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The initial stage investigation is the beginning 

step in the Exploratory Advanced Research 

(EAR) Program process for exploring ideas 

across traditional and nontraditional fields 

of research and stimulating new approaches 

to problem solving. The process starts with 

a literature review and reference scanning 

to get a better understanding of active 

research in a particular topic area. The EAR 

Program annually explores 20 or more topics.

The EAR Program literature and reference 

scanning activity provides background information that aims to increase researchers’ 

knowledge and understanding in a particular 

field or topic area, and contributes to the 

Federal Highway Administration

Initial Stage Reference Search

Contents

Reference Results: Literature and Researchers

Multilevel planning for semiautonomous vehicles in traffic scenarios based on 

separation maximization 3

Effectiveness and driver acceptance of a semiautonomous forward obstacle 

collision avoidance system 3

Shared steering control between a driver and an automation: Stability in the presence of 

driver behavior uncertainty 4

Sharing control with haptics: Seamless driver support from manual to automatic control 4

Highly automated driving, secondary task performance, and driver state 5

Control task substitution in semiautomated driving: Does it matter what aspects 

are automated? 6

Constraint-based planning and control for safe, semiautonomous operation vehicles 6

Internet-based shared control of vehicle steering when driver is under situation 

of tendency to accidents 7

Shared lateral control of a passenger car: Design on the basis of cybernetic driver model 

and H2-preview control 7

Optimal control with preview for lateral steering of a passenger car: Design and test 

on a driving simulator 8

Preface to the special section on human factors and automation in vehicles: Designing 

highly automated vehicles with the driver in mind 8

TOPIC

process of identifying priorities and opportunities for strategic investment in further 

research. The EAR Program reference librarian uses various selection criteria, such as 

authority, relevance, and timelines, and will 

scan information that has not been published, 

such as presentations, papers, and grant 

awards.

For more information about the Federal 

Highway Administration Research Library, 

visit http://www.fhwa.dot.gov/research/

library/index.cfm. For more information 

about the EAR Program, visit http://www.

fhwa.dot.gov/advancedresearch/about.

cfm.

Driver simulators to test shared controls, 

limited autonomy vehicle systems

Identification of the use of driver simulators for semiautonomous 

(or shared control) vehicle systems (2012–present), including related 

research from other modes of transportation (e.g., rail or aviation). 

Focus is on the research method and use of driving simulators.
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Haptic steering direction guidance for pedestrian–vehicle collision avoidance 9

An adaptive driver support system: User experiences and driving performance in a simulator 9

Reference Results: Organizations and Researchers

Modeling of a haptic shared control system: Application to lateral control of car 10

Driving simulator test bed 11

Reference Results: Workshop

SMC 2013 Workshop on shared control: Predict, Assist, and Assess Human Movements 12
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Reference Results: Literature and Researchers

Multilevel planning for semiautonomous vehicles in traffic scenarios 

based on separation maximization

Author(s): Kala, Rahul;1 Warwick, Kevin1

Year: 2013

Source: Journal of Intelligent and Robotic Systems, vol. 72, no. 3–4, pp. 559–590

Publisher: Springer Verlag

Author affiliation:

1

School of Systems Engineering, University of Reading, Whiteknights, Reading, Berkshire RG6 6AY, 

United Kingdom, https://www.reading.ac.uk/sse/contact/sse-contact.aspx 

The planning of semiautonomous vehicles in traffic scenarios is a relatively new problem 

that contributes toward the goal of making road travel by vehicles free of human drivers. 

An algorithm needs to ensure optimal real-time planning of multiple vehicles (moving in 

either direction along a road) in the presence of a complex obstacle network. Unlike other 

approaches, here the authors assume that speed lanes are not present and that different 

lanes do not need to be maintained for inbound and outbound traffic. The authors’ basic 

hypothesis is to carry forward the planning task to ensure that a sufficient distance is 

maintained by each vehicle from all other vehicles, obstacles, and road boundaries. 

The authors present a four-layer planning algorithm that consists of road selection 

(for selecting the individual roads of traversal to reach the goal), pathway selection 

(a strategy to avoid or overtake obstacles, road diversions, and other blockages), pathway 

distribution (to select the position of a vehicle at every instance of time in a pathway), 

and trajectory generation (for generating a curve that is smooth enough to allow for 

the maximum possible speed). Cooperation among vehicles is handled separately at the 

different levels, the aim being to maximize the separation between vehicles. Simulated 

results exhibit behaviors of smooth, efficient, and safe driving of vehicles in multiple 

scenarios, along with typical vehicle behaviors including following and overtaking.

Effectiveness and driver acceptance of a semiautonomous forward 

obstacle collision avoidance system

Author(s): Itoh, Makoto;1

 Horikome, Tatsuya;2 Inagaki, Toshiyuki1

Year: 2013

Source: Applied Ergonomics, vol. 44, no. 5, pp. 756–763

Publisher: Elsevier

Author affiliations:

1

Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki 305–8573, 

Japan, http://www.sie.tsukuba.ac.jp/english/ 2

Isuzu Advanced Engineering Center LTD, Fujisawa, Kanagawa, Japan, http://www.isuzu.co.jp/world/

index.html 

The authors propose a semiautonomous collision avoidance system for the prevention of 

collisions among vehicles and pedestrians and objects on a road. The system is designed 

to be compatible with the human-centered automation principle, that is, the decision 

to perform a maneuver to avoid a collision is made by the driver. The system, however, 

is partly autonomous in that it turns the steering wheel independently when the driver 

applies only the brake, indicating his or her intent to avoid the obstacle. With a medium-
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fidelity driving simulator, the authors conducted an experiment to investigate the 

effectiveness of this system for improving safety in emergency situations, as well as its 

acceptance by drivers. The results indicate that the system effectively improves safety in 

emergency situations, and the semiautonomous characteristic of the system was found 

to be acceptable to drivers.

Shared steering control between a driver and an automation: Stability 

in the presence of driver behavior uncertainty

Author(s): Saleh, Louay;1 Chevrel, Philippe;2 Claveau, Fabien;2 Lafay, Jean-François;2 Mars, Franck2

Year: 2013

Source: IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 2, pp. 974–983

Publisher: IEEE

Author affiliation:

1

Higher Institute of Applied Sciences and Technology, Damascus 31983, Syria, http://www.hiast.edu.sy/en 

2

IRCCyN, Institut de Recherche en Communications et Cybernétique Nantes, Ecole Centrale de 

Nantes, Nantes F-44321, France, http://www.irccyn.ec-nantes.fr/?lang=en 

The authors present an advanced driver assistance system (ADAS) for lane-keeping, 

together with an analysis of its performance and stability with respect to variations in 

driver behavior. The automotive ADAS as proposed is designed to share control of the 

steering wheel with the driver in the best possible way. Its development was derived from 

an H2-preview optimization control problem, which is based on a global driver–vehicle–

road (DVR) system. The DVR model makes use of a cybernetic driver model to take into 

account any driver–vehicle interactions. Such a formulation allows for (1) consideration 

of driver-assistance–cooperation criteria in the control synthesis, (2) improvement of the 

performance of the assistance as a cooperative copilot, and (3) analysis of the stability 

of the whole system in the presence of driver model uncertainty. The results have been 

experimentally validated with one participant using a fixed-base driving simulator. The 

developed assistance system improved lane-keeping performance and reduced the risk 

of a lane-departure accident. Good results were obtained by using several criteria for 

human–machine cooperation. Poor stability situations were successfully avoided due to 

the robustness of the whole system, in spite of a large range of driver model uncertainty.

Sharing control with haptics: Seamless driver support from 

manual to automatic control

Author(s): Mulder, Mark;1 Abbink, David A.;1 Boer, Erwin R.1, 2

Year: 2012

Source: Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 54, 

no. 5, pp. 786–798

Publisher: SAGE Publications, Inc. 

Author affiliations:

1

Delft University of Technology, 2629 HS Delft, Netherlands, http://www.tudelft.nl/en/ 

2

Entropy Control, Inc., La Jolla, CA 92037, United States 

The authors investigated haptic shared control as a human–machine interface that can 

intuitively share control between drivers and an automatic controller for curve negotiation. 

As long as automation systems are not fully reliable, a role remains for the driver to 

be vigilant to the system and the environment to catch any automation errors. The 
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conventional binary switches between supervisory and manual control have many known 

issues, and haptic shared control is a promising alternative. A total of 42 respondents of 

varying ages and driving experience participated in a driving experiment in a fixed-base 

simulator, in which curve negotiation behavior during shared control was compared with 

curve negotiation behavior during manual control, as well as to three haptic tunings of 

an automatic controller without driver intervention. Under the experimental conditions 

studied, the main beneficial effect of haptic shared control compared with manual control 

was that less control activity (16 percent in steering wheel reversal rate, 15 percent in 

standard deviation of steering wheel angle) was needed for realizing an improved safety 

performance (e.g., 11 percent in peak lateral error). Full automation removed the need 

for any human control activity and improved safety performance (e.g., 35 percent in 

peak lateral error) but put the human in a supervisory position. The authors concluded 

that haptic shared control kept the driver in the loop with enhanced performance at 

reduced control activity, mitigating the known issues that plague full automation. Haptic 

support for vehicular control ultimately seeks to intuitively combine human intelligence 

and creativity with the benefits of automation systems. 

Highly automated driving, secondary task performance, 

and driver state

Author(s): Merat, Natasha;1 Jamson, A. Hamish;1 Lai, Frank C. H.;1 Carsten, Oliver1

Year: 2012

Source: Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 54, 

no. 5, pp. 762–771

Publisher: SAGE Publications, Inc. 

Author affiliation:

1

Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, United Kingdom, 

http://www.its.leeds.ac.uk/ 

The authors conducted a driving simulator study, which compared the effect of changes 

in workload on performance in manual and highly automated driving. Changes in driver 

state were also observed by examining variations in blink patterns. With the addition of 

a greater number of advanced driver assistance systems in vehicles, the driver’s role is 

likely to alter in the future from an operator in manual driving to a supervisor of highly 

automated cars. Understanding the implications of such advancements on drivers and 

road safety is important. A total of 50 participants were recruited for this study and drove 

the simulator in both manual and highly automated modes. In addition to comparing 

the effect of adjustments in driving-related workload on performance, the authors 

also investigated the effect of a secondary Twenty Questions task. In the absence of 

the secondary task, drivers’ responses to critical incidents were similar in manual and 

highly automated driving conditions. The worst performance was observed when drivers 

were required to regain control of driving in the automated mode while distracted by 

the secondary task. Blink frequency patterns were more consistent for manual than 

automated driving but were generally suppressed during conditions of high workload. 

Highly automated driving did not have a deleterious effect on driver performance when 

attention was not diverted to the distracting secondary task. As the number of systems 

implemented in cars increases, an understanding of the implications of such automation 

on drivers’ situation awareness, workload, and ability to remain engaged with the driving 

task is important. 
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Control task substitution in semiautomated driving: Does it matter 

what aspects are automated?

Author(s): Carsten, Oliver;1 Lai, Frank C. H.;1 Barnard, Yvonne;1 Jamson, A. Hamish;1 Merat, Natasha1

Year: 2012

Source: Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 54, 

no. 5, pp. 747–761

Publisher: SAGE Publications, Inc. 

Author affiliation:

1

Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, United Kingdom, 

http://www.its.leeds.ac.uk/ 

The authors designed this study to show how driver attention to the road scene and 

engagement of a choice of secondary tasks are affected by the level of automation 

provided to assist or take over the basic task of vehicle control. The authors also 

designed the study to investigate the difference between support in longitudinal control 

and support in lateral control. There is comparatively little literature on the implications 

of automation for drivers’ engagement in the driving task and for their willingness to 

engage in nondriving-related activities. The authors conducted a study on a high-level 

driving simulator in which drivers experienced three levels of automation: manual driving; 

semiautomated driving, with either longitudinal or lateral control provided; and highly 

automated driving, with both longitudinal and lateral control provided. Drivers were free 

to pay attention to the roadway and traffic or to engage in a range of entertainment 

and grooming tasks. Engagement in the nondriving tasks increased from manual to 

semiautomated driving and increased further with highly automated driving. There were 

substantial differences in attention to the road and traffic between the two types of 

semiautomated driving. The literature on automation and the various task analyses of 

driving do not currently help to explain the effects that were found. Lateral support and 

longitudinal support may be the same in terms of levels of automation but appear to be 

regarded rather differently by drivers. 

Constraint-based planning and control for safe, semiautonomous 

operation vehicles

Author(s): Anderson, Sterling J.;1 Karumanchi, Sisir B.;1 Iagnemma, Karl1

Year: 2012

Source: 2012 IEEE Intelligent Vehicles Symposium (IV)

Publisher: IEEE

Author affiliation:

1

Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, 

United States, http://meche.mit.edu/ 

The authors present a new approach to semiautonomous vehicle hazard avoidance 

and stability control, based on the design and selective enforcement of constraints. 

This differs from traditional approaches that rely on the planning and tracking of paths. 

This emphasis on constraints facilitates “minimally invasive” control for human–machine 

systems: Instead of forcing a human operator to follow an automation-determined path, 

the constraint-based approach identifies safe homotopies and allows the operator to 

navigate freely within them, introducing control action only as necessary to ensure that the 

vehicle does not violate safety constraints. The method evaluates candidate homotopies 

based on “restrictiveness,” rather than on traditional measures of path goodness, and 
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designs and enforces requisite constraints on the human’s control commands to ensure 

that the vehicle never leaves the controllable subset of a desired homotopy. Identification 

of these homotopic classes in off-road environments is performed by using geometric 

constructs. The goodness of competing homotopies and their associated constraints 

is then characterized by using geometric heuristics. Finally, input limits satisfying 

homotopy and vehicle dynamic constraints are enforced by using threat-based feedback 

mechanisms to ensure that the vehicle avoids collisions and instability while preserving 

the human operator’s situational awareness and mental models. The methods developed 

in this work are shown in simulation and experimentally demonstrated in safe, high-speed 

teleoperation of an unmanned ground vehicle.

Internet-based shared control of vehicle steering when driver is under 

situation of tendency to accidents

Author(s): Zhong, Ming-En;1 Wu, Ping-Dong;2 Peng, Jun-Qiang3 

Year: 2012 

Source: Materials Science Forum, vol. 704–705, pp. 650–656

Publisher: Trans Tech Publications, Inc. 

Author affiliations:

1

Department of Mechanical Engineering, Xiamen University of Technology, Xiamen, China,

http://english.xmut.edu.cn/ 2

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China, 

http://english.bit.edu.cn/AboutBIT/officesschools/SchoolsDepartments/78021.htm 3

School of Mechanical and Electronic Engineering, Tianjin Polytechnic University, Tianjin, China,

http://www.csc.edu.cn/laihua/universitydetailen.aspx?collegeId=268 

Probability of traffic accidents grows when the driver’s environment has a tendency to 

cause accidents. The authors introduce a new vehicle model under Internet-based shared 

control technology, modeling toward the Internet-based shared control of the steering 

system. The authors simulated influence of the network transmission delay on the steering 

performance and created a closed-loop control circuit model. The authors put forward a 

systematic controller algorithm, the input of which gains range from the viewpoint of the 

sufficient condition for delay-dependent robust stability and steady-state error and design, 

and shows a dynamic, self-switching, delay-dependent robust controller. Simulation and 

experimental results show the validity of the proposed method.

Shared lateral control of a passenger car: Design on the basis of 

cybernetic driver model and H2-preview control

Author(s): Saleh, Louay;1 Chevrel, Philippe;1 Claveau, Fabien;1 Lafay, Jean-François;1 Mars, Franck1

Year: 2012

Source: Journal Européen des Systèmes Automatisés, vol. 46, no. 4–5, pp. 535–557

Publisher: Lavoisier 

Author affiliation:

1

IRCCyN, Institut de Recherche en Communications et Cybernétique Nantes, Ecole Centrale de Nantes, 

Nantes F-44321, France, http://www.irccyn.ec-nantes.fr/?lang=en 

The authors propose a cybernetic driver model that is able to perform lateral control. 

On the basis of this model, the authors designed an active assistance function that 

helps the driver in real time for lane-keeping. The device applies an additional torque 
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to the steering column in a continuous way, which achieves a shared lateral control with 

the driver. The driver model has been identified from experimental data collected on a 

fixed-base driving simulator. The designed control law takes advantage of the predictive 

capabilities of the driver model. The synthesis of this “electronic copilot” was performed 

by stating an H2 optimization problem with preview on the overall driver–vehicle–road 

system. Last, the authors evaluated the quality of the proposed shared steering control 

in terms of performance (quality of lane-keeping) and driver-assistance interaction 

coherence, which may guarantee its acceptability.

Optimal control with preview for lateral steering of a passenger car: 

Design and test on a driving simulator

Author(s): Saleh, Louay;1 Chevrel, Philippe;1 Lafay, Jean-François1 

Year: 2012 

Source: Lecture Notes in Control and Information Sciences, vol. 423, pp. 173–185

Publisher: Springer Verlag 

Author affiliation:

1

IRCCyN, Institut de Recherche en Communications et Cybernétique de Nantes, Ecole Centrale de 

Nantes, Nantes F-44321, France, http://www.irccyn.ec-nantes.fr/?lang=en 

The authors studied the characteristics of the optimal preview control for lateral steering 

of a passenger vehicle. Such control is known to guarantee improved performance when 

the near future of the exogenous signal—here, the road curvature—is known. The synthesis 

is performed in continuous time and leads to a two-degrees-of-freedom feedback and 

feedforward controller, whose feedforward part is a finite impulse response filter. The 

controller has been implemented on the SCANeRTM Driving Simulator, available at IRCCyN, 

whose steering column is electrically powered. The authors propose a methodology for 

choosing the weighting matrices in the quadratic index and the preview time and also 

discuss the obtained experimental results.

Preface to the special section on human factors and automation in 

vehicles: Designing highly automated vehicles with the driver in mind

Author(s): Merat, Natasha;1 Lee, John D.2 

Year: 2012

Source: Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 54, 

no. 5, pp. 681–686

Publisher: SAGE Publications Inc. 

Author affiliations:

1

University of Leeds, Leeds LS2 9JT, United Kingdom, http://www.leeds.ac.uk/ 

2

College of Engineering, University of Wisconsin–Madison, Madison, WI 53706, United States,

http://www.engr.wisc.edu/ 

In this special section, the authors bring together diverse research regarding driver 

interaction with advanced automotive technology to guide the design of increasingly 

automated vehicles. Rapidly evolving vehicle automation will likely change cars and trucks 

even more in the next 5 years than the preceding 50, radically redefining what it means 

to drive. This special section includes 10 articles from European and North American 

researchers, who report on simulator and naturalistic driving studies. Little research 

has considered the consequences of fully automated driving, with most focusing on 
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lane-keeping and speed-control systems individually. The studies reveal two underlying 

design philosophies: automate driving versus support driving. Results of several studies, 

consistent with previous research in other domains, suggest that the automate philosophy 

can delay driver responses to incidents in which the driver has to intervene and take control 

from the automation. Understanding of how to orchestrate the transfer or sharing of control 

between the system and the driver, particularly in critical incidents, emerges as a central 

challenge. Designers should not assume that automation can substitute seamlessly for a 

human driver, nor can they assume that the driver can safely accommodate the limitations 

of automation. Designers, policy makers, and researchers must give careful consideration 

to what role the person should have in highly automated vehicles and how to support the 

driver if the driver is to be responsible for vehicle control. As in other domains, driving safety 

increasingly depends on the combined performance of the human and automation, and 

successful designs will depend on recognizing and supporting the new roles of the driver.

Haptic steering direction guidance for pedestrian–vehicle 

collision avoidance

Author(s): Itoh, Makoto;1 Inagaki, Toshiyuki;1 Tanaka, Hiroto2

Year: 2012

Source: Conference Proceedings, 2012 IEEE International Conference on Systems, 

Man and Cybernetics, pp. 3327–3332

Publisher: IEEE 

Author affiliations:

1

Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Japan,

http://www.sie.tsukuba.ac.jp/english 2

Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan, 

http://www.sie.tsukuba.ac.jp/english 

The authors discuss an assistance system that momentarily adds tiny torque to the steering 

wheel to help the driver choose the direction for avoiding collision with a pedestrian. To 

investigate the effectiveness of the system, the authors conducted an experiment with 

a medium-fidelity driving simulator. The results of the experiment showed that there 

existed situations where the system was effective to enhance the driver’s appropriate 

selection of steering direction. In addition, the system reduced driver reaction time 

significantly; however, there were cases in which the driver completely disagreed with 

the system’s proposal. To make such a system acceptable to drivers, drivers’ ways of 

choosing a direction should be taken into account.

An adaptive driver support system: User experiences and driving 

performance in a simulator

Author(s): Dijksterhuis, Chris;1 Stuiver, Arjan;1 Mulder, Ben;1 Brookhuis, Karel A.;1 De Waard, Dick1

Year: 2012

Source: Human Factors: The Journal of the Human Factors and Ergonomics Society, vol. 54, 

no. 5, pp. 772–785

Publisher: SAGE Publications, Inc. 

Author affiliation:

1

University of Groningen, Groningen 9712 TS, Netherlands, http://www.rug.nl/ 

The aim of this study was to test the implementation of an adaptive driver support 

system. Providing support might not always be desirable from a safety perspective, as 
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support may lead to problems related to a human operator being out of the loop. In 

contrast, adaptive support systems are designed to keep the operator in the loop as 

much as possible by providing support only when necessary. A total of 31 experienced 

drivers were exposed to three modes of lane-keeping support: nonadaptive, adaptive, 

and no-support. Support involved continuously updated lateral position feedback 

shown on a head-up display. When adaptive, support was triggered by performancebased indications of effort investment. Narrowing lane width and increasing density of 

oncoming traffic served to increase steering demand, and speed was fixed in all conditions 

to prevent any compensatory speed reactions. Participants preferred the adaptive 

support mode mainly as a warning signal and tended to ignore nonadaptive feedback. 

Furthermore, driving behavior was improved by adaptive support in that participants 

drove more centrally, displayed less lateral variation, and drove less outside the lane’s 

delineation when support was in the adaptive mode compared with both the no-support 

mode and the nonadaptive support mode. A human operator is likely to use machinetriggered adaptations as an indication that thresholds have been passed, regardless of 

the support that is initiated. Therefore, supporting only the sensory processing stage of 

the human-information processing system with adaptive automation may not feasible. 

These conclusions are relevant for designing adaptive driver support systems.

Reference Results: organizations and Researchers

Modeling of a haptic shared control system: Application to lateral 

control of car

Research Institution: Delft University of Technology, Faculty of Aerospace Engineering, 

2628 CD Delft, Netherlands, http://www.lr.tudelft.nl/en 

Author: Mulder, Mark

Technical Contact: Abbink, David 

http://www.lr.tudelft.nl/en/organisation/departments/control-and-operations/control-and-simulation/

organisation/staff-members/mark-mulder/master-assignments/modeling-of-a-haptic-sharedcontrol-system/ 

The goal of this research is to determine a haptic shared control system that is based on 

models of human steering interaction. There is a need to determine, or assume, which 

sensor input to the control system is suitable for conversion into haptic guidance. With 

this sensor input, the controller determines the optimal angle for the steering wheel such 

that the vehicle is steered toward its desired reference state. Based on the known steering 

wheel dynamics and assumed (static) neuromuscular properties of the human driver, the 

optimal angle yields a guidance force.

Proposed Haptic Shared Control System Architecture

Project Outline

Preliminary phase

1. Create research literature review on lateral control of cars: Which feedback 

variables do humans use?

2. Become familiarized with the control models that describe the human–machine 

interaction (MATLAB®).
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3. Develop a simulation model with which to test different controllers.

4. Carry out simulations with model to test the influence of model parameters 

(from the controller, the steering wheel, and the neuromuscular system) on 

performance and control activity (MATLAB).

5. Present results to the Control and Simulation Group.

Final phase

1. Design a driving simulator experiment to test the controller in a more 

realistic setting based on the most promising controller parameters and 

parameter values.

2. Analyze the results of the experiment.

3. Write a report in the form of a paper and appendices.

4. Present final results.

Driving simulator test bed

Research Institution: University of Southern California, Ming Hsieh Department of Electrical 

Engineering, Ming Hsieh Institute, http://mhi.usc.edu/

Contact: Ioannou, Petros

http://mhi.usc.edu/about/news/2013/04/11/mhi-supports-driving-simulator-test-bed/

The driving simulator project will enable University of Southern California (USC) 

researchers to carry out studies on a variety of topics, including human factors, vehicle 

dynamics and interaction with drivers, impact on drivers of sensors and warnings, impact 

on drivers of different control techniques and automation, driver assistance systems, and 

information systems. The simulator developed for this research is improved by the use of 

computer science techniques to develop additional driving scenarios and visualizations. 

The driving simulator will be used for the research topics mentioned above, as well as for 

individual-directed research studies and projects. The simulator will be accessible to all 

members of the USC Electrical Engineering Department and (with permission and on a 

case-by-case basis) to students and researchers outside the department.

Activity 1: Safety Evaluation of Advanced Driver Attention Systems (ADAS)

The analysis of ADAS using an actual vehicle could be costly and dangerous, as subject 

drivers cannot ethically be subjected to dangerous driving situations; as a result, the use 

of driving simulators to assess the effectiveness of these systems is crucial. In this activity 

the researchers are developing vehicle-following and lane-changing scenarios in which 

different drivers will operate in conjunction with the Institute’s version of ADAS, which 

will provide warnings regarding unsafe situations as well as directions as to when to 

change lanes or merge into traffic. The drivers’ responses will be assessed for compliance 

and safety and used to modify and improve ADAS.

Activity 2: Truck Driving in a Platoon

Under this activity, the researchers plan to develop a driving environment that will be used 

to perform human factors tests associated with trucks in a platoon. In such situations they 

will study how truck drivers respond to joining and exiting a platoon. They will start with 
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manually driven trucks and progress to trucks that can be driven in the automated mode; 

in such cases, the driver response in switching between the manual and automated mode 

will be studied using the simulator. 

Reference Results: workshop

SMC 2013 Workshop on shared control: Predict, Assist, and 

Assess Human Movements

Session Chair: Honghai Liu1

Keynote Speaker: Robert Riener2

Year: 2013

Meeting: IEEE SMC 2013: International Conference on Systems, Man, and Cybernetics, 

Manchester M60 2DS, United Kingdom, http://www.smc2013.org/programfc45.html?cid=361

Sponsor: IEEE

Presenter Affiliation:

1

School of Computing, University of Portsmouth, Portsmouth P01 2UP, United Kingdom,

http://www.port.ac.uk/school-of-computing/staff/professor-honghai-liu.html 2

Sensory-Motor Systems Laboratory, ETH Zürich, Zentrum, 8092 Zurich, Switzerland,

http://www.sms.hest.ethz.ch/

Mechatronic systems and their clinical applications play an increasingly important role in 

neuroscience and neurorehabilitation. Novel technical systems are being developed—or 

are, in some cases, already in regular clinical use—within the different therapeutic phases 

of this field of research, which range from diagnostic neuroimaging via neurosurgical 

technologies to therapeutic treatments in the acute, subacute, and chronic stages of 

neurorehabilitation. The presenter focused on different types of interaction technologies 

that will allow future rehabilitation robotic systems to (1) detect motion intention that will 

support patients in an intuitive way during therapy, (2) assist patients as needed during 

the performed patient movements of a therapy session, and (3) quantitatively assess the 

motor functions of patients during and after a therapy session. As part of this research, 

one way to engage human subjects in a movement task is to let the assisting robotic 

system estimate the subject’s movement intention and support the subject continuously 

during his freely chosen task rather than imposing upon the subject a predefined robotic 

action. The researchers developed a method for predicting targets of human reaching 

motions that uses different sensing technologies, such as electroencephalography, 

electrooculography, camera-based eye tracking, electromyography, hand position, and 

an estimate of the subject’s personal preferences. Supervised machine learning was used 

to make predictions at different points in time (before and during the motion), with each 

individual sensor and with various combinations of sensors. Furthermore, during the 

movement therapy, audiovisual displays and rendering methods were used to present 

a virtual environment to the subject and allow the subject to perform games, virtual 

functional tasks, or virtual activities of daily living. For purposes of this research, the human 

subjects were integrated into the robotic system not only to provide a biomechanical 

view but also to monitor psychophysiological effects. Psychophysiological integration 

involves recording and controlling the subject’s physiological reactions, so that the 

subject receives appropriate stimuli and is challenged in a moderate but engaging way 

without causing the subject undue stress or harm. Last, assessment routines integrated 
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into the robotic training can enhance patient diagnosis, quantify the progress of therapy, 

identify patient impairment level, and adapt a patient therapy program to optimize 

therapy outcomes, which will eventually contribute to an optimization of a patient’s 

rehabilitation. Different robot-assisted assessment routines were presented that have 

been implemented into different training devices that allow objective and quantitative 

evaluation of biomechanical functions in patients with neurological deficits (e.g., deficits 

that have occurred as a result spinal cord injury or stroke). This talk presented several 

virtual reality display methods and psychophysiological recording and assessment 

strategies that have been implemented and tested on different rehabilitation devices, 

such as the actuated gait orthosis Lokomat® and the arm therapy device ARMin. 
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