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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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Optimal Traffic Management In Urban Traffic Network Using PTV VISSIM And MATLAB SIMULINK

Univ of North Carolina Charlotte-Pouria Karimi Shahri
Univ. of North Carolina Charlotte-Amir H. Ghasemi
  • Technical Paper
  • 2020-01-0887
To be published on 2020-04-14 by SAE International in United States
This paper aims to develop a platform for integrating PTV VISSIM and MATLAB Simulink to design and analyze the flow of traffic in an urban traffic network. We model a non-signalized traffic network in VISSIM. From VISSIM, we take the inflow and outflow rates data and send them to the controller in MATLAB thought a VISSIM Component Object (COM) Interface. By employing an extremum seeking approach, an optimal velocity is determined and send back to the VISSM through a COM interface. Numerical simulation demonstrates the effectiveness of the platform for testing different traffic control approaches. {\bf Keywords:} Matlab-VISSIM integrated, traffic networks, model predictive control, exteremum seeking
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An Image Recognition Application Method for Vertical Movement of Vehicles

Ming Li
  • 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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Dyno-in-the-Loop: An Innovative Hardware-in-the-Loop Development and Testing Platform for Emerging Mobility Technologies

Oak Ridge National Laboratory-Zhiming Gao, Tim LaClair
University Of California Riverside-Guoyuan Wu, Dylan Brown, Zhouqiao Zhao, Peng Hao, Michael Todd, Kanok Boriboonsomsin, Matthew Barth
  • Technical Paper
  • 2020-01-1057
To be published on 2020-04-14 by SAE International in United States
Today’s transportation is quickly transforming with the advent of shared-mobility, vehicle electrification, connected vehicle technology, and vehicle automation. These technologies will not only affect our safety and mobility, but also our energy consumption, air pollution, and climate change. As a result, it is of unprecedented importance to understand the overall system impacts, as a result of introducing these emerging technologies and concepts. However, existing modeling tools are not able to properly capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. For example, it is quite challenging to calibrate state-of-the-art microscopic traffic simulators to properly model the behavior of automated vehicles or to address potential cyber-security issues in a Connected Vehicle (CV) environment. It is even more difficult to scale up the assessment on a larger spatial scale (e.g., statewide, nationwide) or to project these impacts over a longer temporal span. To address these gaps, we have developed a Dyno-in-the-Loop (DiL) development and testing approach which integrates a test vehicle, a chassis dynamometer, and high fidelity…
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A method of real-road simulations of heavy duty vehicle performance

University of Leeds-Jianbing Gao, Haibo Chen PhD, Junyan Chen MD, Kaushali Dave PhD
  • Technical Paper
  • 2020-01-0370
To be published on 2020-04-14 by SAE International in United States
Traffic and vehicle simulations are developed individually, however, vehicle performance optimization is one of the main targets of traffic management. Joint simulations of traffic and vehicle under real-road situations can reflect the semi-real-world performance of vehicles, with real road situations and traffic conditions being taken into considerations. This paper proposed a approach, which combined the traffic and vehicle simulations that were realized by SUMO and GT-Suite software, respectively. In the simulation, the real-road conditions were used, such as the road elevation and rolling resistance factor, hence, the simulation results were much more close to the real-road driving. The process of the real-road vehicle simulation is as following: 1) obtain the 2D real-road network; 2) integrate the road elevation into the 2D real-road network; 3) extract the targeted route for further simulation; 4) load the real-road network and traffic information into SUMO software; 5) input the traffic simulation results into GT-Suite software to finish the vehicle simulation. It should be noted that in the 3rd step, the crossways of other roads and the target one were…
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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 Berkeley-Fei Ye
  • 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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Characteristics of Transient NOx Emission of HEV under Real Road Driving

Anhui Jianghuai Automobile Group Corp.-Bo He
Anhui Jianghuai Automobile Group Gorp.-Shi Bo
  • Technical Paper
  • 2020-01-0380
To be published on 2020-04-14 by SAE International in United States
To meet the request of China National 6b emission regulations which will be officially implemented in China, firstly including the RDE emission test limits, the transient emissions on real road condition are paid more attention. Several non-plug-in hybrid light-duty gasoline vehicles (HEV) sold in the Chinese market were selected to study real road emissions employed fast response NOx analyzer from Cambustion Ltd. with a sampling frequency of 100Hz. The concentration of NOx emissions before and after the TWC (Three Way Catalyst) of the hybrid vehicle were also sampled and analyzed, and the working efficiency of the TWC in real road driving process was investigated. It is found that when the engine is at low-speed and heavy-load conditions, especially when fuel is injected after fuel cut, instantaneous spikes in tailpipe NOx emissions could be observed, which means that traffic positions such as crosswalks, speed bumps, high-speed entrances, traffic lights, would lead to higher NOx emissions. At the same time, emissions from PEMS were also recorded and compared with the results from fast response NOx analyzer. Obvious…
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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 Co-James Fishelson
Ford Motor Co Ltd-Adit Joshi
  • 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 Univ-Mustafa Ridvan Cantas, Karina Meneses Cime
Ohio State University-Ozgenur Kavas-Torris, 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…