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As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC.

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

A gasoline engine with an electronically controlled fuel injection system has substantially better fuel economy and lower emissions than a carburetted engine. In general, the stability of engine operation is improved with fuel injector, but the stability of engine operation at idle is not improved compared with a carburetted gasoline engine. In addition, the increase in time that an engine is at idle due to traffic congestion has an effect on the engine stability and vehicle reliability. Therefore, in this research, we will study the influence of fuel injection timing, spark timing, dwell angle, and air-fuel ratio on engine stability at idle.

Automating road vehicle control can increase the range and reliability of dynamic testing. Some tests, for instance, specify precise steering inputs which human test drivers are only able to approximate, adding uncertainty to the test results. An automated steering system has been developed which is capable of removing these limitations. This system enables any production car or light truck to follow a user-defined path, using global position feedback, or to perform specific steering sequences with excellent repeatability. The system adapts itself to a given vehicle s handling characteristics, and it can be installed and uninstalled quickly without damage or permanent modification to the vehicle.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

During Phase VI of the National Highway Traffic Safety Administration's (NHTSA) Light Vehicle Rollover Research Program, three of the twenty-six light vehicles tested exhibited significant response asymmetries with respect to left versus right steer maneuvers. This paper investigates possible vehicle asymmetric characteristics and unintended inputs that may cause vehicle asymmetric response. An analysis of the field test data, results from suspension and steering parameter measurements, and a summary of a computer simulation study are also given.

In an earlier paper, some of the authors of this paper pointed out some of the difficulties involved in event based engine control. In particular it was shown that event based (or constant crank angle) sampling is very difficult to carry out without running into aliasing and sensor signal averaging problems. This leads to errors in reading the air mass flow related sensors and hence inaccurate air/fuel ratio control. The purpose of this paper is first to demonstrate that the conjectures about the operator input spectrum in a vehicle do actually obtain during vehicle operation in realistic road situations. A second purpose is to extend earlier modelling work and to present an approximate physical method of predicting the level of engine pumping fluctuations at any given operating point. The physical method given is based on a modification of the Mean Value Engine Model (MVEM) of a Spark Ignition (SI) engine presented previously.

As vehicle development timelines continue to shorten, it is necessary for the full vehicle NVH engineer to be able to predict performance without actual prototypes. There has been significant advancement in the accuracy of finite element modeling techniques of trimmed bodies; however accuracy is still low in the road noise mid frequency range from 150-400Hz. Also, calculation times for these frequencies are long, with very large results files in some cases. To alleviate these limitations, a Hybrid approach has been used, where a finite element suspension and drive train model is coupled with a test based Frequency Response Function (FRF) model of the trimmed body. The predicted road noise level was compared to actual vehicle tests and exhibited excellent correlation.

The airport is but a part of the transportation system of an urban area. While access to the airport is a significant problem faced by millions of travelers and affects a wider spectrum of our population each year, it does not yet command a sufficiently large urban transportation market, as compared to the urban commuter market, to justify the construction of airport-access-only, ground-transportation systems. Dual-mode vehicle systems that combine the advantages of both automobile and transit systems are investigated as potential solutions to the airport access problem. These are particularly interesting because they also show promise of a major solution to the general urban transportation problem. Special consideration of an airport access system as a demonstration site for new urban transportation projects is presented.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

Platooning heavy-duty trucks decreases aerodynamic drag for following trucks, reducing energy consumption, and increasing both range and mileage. Previous platooning experimentation has demonstrated fuel economy benefits in two-, three-, and four-truck configurations. However, exogenous variables disturb the ability of these platoons to maintain the desired formation, causing an accordion effect within the platoon and reducing energy benefits via acceleration/deceleration events. This phenomenon is increasingly exacerbated as platoon size and road grade variations increase. The current work assesses how platoon size, road curvature, and road grade influence platoon energy efficiency. Fuel consumption rate is experimentally quantified for four heterogeneous Class 8 vehicles operating in standalone (baseline), two-, and four-truck platooning configurations to assess fuel consumption changes while driving through diverse road conditions.

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. Drafting allows following vehicles to increase fuel economy and save money on refueling, whether that be at the pump or at a charging station. However, autonomous solutions are still in infancy, and controller evaluation is an exciting challenge proposed to researchers. This work brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). Rather than utilize its emissions investigative benefits, the present work applies VSP to heterogeneous Class 8 Heavy-Duty truck platoons as a means of evaluating the efficacy of Cooperative Adaptive Cruise Control (CACC).

Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is seen as either a “pull” effect experienced by the following vehicles or a “push” effect experienced by the leader. The energy savings magnitude increases nonlinearly as headway (following distance) is reduced [1]. In efforts to maximize energy savings, cooperative adaptive cruise control (CACC) is utilized to maintain relatively short headways. However, when platooning is attempted in the real world, small transient accelerations caused by imperfect control result in observed energy savings being less than expected values. This study analyzes the performance of a recently developed nonlinear model predictive control (NMPC) platooning strategy over challenging terrain.

Due to aerodynamic drag reduction, vehicles may have significant energy savings while platooning in close succession. However, when circumstances force active deceleration to maintain the platoon, such as during vehicle cut-ins or grade changes, the aerodynamic efficiency benefits may be undermined by losses in kinetic energy. In this work, a theoretical relationship is derived to correlate the amount of active deceleration a vehicle experiences with energy efficiency. The derived relationship is leveraged to analyze platooning data from the last vehicle in a class 8 vehicle platoon. The data include both two- and four-truck platoons operating under nine different truck-to-truck gap control strategies. Using J1939 CAN data and GPS-estimated grade profiles, off-throttle data were isolated and longitudinal acceleration is estimated as a function of grade using Kalman filtering.

Future SAE Level 4 and Level 5 autonomous vehicles will require novel applications of localization, perception, control and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This paper concentrates on low speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of campus as an initial autonomous vehicle (AV) pilot test route for the deployment of low speed autonomous shuttles. This paper presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

With the advent of increasing autonomous vehicles on public roads, the safety of vulnerable road users such as pedestrians, cyclists, etc. has never been more important. These especially include Blind or Visually Impaired (BVI) pedestrians who face difficulty in making confident decisions in road crossings without the help of accessible pedestrian signals (APS). This paper addresses some of the safety measures that can be taken to improve and assess the safety of BVI pedestrians in a controlled environment like a BVI school campus where autonomous vehicles are operated. The majority of research on autonomous vehicle safety does not consider the edge cases of encounters with BVI pedestrians. Based on this motivation, requirements and characteristics of Non-BVI and BVI pedestrians have been stated along with the motion models used to predict their future movements. Existing tools based on Bayesian multi-model filters were used for pedestrian tracking and motion predictions.

Roundabout is a unique approach of managing traffic at intersections because it relies on driver’s instincts of safety. Roundabouts are considered safer than other ways of intersection traffic management due to low speed limits, smoother merging, and reduced fatal accidents. Despite their benefits and increasing usage, there is lack of clear understanding of the roundabouts, particularly due to scarcity of data and simulation models and the complexity of the structure. Real-time and offline traffic data recorded at a roundabout provides a basis for 1) identification of the safety issues, 2) understanding unexpected and risky driver behavior, 3) proposing potential mobility solutions, and 4) developing simulation models. The processed data may be used in controlling metered roundabouts, communicating with connected and automated vehicles (CAVs) etc. In this paper an approach to obtain useful traffic information from video feed data at a roundabout is presented.

Platooning has the potential to reduce greenhouse gas emissions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics of two- and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. For real world application and accurate return on investment for potential adopters, non-uniform platoons and the impacts of grade and disturbances on a platoon’s fuel economy must also be characterized. This study investigates the fuel economy of a heterogeneous four-truck platoon on a closed test track. Tests were run for one hour at a speed of 45 mph. The trucks used for this study are two 2015 Peterbilt 579’s with a Cummins ISX15 and a Paccar MX-13, and two 2009 Freightliner M915A5’s, one armored and the other unarmored. Many analysis methodologies were leveraged to describe and compare the fuel data, including lap-wise and track-segment analysis.

A two-truck platoon based on a prototype cooperative adaptive cruise control (CACC) system was tested on a closed test track in a variety of realistic traffic and transient operating scenarios - conditions that truck platoons are likely to face on real highways. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate, serving as proxies to evaluate the impact of aerodynamic drag reduction under constant-speed conditions. These measurements demonstrate the effects of: the presence of a multiple-passenger-vehicle pattern ahead of and adjacent to the platoon, cut-in and cut-out manoeuvres by other vehicles, transient traffic, the use of mismatched platooned vehicles (van trailer mixed with flatbed trailer), and the platoon following another truck with adaptive cruise control (ACC).