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A Dynamic Local Trajectory Planning and Tracking Method for UGV Based on Optimal Algorithm

Chongqing University-Yangxin Sun, Zhenfei Zhan, Yudong Fang, Ling Zheng, Liuhui Wang, Gang Guo
Published 2019-04-02 by SAE International in United States
UGV (Unmanned Ground Vehicle) is gaining increasing amounts of attention from both industry and academic communities in recent years. Local trajectory planning is one of the most important parts of designing a UGV. However, there has been little research into local trajectory planning and tracking, and current research has not considered the dynamic of the surrounding environment. Therefore, we propose a dynamic local trajectory planning and tracking method for UGV driving on the highway in this paper. The method proposed in this paper can make the UGV travel from the navigation starting point to the navigation end point without collision on both straight and curve road. The key technology for this method is trajectory planning, trajectory tracking and trajectory update signal generation. Trajectory planning algorithm calculates a reference trajectory satisfying the demands of safety, comfort and traffic efficiency. A trajectory tracking controller based on model predictive control is used to calculate the control inputs to make the UGV travel along the reference trajectory. The trajectory update signal is generated when needed (e.g. there has a…
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Cooperative Collision Avoidance in a Connected Vehicle Environment

Ohio State University-Sukru Yaren Gelbal, Sheng Zhu, Gokul Arvind Anantharaman, Bilin Aksun Guvenc, Levent Guvenc
Published 2019-04-02 by SAE International in United States
Connected vehicle (CV) technology is among the most heavily researched areas in both the academia and industry. The vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to pedestrian (V2P) communication capabilities enable critical situational awareness. In some cases, these vehicle communication safety capabilities can overcome the shortcomings of other sensor safety capabilities because of external conditions such as 'No Line of Sight' (NLOS) or very harsh weather conditions. Connected vehicles will help cities and states reduce traffic congestion, improve fuel efficiency and improve the safety of the vehicles and pedestrians. On the road, cars will be able to communicate with one another, automatically transmitting data such as speed, position, and direction, and send alerts to each other if a crash seems imminent. The main focus of this paper is the implementation of Cooperative Collision Avoidance (CCA) for connected vehicles. It leverages the Vehicle to Everything (V2X) communication technology to create a real-time implementable collision avoidance algorithm along with decision-making for a vehicle that communicates with other vehicles. Four distinct collision risk environments are…
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A Study of the Performance of Automatic Emergency Braking (AEB) Systems Equipped on Passenger Vehicles for Model Years 2013 to 2018

30 Forensic Engineering-Djordje Miholjcic, Mark Fabbroni, Richard Robinson
Published 2019-04-02 by SAE International in United States
Over the past decade, manufacturers have introduced vehicles equipped with Automatic Emergency Braking (AEB) into the North American market. These vehicles have the capability to not only detect an impending collision and warn the driver, but also to initiate braking independent of the driver. The collision avoidance strategies used by the various manufacturers have not been studied extensively. In 2013, the Insurance Institute for Highway Safety (IIHS) began testing vehicles equipped with AEB in rear-end collision situations in order to issue their front crash prevention safety ratings for these vehicles. To date, over 180 vehicles from 31 manufactures spanning model years 2013 to 2018 have been tested. This paper presents an analysis of the data collected in these tests. The objective of the study was to assess the differences in performance and strategies used, at two different closing speeds, between manufacturers. The difference in strategies included differences in braking rates and timing of the onset of braking. With more vehicles being equipped with AEB systems each year, this study will be a valuable resource for…
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Naturalistic Driving Behavior Analysis under Typical Normal Cut-In Scenarios

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 scenarios are common and of potential risk in China but Advanced Driver Assistant System (ADAS) doesn’t work well under such scenarios. In order to improve the acceptance of ADAS, its reactions to Cut-in scenarios should meet driver’s driving habits and expectancy. Brake is considered as an express of risk and brake tendency in normal Cut-in situations needs more investigation. Under critical Cut-in scenarios, driver tends to brake hard to eliminate collision risk when cutting in vehicle right crossing lane. However, under less critical Cut-in scenarios, namely normal Cut-in scenarios, driver brakes in some cases and takes no brake maneuver in others. The time when driver initiated to brake was defined as key time. If driver had no brake maneuver, the time when cutting-in vehicle right crossed lane was defined as key time. This paper focuses on driver’s brake tendency at key time under normal Cut-in situations. Environment factors (for example, traffic condition and road type), cutting-in vehicle type and motion factors were considered as influence factors. To comprehensively take those factors into account, cluster…
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Coupling Safety Distance Model for Vehicle Active Collision Avoidance System

Jilin University Automotive Engineering College-Jie Dong, Liang Chu
Published 2019-04-02 by SAE International in United States
As an important part of the active collision avoidance system of the vehicle, the safety distance model determines the safety of the vehicle and the utilization of the road. The safety distance is too large to affect the traffic flow of the road. If it is too small, it will cause traffic accidents. Therefore, the design of the safety distance model depends on whether it can adapt to the complex and changing traffic environment, and effectively balance the safety of the driving process, the car following and the utilization of the road. According to the actual requirements of system security alarm and system false alarm reduction, three safety distance models and one constraint condition are established. The safety distance model maintained by the vehicle spacing, the safety distance model reflecting the characteristics of the driver, and the longitudinal minimum safety distance model when steering the lane change. When the pre-crash time is equal to the driver response time, the distance at this time is the minimum constraint condition of the warning distance. Based on these,…
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Road Tested

Autonomous Vehicle Engineering: March 2019

Lindsay Brooke
  • Magazine Article
  • 19AVEP03_11
Published 2019-03-01 by SAE International in United States

Transportation-infrastructure expert Kirk Steudle reflects on the rapid progress toward the connected-AV future and the challenges ahead.

In the auto industry, mechanical and electrical engineers work from the tire up. Civil engineers work from the tire down,” quips Kirk Steudle. “And although it's taken a while for both to understand each other's jargon, the connected-and-autonomous vehicle is forcing them all together-to solve problems for society's mobility.”

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Deep Learning in Machine Vision

  • Magazine Article
  • TBMG-33894
Published 2019-03-01 by Tech Briefs Media Group in United States

FLIR Systems has introduced their Firefly machine vision camera with open platform deep learning inference onboard. Deep learning makes it possible to easily develop high performance solutions for difficult vision problems.

 

Evaluation of V2V Reception Cadence- A New Metric for System Level Performance Analysis

General Motors LLC-Ayelet Aharon, Igal Kotzer
Published 2019-01-16 by SAE International in United States
Vehicle to Everything (V2X) communication is a prominent solution for active safety collision avoidance and for providing autonomous vehicles Non-Line of Sight (NLOS) capabilities. For safety purposes, it is essential the V2X technology would support communication between all road users, e.g., Vehicles (V2V), pedestrians (V2P) and road infrastructure (V2I). Hence, the efficiency of a V2V communication solution should be evaluated through system level performance. In addition, the examined performance metrics need to reflect safety related properties. Metrics as Packet Reception Ratio (PRR) and transmission latencies, which are commonly used to assess V2X system’s functionality, aren’t enough since reception latencies are overlooked. The latter is crucial in ensuring messages would reach their destination on time to avoid hazardous incidents. The reception cadence may be much lower than this of the transmission due to various phenomenon (e.g. channel congestion). Still, whether this pose a safety’s threat depends on mechanical aspects such as the distance between vehicles or their relative speed. In this paper, we present a metric called CD-PRR (Cadence Dependent PRR) - a generalization of the…
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Clear Vision for UAVs

  • Magazine Article
  • TBMG-33549
Published 2019-01-01 by Tech Briefs Media Group in United States

The rapidly expanding world-wide use of unmanned aerial vehicles (UAV) — drones — is driving a growing market for specialized imaging technology. According to Chris Yiu, General Manager, High Performance BU at SmartSens Technology (Santa Clara, CA, Shanghai, China), there are two basic functions for imaging technology aboard drones: one is optical flow, collision-avoidance sensing; the other is video capture of objects on the ground. With the recent emphasis on self-flying drones, collision-avoidance is of major importance.

 

Theory of Collision Avoidance Capability in Automated Driving Technologies

SAE International Journal of Connected and Automated Vehicles

Toyota Motor Corporation, Japan-Toshiki Kindo
Toyota Research Institute-North America, USA-Bunyo Okumura
  • Journal Article
  • 12-01-02-0004
Published 2018-10-29 by SAE International in United States
To evaluate that automated vehicle is as safe as a human driver, a following question is studied: how does an automated vehicle react under extreme conditions close to collision? In order to understand the collision avoidance capability of an automated vehicle, we should analyze not only such post-extreme condition behavior but also pre-extreme condition behavior. We present a theory to analyze the collision avoidance capability of automated driving technologies. We also formulate a collision avoidance equation on the theory. The equation has two types of solutions: response driving plans and preparation driving plans. The response driving plans are supported by response strategy on which the vehicle reacts after detection of a hazard and they are highly efficient in terms of travel time. The preparation driving plans are supported by preparation strategy on which the vehicle simulates each hazard before detecting hazards and they are safer than the response driving plans but it is not always efficient. The theory suggests that applicative driving plan of automated vehicle is as follows: 1) the automated vehicle takes the…
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