFSS array that showed the most sensitivity, in order of…
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Evaluation of Different ADAS Features in Vehicle Displays

University of Michigan-Abhishek Mosalikanti, Pranove Bandi, Sang-Hwan Kim
Published 2019-04-02 by SAE International in United States
The current study presents the results of an experiment on driver performance including reaction time, eye-attention movement, mental workload, and subjective preference when different features of Advanced Driver Assistance Systems (ADAS) warnings (Forward Collision Warning) are displayed, including different locations (HDD (Head-Down Display) vs HUD (Head-Up Display)), modality of warning (text vs. pictographic), and a new concept that provides a dynamic bird’s eye view for warnings.Sixteen drivers drove a high-fidelity driving simulator integrated with display prototypes of the features. Independent variables were displayed as modality, location, and dynamics of the warnings with driver performance as the dependent variable including driver reaction time to the warning, EORT (Eyes-Off-Road-Time) during braking after receiving the warning, workload and subject preference. The primary results were in line with previous research, validating previous claims of the superiority of HUD over HDD in warning delivery. It was also found that the text format of the warning yielded higher response rates along with lower workload, while most participants preferred the dynamic bird’s eye view layout.
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Robust Validation Platform of Autonomous Capability for Commercial Vehicles

Isuzu Technical Center of America Inc.-Yong Sun, Hanxiang Li, Weilun Peng
Published 2019-04-02 by SAE International in United States
Global deployment of autonomous capability for commercial vehicles is a big challenge. In order to improve the robustness of autonomous approach under different traffic scenarios, environments, road conditions, and driver behaviors, a combined approach of virtual simulation, vehicle-in-the-loop (VIL) testing, proving ground testing, and final field testing have been established for algorithms validation. During the validation platform setup, different platforms for different functionalities have been studied, including open source virtual testing environment (CARLA, AirSim), and commercial one (IPG). We also cooperate with MCity to do proving ground validation. In virtual testing, the functionality of sensors (camera, radar, Lidar, GPS, IMU) and vehicle dynamic models can be applied in the virtual environment. In VIL testing, real world and virtual test will be connected for different validation purposes. The proving ground testing will be performed in real environment with rich scenarios and high safety. Several challenges have been overcome during implementation, including data transmission, computing time, sensor system consistency, vehicle dynamic model consistency and etc. In this paper, a robust autonomous driving validation platform, including perception, planning…
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How to Model Real-World Driving Behavior? Probability-Based Driver Model for Energy Analyses

Daimler AG-Tobias Schuermann, Tobias Goedecke, Stefan Schmiedler, Daniel Goerke
University of Applied Sciences Esslingen-Kai André Boehm
Published 2019-04-02 by SAE International in United States
A wide variety of applications such as driver assistant and energy management systems are researched and developed in virtual test environments. The safe testing of the applications in early stages is based on parameterizable and reproducible simulations of different driving scenarios. One possibility is modeling the microscopic driving behavior to simulate the longitudinal vehicle dynamics of individual vehicles. The currently used driver models are characterized by a conflict regarding comprehensibility, accuracy and calibration effort. Due to the importance for further analyses this conflict of interests is addressed by the presentation of a new microscopic driver model in this paper. The proposed driver model stores measured driving behaviors with its statistical distributions in maps. Thereby, the driving task is divided into free flow, braking in front of stops and following vehicles ahead. This makes it possible to display the driving behavior in its entirety. The comprehensibility of this driver model is given by its simplicity and the calibration effort is low with existing measurement data. These data are recorded with a testing vehicle by a map-…
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Driver Behavior Classification under Cut-In Scenarios Using Support Vector Machine Based on Naturalistic Driving Data

SMVIC-Jianyong Cao, Feng Yu
Tongji University-Xuehan Ma, Zhixiong Ma, Xichan Zhu
Published 2019-04-02 by SAE International in United States
Cut-in scenario is common in traffic and has potential collision risk. Human driver can detect other vehicle’s cut-in intention and take appropriate maneuvers to reduce collision risk. However, autonomous driving systems don’t have as good performance as human driver. Hence a deeper understanding on driving behavior is necessary. How to make decisions like human driver is an important problem for automated vehicles. In this paper, a method is proposed to classify the dangerous cut-in situations and normal ones. Dangerous cases were extracted automatically from naturalistic driving database using specific detection criteria. Among those cases, 70 valid dangerous cut-in cases were selected manually. The largest deceleration of subject vehicle is over 4 m/s2. Besides, 249 normal cut-in cases were extracted by going through video data of 2000km traveled distance. In normal driving cases, subject vehicle may brake or keep accelerating and the largest deceleration was less than 3 m/s2. The time when driver initiated to brake was defined as key time. But if driver had no brake maneuver (it happened in normal driving), the time when…
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“Fitting Data”: A Case Study on Effective Driver Distraction State Classification

American Optimal Decisions, Inc.-Alexey Zrazhevsky
DENSO International America Inc.-Yu Zhang
Published 2019-04-02 by SAE International in United States
The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases. The new aspect of this research is optimization of the classification effort, which involved cardinality constraints on 16 overt driver behavior measures. A spline transformation was also implemented to achieve better classification performance. In addition to testing our optimization approach with the SVM, we also explored logistic regression. Results revealed the spline-transformed variables to produce a good “out-of-sample” performance for both the SVM…
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Instrumented Steering Wheel for Accurate ADAS Development

Politecnico di Milano-Gianpiero Mastinu, Massimiliano Gobbi, Francesco Comolli
Toyota Central R&D Labs-Masatoshi Hada
Published 2019-04-02 by SAE International in United States
We introduce in this paper a new Instrumented Steering Wheel (ISW) for ADAS development. The ISW has been designed, constructed and employed with satisfactory results. The ISW is able to measure three forces, three moments and the grip force at each hand of the driver. The ISW has been used for ADAS activities on an instrumented road vehicle. The aim was to use both the vehicle states and the ISW data for evaluating the driver behaviour. Two research activities were performed. The first activity refers to monitoring the driver behaviour during tests on a track. The second activity refers to the use of haptic ISWs, able to improve the ADAS systems.Referring to the first activity, the greatest majority of drivers applied always the same sequence of forces (pull, radial, tangential) either during emergency manoeuvres, either during slow speed curving.Referring to the second activity, we found that, by exploiting an ISW, the driver steering purpose could be inferred, before the steering wheel is rotated.
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