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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 simulating drives through a test-route composed of an arterial that…
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In-Situ Measurement of Component Efficiency in Connected and Automated Hybrid-Electric Vehicles

Southwest Research Institute-Peter Lobato, Kyle Jonson, Sankar Rengarajan, Jayant Sarlashkar
  • Technical Paper
  • 2020-01-1284
To be published on 2020-04-14 by SAE International in United States
Connected and automated driving technology is known to improve real-world vehicle efficiency by considering information about the vehicle’s environment such as traffic conditions, traffic lights or road grade. This study shows how the powertrain of a hybrid-electric vehicle realizes those efficiency benefits by developing methods to directly measure transient real-time efficiency and power losses of the vehicle’s powertrain components through chassis-dynamometer testing. This study is a follow-on to SAE Technical Paper 2019-01-0116, Test Methodology to Quantify and Analyze Energy Consumption of Connected and Automated Vehicles, to understand the sources of efficiency gains resulting from connected and automated vehicle driving. A 2017 Toyota Prius Prime was instrumented to collect power measurements throughout its powertrain and driven over a specific driving schedule on a chassis dynamometer. The same driving schedule was then modified to simulate a connected and automated vehicle driving profile, and the sources of vehicle efficiency improvements are analyzed. While conventional powertrain components typically only have two sources and sinks of power, e.g. an input and output shaft, the components of modern hybrid-electric vehicles are…
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An Image Recognition Application Method for Vertical Movement of Vehicles

Wuhan University of Technology-Ming Li, Gangfeng Tan, Zhenyu Wang, Haoyu Wang, Yifeng Jiang, Donghua Guo, Jiaming Feng
  • Technical Paper
  • 2020-01-0733
To be published on 2020-04-14 by SAE International in United States
In ITS, image processing technology is applied to a wide variety of areas such as visual-based intelligent vehicle navigation, visual-based traffic monitoring and visual-based traffic management. In the identification system of the vehicle body characteristics, most of the recognition is the license plate and the car emblem, etc. This paper proposes an image recognition application method for the vertical motion of the car while driving, mainly including vertical height detection and vertical displacement velocity acceleration recognition. The edge detection model of the image object is established by using the gray image to obtain the car motion segmentation image. At the same time, an image length and actual length coordinate conversion model is established, which can calculate an arbitrary actual length of the image object. In this paper, the Yuejin Shangjun X500 van is selected as the test vehicle. Using camera capture the video data and the height of the vehicle is recognized for each frame. The height is compared with the actual length. The absolute error can be controlled within 40mm, and the minimum relative…
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Deep Learning-based Queue-aware Eco-Approach and Departure system for Plug-in Hybrid Electric Bus at signalized intersections: a simulation study

Oak Ridge National Laboratory-Zhiming Gao, Tim LaClair
University of California-Fei Ye, Peng Hao, Guoyuan Wu, Danial Esaid, Kanok Boriboonsomsin, Matthew Barth
  • Technical Paper
  • 2020-01-0584
To be published on 2020-04-14 by SAE International in United States
Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where signal phase and timing (SPaT) and geometric intersection description (GID) information are well utilized to guide the vehicles passing through the intersection in a most energy efficient manner. Previous studies by the authors formulated the optimal trajectory planning problem as finding the shortest path on a graph model where the nodes define the reachable states of the host vehicle (e.g., speed, location) at each time step, the links govern the state reachability from previous time step, and the link costs represent the energy consumption rate due to state transition. This method is effective in energy saving, but its computation efficiency can be enhanced by machine learning techniques. In this paper, we propose an innovative Deep Learning-based Queue-aware Eco-Approach and Departure (DLQ-EAD) System for a Plug-in Hybrid Electric Bus (PHEB), to provide an online optimal vehicle trajectory considering both the downstream traffic conditions (i.e. traffic lights, queues) and vehicle powertrain efficiency. Based on the optimal solutions…
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A Study of Using a Reinforcement Learning Method to Improve Fuel Consumption of a Connected Vehicle with Signal Phase and Timing Data

The University of Alabama-Ashley Phan, Hwan-Sik Yoon
  • Technical Paper
  • 2020-01-0888
To be published on 2020-04-14 by SAE International in United States
Connected and automated vehicles (CAVs) promise to reshape two areas of the mobility industry: the transportation and driving experience. The connected feature of the vehicle uses communication protocols to provide awareness of the surrounding world while the automated feature uses technology to minimize driver dependency. Constituting a subset of connected technologies, vehicle-to-infrastructure (V2I) technologies provide vehicles with real-time traffic light information, or Signal Phase and Timing (SPaT) data. In this paper, the vehicle and SPaT data are combined with a reinforcement learning (RL) method as an effort to minimize the vehicle’s energy consumption. Specifically, this paper explores the implementation of the deep deterministic policy gradient (DDPG) algorithm. As an off-policy approach, DDPG utilizes the maximum Q-value for the state regardless of the previous action performed. In this research, the SPaT data collected from dedicated short-range communication (DSRC) hardware installed at 16 real traffic lights is utilized in a simulated road modeled after a road in Tuscaloosa, Alabama. The vehicle is trained using DDPG and the SPaT data to determine the optimal action to take in…
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Hardware-in-the-Loop, Traffic-in-the-Loop and Software-in-the-Loop Autonomous Vehicle Simulation for Mobility Studies

Ford Motor Company-Archak Mittal, Adit Joshi, James Fishelson
Ohio State University-Karina Meneses Cime, Mustafa Ridvan Cantas, Garrett Dowd, Levent Guvenc, Bilin Aksun Guvenc
  • Technical Paper
  • 2020-01-0704
To be published on 2020-04-14 by SAE International in United States
We are interested in finding and analyzing the relevant parameters affecting traffic flow when introducing Autonomous Vehicles for ride hailing applications and Autonomous Shuttles for circulator applications in geo-fenced urban areas. Different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate such scenarios. On the other hand, software for autonomous entities is also continuously improved. However, benchmarks for such software usually run in isolation from other factors such as the ones mentioned above. Yet, in order to effectively study the effects of the introduction of autonomous agents into city streets, all these factors must be considered. For these reasons, different simulation tools are needed to converge into a single simulation environment. We create a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities. Our work merges the traffic simulation software Vissim to create realistic traffic, the vehicle dynamic simulation software…
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The Effects of Varying Penetration Rates of L4-L5 Autonomous Vehicles on Fuel Efficiency and Mobility of Traffic Networks

Ohio State University-Ozgenur Kavas-Torris, Mustafa Ridvan Cantas, Karina Meneses Cime, Bilin Aksun Guvenc, Levent Guvenc
  • Technical Paper
  • 2020-01-0137
To be published on 2020-04-14 by SAE International in United States
With the current drive of automotive and technology companies towards producing vehicles with higher levels of autonomy, it is inevitable that there will be an increasing number of SAE level L4-L5 autonomous vehicles (AVs) on roadways in the near future. The effect of this gradually increasing penetration of AVs on mobility, viewed as traffic congestion or traffic flow efficiency in this paper, and fuel efficiency improvement for the individual AV and for the whole road network with a mixed traffic of AVs and non-AVs is currently not well known. Microscopic traffic simulators that simulate realistic traffic flow are crucial in studying, understanding and evaluating the possible effects of having a higher number of autonomous vehicles (AVs) in traffic under realistic mixed traffic conditions including both autonomous and non-autonomous vehicles. In this paper, L4-L5 AVs with varying penetration rates in total traffic flow were simulated using the microscopic traffic simulator Vissim on urban, mixed and freeway roadways to study the effect of penetration rate on fuel consumption and efficiency of traffic flow. The roadways used in…
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VIRTUAL METHOD FOR ELECTRONIC STOP-START SIMULATION & VDV PREDICTION USING MODIFIED DISCRETE SIGNAL PROCESSING FOR SHORT TIME SIGNALS

FCA US LLC-Abhishek Paul, Jaspreet Kukreja, Syed Haider
HBM Prenscia-Joe Spadola
  • Technical Paper
  • 2020-01-1270
To be published on 2020-04-14 by SAE International in United States
Electronic Stop-Start (ESS) system automatically stops and restarts the engine to save energy, improve fuel consumption and reduce emissions when the vehicle is stationary during traffic lights, traffic jams etc. The start and stop events cause unwanted vibrations at the seat track which induce discomfort to the drivers and passengers in the vehicle. These events are very short duration events, usually taking less than a second. Time domain analysis can help in simulating this event but it is difficult to see modal interactions and root cause issues. Modal transient analysis also poses a limitation on defining frequency dependent stiffness and damping for multiple mounts. This leads to inaccuracy in capturing mount behavior at different frequencies. Most efficient way to simulate this event would be by frequency response analysis using modal superposition method. In order to do the same there is a major hurdle which is due to the nature of the signal being highly transient and of short duration, this event is difficult to be captured in frequency domain. Traditional FFT techniques used for domain…
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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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What If the Speed Had Been Less?Causation in Time Limited and Distance Limited Hazards

Road Accident Analysis-John Searle
  • Technical Paper
  • 2020-01-0881
To be published on 2020-04-14 by SAE International in United States
With a path intrusion incident, it is almost always the case that the collision would have been avoided if the pedestrian had not run out, or if the vehicle on the minor road had stopped, or so on. However should the other party be thought to have been travelling at an excessive speed, often the reconstructionist is asked to make a calculation of what whether the collision would, at some alternative speed say equal to the speed limit, still have occurred. In that way causation is addressed.The paper distinguishes between those hazards which are distance limited and those which are time limited, giving definitions of the two types. Distance limited hazards are deterministic, but time limited hazards have a probabilistic basis. This difference has important implications for causation.For a hazard at a fixed distance, there is a well known formula for calculating whether the collision would have been avoided at a slower alternative speed. However a time limited hazard often has no clear cut boundary between avoided/not avoided. According to the warning time during which…