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Technical Paper

Analysis and Mathematical Modeling of Car-Following Behavior of Automated Vehicles for Safety Evaluation

2019-04-02
2019-01-0142
With the emergence of Driving Automation Systems (SAE levels 1-5), the necessity arises for methods of evaluating these systems. However, these systems are much more challenging to evaluate than traditional safety features (SAE level 0). This is because an understanding of the Driving Automation system’s response in all possible scenarios is desired, but prohibitive to comprehensively test. Hence, this paper attempts to evaluate one such system, by modeling its behavior. The model generated parameters not only allow for objective comparison between vehicles, but also provide a more complete understanding of the system. The model can also be used to extrapolate results by simulating other scenarios without the need for conducting more tests. In this paper, low speed automated driving (also known as Traffic Jam Assist (TJA)) is studied. This study focused on the longitudinal behavior of automated vehicles while following a lead vehicle (LV) in traffic jam scenarios.
Technical Paper

Cooperative Collision Avoidance in a Connected Vehicle Environment

2019-04-02
2019-01-0488
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.
Technical Paper

Development of Virtual Fuel Economy Trend Evaluation Process

2019-04-02
2019-01-0510
With the advancement of the autonomous vehicle development, the different possibilities of improving fuel economy have increased significantly by changing the driver or powertrain response under different traffic conditions. Development of new fuel-efficient driving strategies requires extensive experiments and simulations in traffic. In this paper, a fuel efficiency simulator environment with existing simulator software such as Simulink, Vissim, Sumo, and CarSim is developed in order to reduce the overall effort required for developing new fuel-efficient algorithms. The simulation environment is created by combining a mid-sized sedan MATLAB-Simulink powertrain model with a realistic microscopic traffic simulation program. To simulate the traffic realistically, real roads from urban and highway sections are modeled in the simulator with different traffic densities.
Technical Paper

Effect of Traffic, Road and Weather Information on PHEV Energy Management

2011-09-11
2011-24-0162
Energy management plays a key role in achieving higher fuel economy for plug-in hybrid electric vehicle (PHEV) technology; the state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining the fuel consumed. The energy management algorithm should be designed to meet all driving scenarios while achieving the best possible fuel economy. The knowledge of the power requirement during a driving trip is necessary to achieve the best fuel economy results; performance of the energy management algorithm is closely related to the amount of information available in the form of road grade, velocity profiles, trip distance, weather characteristics and other exogenous factors. Intelligent transportation systems (ITS) allow vehicles to communicate with one another and the infrastructure to collect data about surrounding, and forecast the expected events, e.g., traffic condition, turns, road grade, and weather forecast.
Technical Paper

Ensuring Fuel Economy Performance of Commercial Vehicle Fleets Using Blockchain Technology

2019-04-02
2019-01-1078
In the past, research on blockchain technology has addressed security and privacy concerns within intelligent transportation systems for critical V2I and V2V communications that form the backbone of Internet of Vehicles. Within trucking industry, a recent trend has been observed towards the use of blockchain technology for operations. Industry stakeholders are particularly looking forward to refining status quo contract management and vehicle maintenance processes through blockchains. However, the use of blockchain technology for enhancing vehicle performance in fleets, especially while considering the fact that modern-day intelligent vehicles are prone to cyber security threats, is an area that has attracted less attention. In this paper, we demonstrate a case study that makes use of blockchains to securely optimize the fuel economy of fleets that do package pickup and delivery (P&D) in urban areas.
Technical Paper

Mission-based Design Space Exploration for Powertrain Electrification of Series Plugin Hybrid Electric Delivery Truck

2018-04-03
2018-01-1027
Hybrid electric vehicles (HEV) are essential for reducing fuel consumption and emissions. However, when analyzing different segments of the transportation industry, for example, public transportation or different sizes of delivery trucks and how the HEV are used, it is clear that one powertrain may not be optimal in all situations. Choosing a hybrid powertrain architecture and proper component sizes for different applications is an important task to find the optimal trade-off between fuel economy, drivability, and vehicle cost. However, exploring and evaluating all possible architectures and component sizes is a time-consuming task. A search algorithm, using Gaussian Processes, is proposed that simultaneously explores multiple architecture options, to identify the Pareto-optimal solutions.
Technical Paper

Multiple Rear-end Collisions in Freeway Traffic, Their Causes and Their Avoidance

1970-02-01
700085
The sensitivity factor, λ, of stimulus-response car following equations was computed, based on response times, τ, obtained from aerial survey data. Vehicles of a platoon are investigated as they approach, proceed through, and leave behind a kinematic disturbance, and an inherent local and asymptotic instability is discovered. Aerial survey data is used in a numerical example to demonstrate how multiple rear-end collisions can be triggered by one vehicle. A driver aid system, informing drivers about the differential velocity between lead and following vehicles, could improve stability, although the final answer appears to lie in automated or semi-automated longitudinal control systems.
Technical Paper

Robust Path Tracking Control for Autonomous Heavy Vehicles

2018-04-03
2018-01-1082
With high maneuverability and heavy-duty load capacity, articulated steer vehicles (ASV) are widely used in construction, forestry and mining sectors. However, the steering process of ASV is much different from wheeled steer vehicles and tractor-trailer vehicles. Unsuitable steering control in path following could easily give rise to the “snaking” behaviour, which greatly reduces the safety and stability of ASV. In order to achieve precise control for ASV, a novel path tracking control method is proposed by virtual terrain field (VTF) method. A virtual U-shaped terrain field is assumed to exist along the reference path. The virtual terrain altitude depends on the lateral error, heading error, preview distance and road curvature. If the vehicle deviates from the reference line, it will be pulled back to the lowest position under the influence of additional lateral tire forces which are caused by the virtual banked road.
Technical Paper

The Highway Research Laboratory of Ohio's Transportation Research Center

1970-02-01
700524
This paper presents some of the technical considerations that underlie the development of the master plan and the establishment of design specifications for Ohio's Highway Research Laboratory. It describes the overall features of the master plan and discusses some of the critical design features as these relate to the various tracks and other field facilities. The development of the master plan was guided by a study of the layout of existing proving grounds and by the experience gained over the years in their operations. It was guided furthermore by a set of principles relating to operational considerations, considerations of flexibility in the layout, land utilization, safety, capacity, and cost. Finally, it was guided by an indication of future research and development needs as expressed by researchers and potential sponsors in both government and industry.
Book

The Road to the Top is Not on the Map: Conversations with Top Women of the Automotive Industry

2019-10-01
Carla Bailo, CEO of the Center for Automotive Research, and Terry Barclay, CEO of Inforum, bring together over 30 of the most influential women in the automotive industry to share their insight and advice. From suppliers to OEMs, they hail from every corner of the industry. Readers will learn how to take charge of their own careers by understanding the experiences these professionals. Topics include: • Work-Life Integration - How can you be whole at home, at work, and in the community? • Education and Lifelong Learning - Do you really need a graduate degree? • Mentor and Sponsor Relationships - How do you find mentors and sponsors and form productive relationships with them? • Career Challenges - How do you evaluate when to take career risks? How do you say yes when all the boxes aren't checked? • Resilience - Where do you find the internal fortitude to keep going? • Personal Satisfaction - What do these leaders find most joyful about their careers?
Technical Paper

Use of Hardware in the Loop (HIL) Simulation for Developing Connected Autonomous Vehicle (CAV) Applications

2019-04-02
2019-01-1063
Many smart cities and car manufacturers have been investing in Vehicle to Infrastructure (V2I) applications by integrating the Dedicated Short-Range Communication (DSRC) technology to improve the fuel economy, safety, and ride comfort for the end users. For example, Columbus, OH, USA is placing DSRC Road Side Units (RSU) to the traffic lights which will publish traffic light Signal Phase and Timing (SPaT) information. With DSRC On Board Unit (OBU) equipped vehicles, people will start benefiting from this technology. In this paper, to accelerate the V2I application development for Connected and Autonomous Vehicles (CAV), a Hardware in the Loop (HIL) simulator with DSRC RSU and OBU is presented. The developed HIL simulator environment is employed to implement, develop and evaluate V2I connected vehicle applications in a fast, safe and cost-effective manner.
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