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Vehicle Velocity Prediction Using Artificial Neural Network and Effect of Real World Signals on Prediction Window.

Colorado State University-Aaron Rabinowitz, Thomas Bradley
Western Michigan University-Tushar Gaikwad, Farhang Motallebiaraghi, Zachary Asher, Alvis Fong, Rick Meyer
  • Technical Paper
  • 2020-01-0729
To be published on 2020-04-14 by SAE International in United States
Prediction of vehicle velocity is important since it can realize improvements in the fuel economy/energy efficiency, drivability and safety. Velocity prediction has been addressed in many publications. Several references considered deterministic and stochastic approaches such as Markov chain, autoregressive models, and artificial neural networks. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain inclusive datasets. Using these inclusive datasets of sensors in deep neural networks, high accuracy velocity predictions can be achieved. This research builds upon previous findings that Long Short-Term Memory (LSTM) deep neural networks provide the highest velocity prediction fidelity. We developed LSTM deep neural network which uses different groups of datasets collected in Fort Collins. Synchronous data was gathered using a test vehicle equipped with sensors to measure ego vehicle position and velocity, ADAS-derived near-neighbor relative position and velocity, and infrastructure-level transit time and signal phase and timing. Effect of different group of datasets on forward velocity prediction window of 10, 15, 20 and 30 seconds is studied. Developed algorithm is tested…
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Effects of a Probability-Based Green Light Optimized Speed Advisory on Dilemma Zone Exposure

Indiana Department of Transportation-James Sturdevant
Purdue University-Enrique Saldivar-Carranza, Howell Li, Woosung Kim, Jijo Mathew, Darcy Bullock
  • Technical Paper
  • 2020-01-0116
To be published on 2020-04-14 by SAE International in United States
Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data. By utilizing this advisory method, real-time communications from the vehicle to infrastructure (V2I) become unnecessary, eliminating data-loss related issues. The effects of three different advice approaches (conservative, balanced, and aggressive) on dilemma zone exposure are analyzed. Proof of concept is carried out by virtually driving through a test-route composed of an arterial that…
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Data-driven framework for fuel efficiency improvement in extended range electric vehicle used in package delivery applications

University of Minnesota-Pengyue Wang, William Northrop
  • Technical Paper
  • 2020-01-0589
To be published on 2020-04-14 by SAE International in United States
Extended-range electric vehicles (EREVs) are a potential solution for fossil fuel usage mitigation and on-road emissions reduction. EREVs can be shown to yield significant fuel economy improvements when the proper energy management strategies (EMSs) are employed. However, many in-use EREVs achieve only moderate fuel reduction compared to conventional vehicles due to the fact that their EMS is far from optimal. This paper focuses on rule-based optimization methods to improve the fuel efficiency of EREV last-mile delivery vehicles equipped with two-way Vehicle-to-Could (V2C) connectivity. The method uses previous vehicle data collected on actual delivery routes and a machine learning method to improve the fuel economy of future routes. The paper first introduces the main challenges of the project such as inherent uncertainty in human driver behavior and in the roadway environment. Then, the framework of our practical physics-model guided data-driven approach is introduced. For vehicles with small amounts of previous data, a Bayesian method is used to adjust a control parameter in the EMS offline for each vehicle with introduced prior information derived from large numbers…
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Hardware-in-the-Loop and Public Road Testing of RLVW and GLOSA Connected Vehicle Applications

Camp LLC-Jayendra Parikh
Ford Motor Co., Ltd.-Alexander Katriniok
  • Technical Paper
  • 2020-01-1379
To be published on 2020-04-14 by SAE International in United States
Each year, large number of traffic accidents with a large number of injuries and fatalities occur. To reduce these accidents, automotive companies have been developing newer and better active and passive safety measures to increase the safety of passengers. With the developments in connected vehicle infrastructure on the roads and on-board-units for Vehicle to Everything (V2X) connectivity in newer vehicles, V2X communication offers possibilities for preventing accidents as V2X equipped vehicles have situational awareness of other vehicles and road users around them through Vehicle to Vehicle (V2V) and Vehicle to Pedestrian (V2P) communication, and signal phase and timing and map information on signalized intersections through Vehicle to Infrastructure (V2I) communication. Therefore, vehicle on-board computers can calculate an optimal speed profile for fuel economy purposes or prevent crashes related to red light violations. This paper addresses these two main advantages, firstly by developing and using Hardware-in-the-Loop (HIL) simulator testing and experimental vehicle testing environments of an algorithm for preventing red light violation, called Red Light Violation Warning (RLVW). The HIL simulator used in the testing is…
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Performance Evaluation of the Pass at Green Connected Vehicle V2I Application Using Simulation, Dynamometer and Track Testing

Ohio State University-Ozgenur Kavas-Torris, Mustafa Ridvan Cantas, Sukru Yaren Gelbal, Levent Guvenc
  • Technical Paper
  • 2020-01-1380
To be published on 2020-04-14 by SAE International in United States
In recent years, the trend in the automotive industry has been favoring the reduction of fuel consumption in vehicles with the help of new and emerging technologies, such as Vehicle to Infrastructure (V2I), Vehicle to Vehicle (V2V) and Vehicle to Everything (V2X) communication. As the world of transportation gets more and more connected through these technologies, the need to implement algorithms with V2I capability is amplified. In this paper, an algorithm called Pass at Green (PaG), utilizing V2I to modify the speed profile of a vehicle to decrease fuel consumption has been studied. PaG uses Signal Phase and Timing (SPaT) information acquired from upcoming traffic lights, which are the current phase of the upcoming traffic light and the remaining time that the phase stays active. Then, PaG modifies the speed of the vehicle by accelerating, keeping its speed constant or decelerating to decrease fuel consumption, minimize idling time and reduce the likelihood of catching a red light in an intersection. As presented in this paper, the fuel economy benefit achieved by the PaG algorithm was…
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Leverage wireless technologies in timber harvesting to enhance operational productivity and business profitability

John Deere-Ishani Pandit, Suchitra Iyer
  • Technical Paper
  • 2020-01-1378
To be published on 2020-04-14 by SAE International in United States
Growing needs of forestry products; primarily wood followed by pulp and paper industry have mechanized the process of harvesting timber in most part of world. Such job sites have several machines and vehicles working together to harvest and transport the logs. Timber logging is very similar to crop harvesting with longer harvesting cycle and hence it is critical that every part of it is effectively utilized; timely harvest and transport to factories play an important role. Traditionally, these areas have had little cellular connectivity, restricting communication between operators, machines, land owners and factories. With better connectivity, it will be easier to monitor and operate job sites for example if skidder would know how many trees are felled, how many logs and bunches are created and where they are kept; it would reduce time and fuel spent in searching for logs. Also, with better communication between machines, skidder would know when to pick up logs and avoid longer wait time. Timely pick up of felled trees is critical in ensuring log quality. With upcoming wireless technologies…

New Architectural Design of the Runtime Server for Remote Vehicle Communication Services

SAE International Journal of Connected and Automated Vehicles

Germany-Vladivy Poaka
Technische Universität Clausthal, Germany-Sven Hartmann
  • Journal Article
  • 12-03-01-0002
Published 2020-01-17 by SAE International in United States
This article addresses the issue of a design to provide remote vehicle communication services sustainably. These services include new features such as remote repair of Electronic Control Unit (ECU)’s software errors and feature on demand, to mention just a few key objectives. With the usual implementations of the Modular Vehicle Communication Interface (MVCI) runtime server [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14] many difficulties remain [15]. They are not sustainable and require dedicated hardware. The Dictionary Server discussed here provides necessary data to diagnostic applications in general, without putting at risk Original Equipment Manufacturer (OEM)’s expertise. It also provides data to the road infrastructure for V2V- and Vehicle-to-Infrastructure (V2X)-based services. This crucial diagnostic data contains ECUs’ communication parameters, memory programming data, and other available functions. They are kept confidentially by OEMs. Furthermore, our solution is nondisruptive, as it also supports traditional vehicle communication services. We evaluated a prototype in terms of time complexity, scalability, and availability.
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Connected Vehicles - An Ecosystem for Services

Automotive Software-Prabha Baragur Venkataram
  • Technical Paper
  • 2019-28-2447
Published 2019-11-21 by SAE International in United States
This paper outlines the different aspects of the Connected Vehicle concept. The blocks required to implement a Connected Vehicle infrastructure is also discussed in detail.Two main types of short-range wireless communication are discussed in Connected Vehicles context namely Vehicle-to-Vehicle (V2V), and Vehicle-to-Infrastructure (V2I) communication.An overview of the evolution of the Connected Vehicle and its operational aspects are presented together with its application. The impacts and potential operational benefits of the Connected Vehicle are discussed.The various challenges to architect non-functional requirements in the case of Connected Vehicle technology are identified and discussed.
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Active Safety System for Connected Vehicles

SAE International Journal of Connected and Automated Vehicles

Michigan State University, USA-Hothaifa Al-Qassab, Su Pang, Mohammed Al-Qizwini, Daniel Kent, Hayder Radha
  • Journal Article
  • 12-02-03-0013
Published 2019-10-14 by SAE International in United States
The development of connected-vehicle technology, which includes vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, opens the door for unprecedented active safety and driver-enhanced systems. In addition to exchanging basic traffic messages among vehicles for safety applications, a significantly higher level of safety can be achieved when vehicles and designated infrastructure locations share their sensors’ data. In this article, we propose a new system where cameras installed on multiple vehicles and infrastructure locations share and fuse their visual data and detected objects in real time. The transmission of camera data and/or detected objects (e.g., pedestrians, vehicles, cyclists, etc.) can be accomplished by many communication methods. In particular, such communications can be accomplished using the emerging Dedicated Short-Range Communications (DSRC) technology. In our proposed system the vehicle receiving the visual data from an adjacent vehicle fuses the received visual data with its own camera views to create a much richer visual scene. We conducted several experiments across a pair of vehicles equipped with DSRC devices and our proposed system. These experiments demonstrated that our system achieves high accuracy,…
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Data connectivity in HARSH ENVIRONMENTS

SAE Truck & Off-Highway Engineering: August 2019

Christian Manko
  • Magazine Article
  • 19TOFHP08_03
Published 2019-08-01 by SAE International in United States

Ensuring high-speed data transmission requires OEM designers to think more about components, placement and the impact of environmental conditions early in design.

Technology advances are increasingly bringing a new level of connectivity to industrial and commercial vehicles. Customers are demanding functionality that automates or enhances operational tasks to increase driver productivity and safety and, in many cases, also brings down total cost of ownership.

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