The Use of a Steering Shaping Function to Improve 

Human Performance in By-Wire Vehicles 

by Susan G. Hill, Jason S. Metcalfe, and Kaleb McDowell 

ARL-TR-4387 March 2008 

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Army Research Laboratory 

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ARL-TR-4387 March 2008 

The Use of a Steering Shaping Function to Improve 

Human Performance in By-Wire Vehicles 

Susan G. Hill and Kaleb McDowell 

Human Research and Engineering Directorate, ARL 

Jason S. Metcalfe 

DCS1 Corporation 

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13. SUPPLEMENTARY NOTES 

J.S. Metcalfe (DCS) participated in this collaborative effort as a result of a U.S. Army Tank-Automotive Research Development and 

Engineering Center (TARDEC)-sponsored project. This work is a collaborative effort between TARDEC and ARL. 

14. ABSTRACT 

The U.S. Army is examining evolutionary concepts for the command and control of military vehicles. Currently, there is a performance issue 

regarding vehicle control at higher speeds for some indirect vision, by-wire tactical vehicles. By-wire vehicles are those in which mechanical 

links between the driver and control devices are replaced by electronic or computerized signals. Specifically, an operator’s ability to maintain 

reliable control of by-wire military vehicles while driving appears to be progressively compromised as vehicle speed increases. Several 

factors have been identified as possible sources of this difficulty, including lags in the system control loop, characteristics of the steering 

interface (such as its shaping function or lack of force feedback), inadequate visual display, and physical effects of vehicle motion on the 

operator (McDowell et al., 2007a). This report is a review of the current state of knowledge regarding the steering shaping function, which 

specifies the dynamic spatial relationship between steering input from the driver and vehicle heading direction. The overall goal of the 

review is to identify design parameters critical to improving current by-wire implementation in military tactical vehicles, thereby identifying 

design elements to optimize human-vehicle system performance for secure mobile operations. 

Through a review of general automotive literature related to variable gear ratio steering systems as well as steer-by-wire design and 

implementation, three main factors affecting steering control were identified. The primary factors of influence that were reviewed included 

the overall range of motion (“throw”) of the steering device, the steering shaping function, and modifications of the shaping function because 

of vehicle motion characteristics. In addition, variations in performance were observed to be a consequence of dynamic characteristics of the 

operator and the vehicle and most importantly, the interaction between the operator and the vehicle. This review concludes that the shaping 

function is a central influence over system performance, and further, it is apparent that no single shaping function will suffice across all 

driving scenarios. Owing to noteworthy driver performance issues at higher vehicle speeds (particularly with nonstandard steering devices, 

such as joysticks), a call is made for further research to extend the current understanding of steering control. Specifically, we suggest that the 

achievement of optimal steering characteristics will most likely come with a greater understanding of the dynamic variations needed within 

shaping functions in order to accommodate different vehicle, task, and operator characteristics.

15. SUBJECT TERMS

 drive by wire; human performance; shaping function 

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iii 

Contents 

List of Figures iv

Acknowledgments v

1. Statement of Issue 1

2. Introduction 1

3. Drive by Wire and Control 3

4. The Human Operator 4

5. Improved Vehicle Control With the Use of a Steering Shaping Function 6

6. Shaping Functions, Variable Steering Ratios, and Driver Performance 9

6.1 Angular Range of Motion (“Throw”) of the HMI...........................................................9 

6.2 The Interaction of Speed and Throw.............................................................................11 

6.3 Considerations of Variability Attributable to Task and Individual Operator 

 Differences ....................................................................................................................16 

7. Summary 18

8. Conclusions and Future Directions 19

9. References 21

Distribution List 25 
iv 

List of Figures 

Figure 1. The CAT, based on a modified Stryker vehicle, undergoing development at 

TARDEC in collaboration with ARL. .......................................................................................2 

Figure 2. A comparative example of the difference between conventional (A) and by-wire 

(B) steering systems...................................................................................................................3 

Figure 3. BMW’s active steer system is based on varying the steering ratio, depending on 

vehicle speed............................................................................................................................13 

Figure 4. Experimentally observed yaw gain as a function of vehicle speed, for both variable 

steering ratio (steer-by-wire) and fixed ratio (conventional vehicle) ......................................15 

Figure 5. Results from simulated driving with a variety of gear ratios. (A) depicts the 

“shaping functions” for the five different gear ratios tested (three fixed: 6, 13, 20 and two 

variable: linear and nonlinear 20-6:1). The remaining graphs represent driver ratings of 

each gear ratio based on perceived ease of control (B), vehicle response on fast 

movements (C), and required steering angle (D).....................................................................16 

Figure 6. Joystick sensitivity as a function of joystick angle and simulated speed......................19 
v 

Acknowledgments 

This work is the result of a collaborative effort between the U.S. Army Tank-Automotive 

Research, Development, and Engineering Center (TARDEC) and the U.S. Army Research 

Laboratory. Specifically, the author Jason S. Metcalfe participated in this effort as a result of a 

TARDEC-sponsored project at DCS Corporation. 
vi 

INTENTIONALLY LEFT BLANK
1 

1. Statement of Issue 

The U.S. Army is examining evolutionary concepts for the command and control (C2) of military 

vehicles. Currently, there is an important performance issue regarding vehicle control at higher 

speeds for some indirect vision, by-wire vehicles, that is, those vehicles in which mechanical links 

between the driver and control devices are replaced by electronic or computerized signals. 

Specifically, an operator’s ability to reliably maintain control of by-wire military vehicles during 

mobility appears progressively compromised as vehicle speed increases. Several factors have 

been identified as possible sources of this difficulty, including lags in the system control loop, 

steering shaping function and/or lack of force feedback, inadequate visual display, indirect vision 

system, and finally, physical effects of vehicle motion on the operator (McDowell, Oie, Tierney, & 

Flascher, 2007). This review is intended to assess the current state of knowledge regarding one of 

these factors, specifically, the shaping function. The overall goal is to support the identification of 

design parameters critical to improving the current by-wire implementation for military tactical 

vehicles and to ultimately optimize system (i.e., human-vehicle) performance for the execution of 

secure mobile operations. 

2. Introduction 

In support of future force initiatives, the U.S. Army is examining new and evolutionary concepts 

for modernization of the C2 of military vehicles. Advanced development of vehicle electronics 

(vetronics) technologies is seen as a catalyst, pushing the transformation of the U.S. military to a 

highly networked and automated presence on the battlefield (Keller, 2004). One program aimed at 

the development and implementation of advanced vetronics technology is the Crew Integration and 

Automation Test Bed (CAT; see figure 1), developed at the U.S. Army Tank Automotive 

Research, Development, and Engineering Center (TARDEC) in collaboration with the U.S. Army 

Research Laboratory’s (ARL’s) Human Research and Engineering Directorate. The CAT provides 

an important platform for conducting research on a variety of issues, among which are human 

factors considerations associated with staffing semi-autonomous and/or autonomous vehicles with 

a reduced crew of two military personnel. Of primary concern as research and development efforts 

proceed is the influence of automation and related technologies on the human-vehicle system 

performance during secure mobile operations, defined here as operations that require sustaining a 

real-time understanding of the environment local to one’s vehicle and platoon (local area 

awareness) concurrent with the performance of primary tasks for terrain traversal (McDowell, 

Nunez, Hutchins, & Metcalfe, 2008). 
2 

Figure 1. The CAT, based on a modified Stryker vehicle, undergoing development at TARDEC in collaboration with ARL. 

The optimization of Soldier performance during secure mobile operations is critical to the 

successful realization of future force concepts (McDowell et al., 2007). As the level of technology 

integrated into fielded equipment increases while crew sizes decrease, Soldiers are likely to be 

faced with elevated cognitive and physical workload during vehicle operation. The tasks 

associated with driving the vehicle, such as steering, throttle and brake control, appear as ideal 

candidates for the incorporation of automation for the purpose of increasing vehicle safety and 

security while reducing operator workload. However, several human performance issues arise 

from the incorporation of technical solutions for meeting automation needs in vehicle control 

systems (Andonian, Rauch, & Bhise, 2003; Stanton & Marsden, 1997; Stanton & Young, 1998). 

Thus, engineering decisions regarding the “what and how” of such implementations are made 

challenging in nontrivial ways. Included in the problems induced by the staffing of automated 

systems are biomechanical (Sirouspour & Salcudean, 2003; Sövényi & Gillespie, 2007), cognitive 

(Parasuraman & Riley, 1997), and psychomotor (Stanton & Marsden, 1997; Stanton & Young, 

1998) issues affecting the execution of system control tasks. 

The current review focuses on one specific aspect of these problems, that is, performance issues 

associated with the reduced “throw” (i.e., angular range of motion of the controller) of drive-bywire human-machine interface (HMI) devices such as yokes and joysticks, as compared with the 

conventional steering wheel. In particular, because of its essential role in defining the behavior of 

the steering system, the characteristics of the shaping function and how it affects driving 

performance will be our focus. We first present a summary of the basic issues associated with 

steer-by-wire vehicles that use nonstandard control devices, followed by a brief discussion of the 

variety of approaches to solving these issues by means of variable gear ratio steering systems. 
3 

3. Drive by Wire and Control 

Future military vehicles will be drive-by-wire (DBW) vehicles, which means that mechanical 

elements of the control system are replaced by operator-controlled input devices coupled with 

remote actuators via a central electronic control system (Mammar, Sainte-Marie, & Glaser, 2001; 

Yih & Gerdes, 2005). A DBW vehicle can be composed of several “x-by-wire” subsystems. 

Examples include steer by wire, brake by wire, and throttle by wire, each referring, of course, to 

the individual vehicle control subsystems for which direct mechanical linkages (such as the 

hydraulic brake line) have been replaced by electrical signals between the input device (e.g., brake 

pedal) and the actuators of the system (e.g., calipers). In this report, we are specifically interested 

in steer-by-wire subsystems, an example of which is shown in figure 2b. While the issues we 

address have analogues in other x-by-wire system components, we will not directly address their 

influence on driver performance. 

 A B 

Figure 2. A comparative example of the difference between conventional (A) and by-wire (B) steering systems. 

(Images are adapted from Yih and Gerdes, 2005, p. 966, figures 1 and 2.) 

Because the actuators in x-by-wire systems are controlled by electrical signals from a computer 

rather than a direct mechanical link to the HMI, input from the driver can be supplemented with or 

modified by intelligent automation. A good example of such automation in civilian vehicles is 

adaptive cruise control (ACC). An ACC system is used in a manner similar to standard cruise 

control except that after the driver sets the desired speed, an adaptive controller regulates spatial 

separation from other vehicles on the road as well as attempts to maintain the speed indicated by 

the driver (c.f. Kelber et al., 2004; Rajamani & Zhu, 2002). The commercial automotive industry 

views by-wire and associated technologies such as ACC as advantageous because they enable new 

design options in terms of packaging vehicle components, integration of intelligent performanceand safety-enhancing control features, and reduction in noise. In the case of by-wire steering, 

ACC can mean increased safety for the driver because there is no steering column that could 

invade the vehicle cabin during a front-end collision (Chiappero & Back, 2002; Fowler, 2003). 
4 

The successful implementation of intelligent driving systems such as ACC facilitates our discussion of military applications by highlighting useful alternatives to traditional control. Of 

particular interest are intelligent systems that allow user specification of vehicle motion without 

explicit need for direct and/or continuous input. Intelligent vehicle systems provide designers the 

opportunity to develop and integrate a range of controllers that ultimately may increase overall 

system performance and may reduce the workload associated with mobility-control tasks (Kelber 

et al., 2004; Stanton & Marsden, 1997). At the same time, such advances in vehicle technology 

and non-traditional controls place a greater emphasis on the importance of careful interface design 

and implementation and how these advances influence human driving performance (Walker, 

Stanton, & Young, 2006). 

Clearly, the integration of by-wire technology and associated non-standard control devices such as 

joysticks into vehicle control systems has significant potential to improve driving performance and 

vehicle safety during mobile operations while decreasing vehicle space claims and operator training time (Andonian et al., 2003). Successful implementation of by-wire and other related technologies, such as vehicle safety features (e.g., antilock brakes, dynamic stability control) and 

electric power steering (EPS), into current automotive industry production lines supports the position that intelligent systems can be extrapolated into capabilities such as active steering, which 

may augment the driver’s input to improve stability and maneuverability. Such systems have 

demonstrated advantages in civilian driving during tasks including lane maintenance (Rossetter, 

Switkes, & Gerdes, 2004) and path selection (Shoemaker, Bornstein, Myers, & Brendle, 1999) 

and are ultimately thought to offer improvements in performance (Ackermann & Bunte, 1997; 

Kasselmann & Keranen, 1969; Yih & Gerdes, 2005). 

4. The Human Operator 

Despite dramatic improvements in intelligent, adaptive technologies for vehicle control systems, 

the time when the role of the human changes from operator to passenger remains in the distant 

future. The essential role of the human within the control loop has long been recognized as the 

best possible solution to the difficulties associated with developing systems that are robust enough 

to account for the myriad of contingencies presented by an open, dynamic task environment 

(Parasuraman, Sheridan, & Wickens, 2000; Parikh, Grassi, Kumar, & Okamoto, 2007; Sellner et 

al., 2006; Sheridan, 1992). Accordingly, research and development efforts continue to incorporate 

the human as an integral element in the operation of the physical driving system. That is to say, 

although issues of vehicle autonomy are an important consideration within future military vehicle 

programs, we do not explicitly focus on autonomous vehicles within this current discussion of 

steer-by-wire systems. Instead, throughout our discussion, we focus on the interaction between 
5 

the human operator and the by-wire steering system as the primary locus of potential control 

difficulties. 

Control theory-based models, which formalize the description of information flow from input to 

output, are frequently used to guide the design and analysis of complex physical systems. Likewise, in modern research, control theory models are employed with increasing frequency to 

facilitate a mechanistic understanding of input-output relations in human performance, both 

independent of (Todorov & Jordan, 2002) and during interactions with physical systems (Huang, 

Smakman, & Guldner, 2004; Sövényi & Gillespie, 2007). There is a broad literature available 

about human performance from the perspective of engineering and control theory (c.f. Jagacinski 

& Flach, 2002; Wickens & Hollands, 2000). Within this literature, it is clear that humans are 

understood to be particularly adept at tasks requiring certain types of control, such as the flexible 

decision making and adaptive reasoning required in unexpected situations. However, at the same 

time, humans have degraded or limited performance in tasks requiring other forms of control such 

as those that require rapid actions and decisions in the presence of lagged feedback regarding 

system response to control input (c.f. Sheridan, 1993). 

Wickens and Hollands (2000) suggested that human performance is specifically limited by its 

fundamental information-handling capabilities such as processing time, information transmission, 

prediction and anticipation, perception of higher derivatives (e.g., velocity, acceleration), and 

processing resources. In general, as the amount and complexity of information that the human is 

required to process increase, performance tends to decrease. For example, it is well known that the 

rate of information transmission, as reflected in the time required to perceive and react to a given 

stimulus (i.e., reaction time), is slowed by a number of factors, including increased age of the 

performer, number of response choices, degraded detectability of the stimulus, incompatibility 

between the stimulus and the response and number of actions that must be planned and performed 

following the stimulus cue (Schmidt & Lee, 1999). 

Increased semi-autonomous operations will be enabled by x-by-wire implementations, accompanied by enhanced functionality for the operator through the Soldier-machine interface (SMI). 

This is very likely to place a high demand on the human operator’s limited information processing 

resources (McDowell et al., 2007, 2008; McGovern, 1987). As a direct consequence of the 

reduced crew size and increased in-vehicle technology, the operator will be required to attend to a 

greater number of tasks simultaneously. Examples of such overlapping tasks include maintenance 

of a supervisory level of control over vehicle mobility requiring frequent monitoring and periodic 

assumption of control over the vehicle while concurrently scanning the local area for potential 

enemy activity and attending to vehicle status variables such as engine temperature and fuel level 

(McGovern, 1987). Accordingly, the impact of enhanced vehicle technology on aspects of human 

performance that are potentially compromised by increased workload and attentional demands 

must remain a high-priority consideration for system designers in optimizing system performance 

and safety. 
6 

A variety of arguments has been forwarded in specific reference to human factors considerations 

for by-wire vehicle design (Stanton & Marsden, 1997; Stanton & Young, 1998; Walker et al., 

2006). For example, Stanton and Marsden (1997) evaluated three generalized human-centered 

justifications for incorporating automation in ground vehicles; these included potential improvements in driver well-being through reduced stress, frustration and workload, removal of human 

error from the control loop, thus reducing likelihood of accidents, and increased commercial and 

consumer options positively affecting sales in the automotive market. Of course, concern was also 

raised that automation could introduce negative performance outcomes unless well conceived and 

applied. For example, Stanton and Marsden considered possible “error-inducing equipment 

design” as sufficiently important to merit inclusion among the four main possible sources of problems in future by-wire systems. The other three major sources of problems included (a) shortfalls 

in the expected benefits of implemented systems; (b) changes in operator expectations and level of 

vigilance based on reliability of the automated system (problems were cited for unreliable as well 

as “overly reliable” cases); and (c) a loss of operator skill and responsiveness to training as a byproduct of diminished perceived relevance of the skill set for the operation of automated systems. 

The human factors issues associated with the shaping function that specifies the relationship 

between HMI commands and vehicle heading, touch on a number of these potential sources of 

problems. In addition to the obvious association with “error-inducing equipment design,” it is 

possible that a poorly selected shaping function could have negative consequences for operator 

perception of vehicle reliability as well as simply having shortfalls in expectations based on the 

intent of the design. 

5. Improved Vehicle Control With the Use of a Steering Shaping Function 

For the purposes of our research, we define a shaping function as a mathematical description of 

the scaling between the input and output of a given system, that is, how the input is “shaped” into 

output. This is similar to the concept of a transfer function, except that the transformation is not 

explicitly occurring in the frequency domain. For steer-by-wire systems, the shaping function 

maps the angular displacements of the HMI control input device (joystick, yoke, or steering wheel) 

to the system response in terms of the vehicle steering angle. The examination of shaping functions is important for several reasons. First, the use of HMI devices with limited “throw,” or total 

angular range of displacement, will pose challenges to the operator. A specific consequence of 

limited throw is the magnification that the operator will perceive relative to his or her expectations, 

based on experience with standard vehicles with steering wheels. In other words, because of the 

smaller permissible angular range of alternate HMI, there will be a lower input position-to-wheelangle ratio (also known as the steering ratio), and therefore, smaller hand/arm motions will 

produce larger vehicle responses. A second issue involves the need for differential steering 

sensitivity across various driving tasks. Consider, for example, the large angular range of steering 

motion required for parallel parking as compared with the relatively small motions needed for lane 
7 

maintenance while one is driving on a highway (Huang et al., 2004; Olson & Thompson, 1970). 

Now envision the variety of steering tasks that may be encountered on the battlefield or during offroad missions in military vehicles. Such task factors are further compounded by the third issue: 

vehicle speed. In particular, as the vehicle moves faster, the magnitude of lateral accelerations 

during steering increases, elevating the risk of oversteering, inducing excessive roll or loss of 

control leading to collision, spinout or rollover (Ackermann & Bunte, 1997; Sakai, Yoneda, & 

Shimizu, 2004). An advantage to the electronic control used in steer by wire is that the steering 

ratio does not have to be fixed, but rather, it can be modulated adaptively across platforms, tasks, 

and speeds to help account for these performance and safety issues (Andonian et al., 2003). 

The primary approach to overcoming the problems mentioned has been to implement variable gear 

ratio (VGR) steering systems. The gear ratio in a steering system provides a description of how 

much angular displacement of the steering wheel is required to produce a particular angular displacement of the vehicle heading via turning of the wheels. For instance, if one complete revolution (360 degrees) of the steering wheel results in the wheels of the vehicle turning 20 degrees, 

then the steering ratio is 360/20, or 18:1. A higher ratio means that one has to give greater input 

(thus expending more energy) to get the wheels to turn a given distance. 

There have been, of course, different mechanisms for implementing VGR systems. We categorize 

the VGR systems as speed variable [sVGR]), which scale the ratio as a function of vehicle speed, 

or angle variable (nVGR), which scale as a function of HMI input angle. VGR steering systems 

have been proposed and studied since the 1960s (Huang et al., 2004; Olson & Thompson, 1970; 

Wohl, 1961). Typically, modern VGR systems are of the sVGR type that work by using an active 

steering system (such as electronic power steering [EPS]) to minimize the ratio at low vehicle 

speeds, reducing the amount of steering wheel motion required to make large maneuvers, and then 

increasing this ratio progressively as vehicle speed increases, thus minimizing the influence of 

minor hand motions that the operator may make while driving at higher speeds. Such systems have 

already been introduced in the commercial automobile market and are currently considered a 

selling point for higher end vehicles and thus, are the types of systems that have received the most 

attention. 

An alternative to speed variable systems is available in the form of the nVGR implementation. 

With an nVGR system, the steering ratio scales as a function of the operator input rather than the 

vehicle motion. Specifically, the response of the wheels to a given angular displacement of the 

HMI will vary, depending on the current angular position of the interface. For example, in a 16-

8:1 nVGR system actuated by a yoke, a 2-degree input issued from the central position of the 

yoke would result in a 16-degree steering angle, but that same input issued when the yoke is near 

one of its extreme angular positions would result in a 32-degree steering angle. For conventional 

vehicles that have a steering column, such as those using a rack-and-pinion mechanism, one can 

achieve nVGR by simply changing the spacing between the gear teeth as the angular distance 

from the central position increases. For by-wire systems, the same results can be obtained in a 

more flexible manner through the use of an appropriately defined shaping function that specifies 
8 

the scaling relationship between the HMI and wheel angle across the range of possible steering 

inputs. 

The use of a shaping function can eliminate the need for or facilitate the function of an on-line, 

dynamic control system that monitors vehicle motion and changes the steering ratio from one 

speed condition to another. That is, if one considers that high-speed driving is most commonly 

associated with a very small range of steering input and lower speed maneuvering (such as 

parking) uses much more of the dynamic range of the steering wheel, then a nonlinear shaping 

function that applies a high ratio for small steering input and a lower, more direct ratio for large 

input will effectively match the steering ratio to vehicle speed by virtue of the task that the driver 

is performing. At the same time, one can envision dynamic selection of shaping functions that are 

optimized for particular vehicle operation scenarios in order to smoothly change steering characteristics in an on-line fashion when a different vehicle response is required. 

A current approach for by-wire military vehicles employs a nonlinear shaping function to map 

steering input to wheel angle. The nonlinearity in the current shaping function is attributable to 

a dead spot (an area of no system response) around the zero point (null position) of the HMI, 

combined with active regions to either side of the inactive dead spot where output increases 

linearly as a function of steering angle. The prominence of the dead spot is important because of 

continuous, subtle input from the operator around the central position, which must be minimized 

in order for the steering output to stabilize (Jagacinski & Flach, 2003). This is particularly true for 

velocity or higher derivative-based motion control systems because small fluctuations, such as 

noise, tend to be significantly magnified with each higher derivative used in the control loop. To 

facilitate stabilization of wheel angle, we have made the dead spot more prominent by defining a 

broader angular region around the null position throughout which there will be zero input to the 

steering system; this null region is known as the dead band. The boundaries of the dead band are 

defined by a “psychophysical edge” where the driver can “feel” (perceive) a change between the 

inactive and active regions. In essence, this dead band acts as a low-pass filter so that the effects 

of small amplitude, high frequency steering input around zero are removed while large amplitude, 

low frequency steering input are allowed to influence the system’s behavior. An important 

justification for inclusion of this dead band is illustrated by the phenomenon of “biodynamic 

feedthrough” in which vibrations of the vehicle are transmitted to the HMI through the operator in 

a purely mechanical manner (Sirouspour & Salcudean, 2003; Sövényi & Gillespie, 2007). 

Obviously, it is not desirable for jostling of the vehicle to affect steering input from the driver, 

particularly in critical situations such as evasive maneuvering where speeds are higher and vehicle 

motion is more vigorous. 

Regardless of how the system is implemented, it appears as if VGR steering has the potential to 

be a performance- and safety-enhancing control option (Huang et al., 2004; Kelber et al., 2004; 

Limpibunterng & Fujioka, 2004; Sakai et al., 2004; Yih & Gerdes, 2005). Although its application 

in conventional vehicles has yet to become standard, how to make decisions regarding the 

particulars of the VGR implementation remains an important engineering challenge for steer-by-
9 

wire systems. That is, by virtue of the way in which by-wire systems function through the 

intermediary of a computerized control system, designers must confront the question of how best 

to transform control input from the HMI to the steering actuators (Andonian et al., 2003; Östlund 

& Peters, 1999; Peters & Östlund, 2005). Fundamental to answering this question are the human 

factors issues raised by nonlinearities implemented in vehicle control through the steering shaping 

function. In other words, it is essential to understand the effects of different parameters of VGR 

steering on human performance during military vehicle driving. 

6. Shaping Functions, Variable Steering Ratios, and Driver Performance 

When one is considering performance difficulties in HMI, the interface should be one of the 

primary system elements assessed as a potential source of error. The functional capacity of the 

driver-vehicle system will be defined in large part by the interaction between the capabilities of the 

operator and the operational characteristics of the HMI. By-wire systems provide a myriad of 

possibilities in terms of the HMI devices that can be used for vehicle control. This flexibility, 

combined with a general lack of complete understanding of human factors issues associated with 

these interfaces, creates a level of ambiguity with respect to the establishment of design standards 

regarding ideal operational characteristics for steer-by-wire vehicles. Moreover, the potential that 

any number of interface-driver combinations may be used with a given by-wire vehicle demands 

that software is adequately programmed to map (a) driver preferences, (b) the dynamic angular 

range of the HMI, and (c) that of the vehicle to one another in order to provide intuitive control 

while optimizing steering input for the physical dynamics of the controlled vehicle. 

In what follows, the effects of VGR systems on human driving performance are assessed in order 

to generate conclusions regarding the structure that the shaping function of the HMI implemented 

in some by-wire vehicles. Although the effects of using VGR systems on driving performance 

constitute an important area of research within the commercial automotive industry, few results 

have been made available through the peer-reviewed literature (presumably owing to proprietary 

issues). This is particularly true in terms of assessing how these results translate to military 

platforms. As such, the available information is reviewed and assessed as a general guide for 

interpretation of expected effects of the shaping function on Soldier performance in military 

situations. Our discussion takes as a starting point that there are three main issues to consider: 

(a) the limited angular range of motion (“throw”) of the HMI, (b) the interaction between throw 

and vehicle speed, and (c) individual differences among and within human operators in terms of 

driving style and task effects. 

6.1 Angular Range of Motion (“Throw”) of the HMI 

Critical to the current review is the fundamental issue that different HMI devices are built with 

different amounts of throw. Consider, for example, that many conventional steering wheels can 
10 

be turned ~3 to 3.75 revolutions within the physical limits of the system, yielding approximately 

±540 to ~675 degrees of allowable motion. On the other hand, joysticks, which are the preferred 

HMI for use in the CAT (primarily because of physical space constraints within the vehicle), are 

typically limited to a ±20- to ~40-degree dynamic range (Andonian et al., 2003; Östlund & 

Peters, 1999; Peters & Östlund, 2005). To translate these angular motions to a more intuitive 

metric, Östlund and Peters provided an example of how a driving movement requiring a 20-

degree displacement of a conventional steering wheel could be accomplished with a 0.6-degree 

displacement of a joystick, which would mean that the operator would only need to move his or 

her hand 1 mm to induce a significant change in vehicle heading. As applied to military platforms, such as a 20-ton, 8-wheeled light armored vehicle (LAV), a ±60-degree yoke would result 

in a linear steering ratio of approximately 1.6:1. This contrasts with steering ratios used in 

conventional automobiles that are nearly an order of magnitude higher, typically around 14:1 

(Olson & Thompson, 1970; Sakai et al., 2004; Schulze, 1981; Tongue, 2005). 

The practical significance of reduced throw in most by-wire HMI devices as compared with a 

standard steering wheel is that it simultaneously allows subtle hand movements to provide finegrained control over vehicle motion, which may be a benefit, but it also considerably increases the 

potential for control degradation because of inadvertent input resulting from biodynamic 

feedthrough (Sirouspour & Salcudean, 2003; Sövényi & Gillespie, 2007), limb positioning errors 

(Allen & Proske, 2006), or small, unintentional postural adjustments of the operator (Treffner, 

Barrett, & Petersen, 2002). That is, with the magnification of the relationship between hand 

movement and vehicle response, it is likely that all accelerations, whether they are of the vehicle 

or the operator, will be physically transmitted to the HMI and will thus serve as unintended control 

input. For instance, centrifugal acceleration during a sharp turn could cause a driver’s body to be 

thrown outward (i.e., away from the turn), and this could result in a counter-steering motion 

translated to the HMI that would disrupt the execution of a smooth and controlled turn of the 

vehicle. This issue is particularly salient for tasks that tend to occur at higher speeds, such as lane 

keeping, where movements of a steering wheel in a conventional vehicle are on the order of 5 to 

10 degrees (Andonian et al., 2003) but would be on the order of 0.5 to 1 degree in the alternate 

HMI by-wire vehicle. As the allowable range of motion in the HMI is reduced, it is very likely 

that the amount of steering errors may be increased by virtue of limits on the resolution of the 

human capability to sense and precisely control limb position. For example, recent evidence 

suggests that perception of arm positioning in a typical human adult may only be accurate to 

within 1 to 2 degrees and during fatiguing circumstances, the errors in positional sensation/ 

perception can increase nearly five fold (Allen & Proske, 2006; Walsh, Hesse, Morgan, & Proske, 

2004). Taking such basic functional aspects of human physiology into account should therefore 

constrain engineering decisions regarding the lower limits of the functional range of a steer-bywire HMI device. 
11 

6.2 The Interaction of Speed and Throw 

The issue of reduced throw in by-wire interfaces for driving is complicated by considerations of 

the speed at which the vehicle is to be controlled. Common wisdom, as well as considerable 

research, suggests that even without the issue of limited throw, task speed is a major factor 

affecting human performance (Plamondon & Alimi, 1997; Schmidt & Lee, 1999), and this 

relationship between task speed and performance has had considerable influence over developments within the domain of human-computer/human-machine interaction (Seow, 2005). Even 

from a purely physical standpoint on the task of driving, as a vehicle moves at increased speeds, 

the effects of heading variations in terms of lateral accelerations and likelihood of losing vehicle 

control (oversteering, spinout) are significantly increased (Ackermann, 1998; Ackermann & Bunte, 

1997; Limpibunterng & Fujioka, 2004; Sakai et al., 2004). This physical reality becomes a critical 

variable when we examine the relationship between driver input and vehicle output as well, and 

this rationale served as the basis of one of the earliest investigations of VGR systems: “... [in 

order] to provide precise control at high speeds and maximum insulation from road shock, the ratio 

should be high. On the other hand, to minimize steering-wheel turning and provide easier lowspeed maneuvering, the ratio should be low. An obvious solution is a variable-ratio steering gear” 

(Olson & Thompson, 1970, p. 553). 

The work of Olson and Thompson (1970) was among the first peer-reviewed publications that 

indicated an impact of the steering ratio on both actual and (self-) perceived operator performance 

during driving. While not an explicit study of sVGR systems, Olson and Thompson used nVGR 

systems to examine driver performance and perception across a number of tasks requiring different 

speed-lateral acceleration combinations (i.e., variable ratio gears included 16-12.2:1 and 16-8:1; 

fixed ratios included 11:1, 13.5:1, and 16:1). Summarily, it was observed that drivers generally 

gave vehicles with VGR systems higher subjective ratings regarding perceived controllability as 

compared with fixed ratio vehicles, and these subjective ratings were supported with statistically 

verified performance improvements during low-speed parallel parking (e.g., reduced parking 

time). Performance enhancements, however, were not statistically supported for a continuous 

motion, higher speed lane-keeping task along a curvilinear path. Additionally, for all conditions, 

drivers indicated nearly ubiquitous dislike of the more “extreme” of the VGR systems used (16-

8:1), specifically citing increased perception of vehicle roll during sharp cornering as problematic 

and suggesting that the steering may have been too sensitive in that system. The important 

message to be taken from these qualitative reports, together with the variations in patterns of 

statistical significance (or lack thereof) across conditions, is the notion that task factors involving 

speed and lateral acceleration are important considerations for VGR system design in terms of 

vehicle performance and operator perceptions affecting trust in the vehicle. Although Olson and 

Thompson cautioned against drawing broad conclusions from their initial assessment of VGR 

systems, it is reasonable to conclude that VGR steering did not degrade performance, and further, 

some evidence was found that a VGR system, appropriately calibrated to speed, could facilitate 

improved vehicle control and operator perceptions. 
12 

Unlike the nVGR systems assessed by Olson and Thompson (1970), modern VGR systems are 

often of the speed-variable variety. The rising popularity of sVGR can be logically attributed, at 

least in part, to its ability to be actuated by the already established electronic or electro-hydraulic 

power steering systems and, of course, further encouraged by the expectation of eventual transition 

to complete electronic vehicle control as will be the case in future steer-by-wire systems. BMW 

(Bayerische Motoren Werke), for instance, is among several producers of high-end vehicles that 

have integrated sVGR into their commercial offerings; others include Lexus, Toyota, Audi, and 

Honda. Such systems are generally known on the commercial market as “active steering” (AS) or 

“active control steering” (ACS) systems. Active steering systems electronically vary the steering 

gain (i.e., ratio) as a function of the steering wheel angle and the current movement state (speed, 

lateral/yaw acceleration) of the vehicle. In such systems, during normal, low- and medium-speed 

driving conditions, the steering ratio is designed to be approximately direct. This means that the 

gear ratio is low and the wheels respond with a greater angular displacement for a given amount 

of steering input from the driver. As a result, the amount of work that the driver must do to 

accomplish typical low-speed maneuvers, such as navigation around a tight corner in a cramped 

space, is reduced as compared with a vehicle using a fixed steering ratio. As the vehicle control 

system detects increasing speed, it then adjusts the steering ratio to decrease sensitivity, thus 

reducing the magnitude of steering response to driver input and therefore, the likelihood of 

maladaptive responses such as oversteering. In more extreme circumstances, such as when driver 

input is inappropriate and would lead to vehicle destabilization, a sophisticated controller algorithm could literally take control from the driver and minimize or even cancel the influence of his 

or her steering input (Tongue, 2005). 

As one of the first widely available sVGR systems, the BMW’s 5-series hybrid active steer system 

is useful as a detailed example (DeMeis, 2003; Sawyer, 2003; Tongue, 2005). Consistent with the 

speed-variable control principles already discussed, fewer than two full turns of the steering wheel 

in a 5-series BMW are needed to achieve maximal change in steering angle (“lock to lock”), and 

thus, the low-speed steering ratio is more direct (on the order of 10:1) whereas at higher speeds, the 

ratio can reach a maximum of 20:1. Moreover, redundancy is built into the system so that if the 

active steering fails, there is a mechanical “backup” that reduces steering to the baseline function 

of a standard, fixed ratio (14.1:1) system. Figure 3 shows the variable steering ratio as implemented in BMW’s active steering system; note the nearly 50% reduction in driver effort during 

normal driving at 50 kph (~31 mph) for the actively variable (blue line) as opposed to a constant 

ratio system (red line). In more extreme circumstances, by contributing as much as 2.5 degrees of 

front wheel countersteering, this active steering system can facilitate recovery from potentially 

hazardous incidents by avoiding activation of the oft-disconcerting dynamic stability control 

(braking) system of the vehicle (DeMeis, 2003). 
13 

Figure 3. BMW’s active steering system is based on varying the steering ratio, 

depending on vehicle speed. (Image adapted from DeMeis, 2003.) 

Although the BMW active steering system has received a bit of attention in the published media, 

no direct information regarding how this system affects human performance has been evidenced 

through peer-reviewed data reports. At the same time, a variety of model-based assessments has 

been used to mathematically infer how sVGR systems analogous to active steer have potential to 

attenuate the influence of maladaptive driver input during critical situations (Azzalini, Gissinger, 

Boussouar, & Coutant, 2002; Huang et al., 2004; Limpibunterng & Fujioka, 2004; Sakai et al., 

2004). For example, Sakai and colleagues developed a cable-type VGR steering system for Honda 

and, through a combination of model-based quantitative and qualitative analyses, were able to 

show enhanced performance in avoidance of a spinout (Sakai et al, 2004). In essence, Sakai and 

colleagues were able to achieve VGR steering characteristics by using the physical properties of a 

flexible cable that has lowered torsional rigidity (reduced stiffness) in place of a standard steering 

column. Because of its physical load-deformation properties, the cable-type EPS system had a 

steering response that was proportional to the magnitude of self-aligning torque experienced by the 

wheels of the vehicle; the torque itself was a function of steering angle and vehicle speed. Active 

torque control components of the system were used to compensate for phase lags, that is, delays in 

the timing of the steering response induced by the physical mechanics of the cable. Computational 

simulations demonstrated how this type of sVGR system could facilitate the avoidance of and 

recovery from spinout attributable to oversteering across a range of driver capabilities. That is, 

not only was this system superior to fixed gear ratio systems for enabling safe maneuvering in the 

extreme situations, but it was also shown as able to tolerate a larger range of lags in the time it 
14 

took for the human driver to initiate corrective steering action (e.g., slowed reaction times) as 

compared with more rigidly actuated systems, such as those using a standard steering column. 

Using a similar analytic method but guided by some earlier empirical data regarding human 

performance in VGR systems (specifically, data from Schulze, 1981), Huang et al. (2004) 

mathematically verified that improvements could be made with VGR systems but added that the 

variation in the gear ratio should be based on different information within different speed ranges. 

Specifically, through closed loop analyses, it was shown that at speeds below ~25 km/h (~15 mph), 

the driver prefers a fixed steering ratio, and thus, position-based feedback control is optimal. In 

such a zeroth order system, the angle specified by the HMI should thus be proportional to the 

curvature of the vehicle path. In other words, the operator should control the vehicle at low speeds 

through a shaping function based on the steering wheel angle alone. Huang et al. further observed 

that at intermediate to higher speeds (~25 to ~45 km/h and above), drivers appeared to prefer 

steering systems that maintain constant yaw gain, that is, a constant rate of change in vehicle yaw 

(vehicle heading angle with respect to a directly forward path) as a function of HMI angle 

(figure 4). Therefore, it was concluded that in intermediate to high speed ranges, the driver 

primarily uses rate information (i.e., first order control) to select the appropriate HMI angle. This 

theoretical analysis gains a modicum of support from the earlier data of Olson and Thompson 

(1970) that revealed lack of performance enhancements for drivers using nVGR systems in lane 

keeping as compared with parallel parking. Perhaps if Olson and Thompson had been able to 

implement a rate-based VGR system for their higher speed tasks (recall, nVGR is based only on 

steering wheel angle), they would have seen benefits throughout their experimental conditions 

rather than only in parallel parking. 

Although data regarding human performance with specific, commercially available sVGR 

systems such as BMW’s active steer tend to be sparse, a number of research groups have assessed 

performance effects of the types of advanced systems that form the basis of those implemented in 

commercial models. In the studies where sVGR components were included, data have been 

presented which support the idea that driver performance in by-wire systems can be equivalent 

to performance of a standard steering system (Yih & Gerdes, 2005) and in certain cases, performance can be enhanced (Kelber et al., 2004). Unfortunately, there are two main problems 

precluding heavy reliance on data from most of the available studies. First, while experimental 

design was usually reasonable in terms of inclusion of appropriate control conditions, the data 

sampling, selection of measures, and subsequent analyses were not generally conducted in a 

manner that allowed verification of qualitatively observed differences through proper use of 

inferential statistics. Second and more problematic for the interpretation of the unique influence 

of sVGR on driver performance is that most studies that have identified performance equivalence 

or enhancements have included sVGR as part of larger active steering systems and thus, did not 

assess its independent contribution to driver performance. Accordingly, although it can be 

inferred that sVGR is an important component of an overall performance-enhancing system, few 

conclusions can be drawn regarding the specific implementation details that optimize vehicle 
15 

safety and driver performance. To speak about this last point, a small amount of information was 

found in an early simulator study of sVGR as compared with a number of fixed ratio systems 

(Schulze, 1981). As with other studies in this domain, inferential statistics were not provided 

to verify that qualitative patterns of difference were real (beyond differences attributable to 

measurement error); however, this study presented evidence that indicated sVGR in the range 

of 20-6:1 leads to driver-perceived performance enhancements when civilian vehicles are being 

operated. Specifically, based on simulated driving with a variety of gear ratios, data (shown in 

figure 5) revealed that drivers preferred the two sVGR systems over fixed ratio systems. Similar 

to work from a decade earlier (Olson & Thompson, 1970), differences were seen in terms of 

driver-perceived ease of use, vehicle responsiveness, and magnitude of steering movements 

required to induce a change in heading direction. 

Figure 4. Experimentally observed yaw gain as a function of vehicle speed, for both variable 

steering ratio (steer-by-wire) and fixed ratio (conventional vehicle). (Image adapted 

from Huang et al., 2004.) 

Overall, it appears that the appropriate selection of a shaping function requires consideration of 

two primary factors, including the operational range (throw) allowed by the HMI as well as the 

vehicle speed and lateral acceleration. Although each type of VGR system (sVGR, nVGR) has 

been predicted and/or shown to be associated with limited improvements, it seems that the 

evidence suggests their combination may lead to even greater benefits. Yet, the discussion to this 

point leads to another, more complex issue that must also factor into engineering decisions 

regarding the selection and specification of the shaping function. That is, it appears as if all the 

previous work has had to contend with and has been limited by inter-individual variability in terms 

of the driving style, expectations, and perceptions of human operators. That is, in addition to 

varying by speed and range of steering input, it is likely that the optimal shaping function will 

need to vary according to the driver and/or the vehicle response desired for execution of a 

particular maneuver or task. 
16 

Figure 5. Results from simulated driving with a variety of gear ratios: (A) depicts the “shaping functions” for the 

five different gear ratios tested (three fixed: 6, 13, 20 and two variable: linear and nonlinear 20-6:1). The 

remaining graphs represent driver ratings of each gear ratio based on perceived ease of control (B), vehicle 

response on fast movements (C), and required steering angle (D). (Images are adapted from Schulze, 1981, 

p. 339, figure 1.) 

6.3 Considerations of Variability Attributable to Task and Individual Operator 

Differences 

Clearly, as the preceding discussion has emphasized, the types of maneuvers to be performed 

impact the desired response characteristics of the vehicle and thus weigh heavily as considerations 

for the development of an appropriate shaping function. As has been emphasized throughout this 

discussion, the relative success of a given driving maneuver will be determined by both the execution speed and HMI input. For example, parallel parking is a low-speed, large motion maneuver 

in which the steering wheel is often turned more than 180 degrees. Lane keeping, on the other 

hand, can be high speed and only requires small movements of a steering wheel that are on the 

order of 5 to 10 degrees. Yet, vehicles are not always handled in these “typical” manners. Highspeed maneuvers can require sudden onset, large steering input that would benefit from a more 

direct gear ratio. Examples of high-speed maneuvers include avoiding obstacles, responding to 

unexpected environmental disturbances (e.g., lateral wind gusts), or executing intentional extreme 
17 

motions (e.g., evasive cornering). The real possibility of needing the capacity to perform such 

infrequent (and often risky) maneuvers provides an interesting instance in which active control 

systems with “intelligent” specification of the shaping function might actually cause control 

difficulties. 

Because the emphasis of most development efforts in the domain of intelligent control systems is 

to maintain performance within a large margin of vehicle safety limits, accounting for extreme 

maneuvering capabilities tends to be of lower priority. As a result, it is possible that situations 

may arise when an otherwise skilled driver attempts to provide input that conflicts with the 

intelligent control system in a catastrophic manner. Tongue (2005) described this potential 

problem through the example of professional race drivers who are required to push their vehicles 

to physical limits while executing frequent and rapid transitions between high- and low-speed 

states. Consider, for example, how racers have to navigate turns; usually, the approach occurs at 

the high speed used through the straightway, followed by a purposeful, discrete, and sudden 

application of the brakes to manage the turn and then a quick acceleration as the turn is completed 

to resume the race. The problem exists in that the speed at which this task unfolds is high, and 

thus the duration over which the rapid cycling between low and high speeds is rather short. 

Therefore, if standard sVGR principles were implemented, the driver would be challenged to pilot 

the vehicle through the turn, based on a steering ratio that was suddenly much more direct than that 

which s/he was acclimated to just milliseconds before, amplifying the vehicle response to steering 

input and quite possibly causing the driver to enter a dangerous (and potentially fatal) oversteering 

situation. The converse could also be true for a rapid low to high speed transition. This example 

illustrates just one of many potential situations in which skilled driving actions will conflict with 

most of the steady state assumptions on which intelligent steering systems are built. Although it is 

not assumed that military drivers would be intentionally racing their vehicles, an appropriate 

solution for relating driver input to vehicle output will need to consider the various types of 

atypical and risky driving maneuvers that could be encountered. Perhaps a potential solution 

would involve the implementation of a mode toggle that allows the driver to switch between 

shaping functions that are tailor-made for various possible control scenarios and tasks, such as 

evasive maneuvering versus lower speed off-road reconnaissance driving. 

Aside from control variations attributable to task factors are variations brought about by the 

intrinsic variability between and within human operators. It is quite possible that the particular 

driving style adopted by one operator could vary according to (a) the information used as feedback 

for steering decisions (Huang et al., 2004); (b) the aspect of vehicle behavior that the driver 

prioritizes for optimization/minimization during movement (Limpibunterng & Fujioka, 2004); 

(c) the level of experience with the vehicle, HMI or driving in general (Andonian et al., 2003); or 

(d) simply the intrinsic neuromotor dynamics of the person (Riley & Turvey, 2002). In a human 

factors study of simulated driving via a joystick, for instance, Andonian and colleagues observed 

that their pattern of results varied considerably with the level of driving experience of each of their 

participants; those who were least experienced tended to show greater performance differences 
18 

between a standard steering wheel and a joystick, whereas those with the greatest amount of 

experience tended to perform well regardless of the specific HMI they used. Modeling efforts 

such as those of Limpibunterng and Fujikoa have demonstrated that with sufficient study and 

human-vehicle system identification efforts, it is feasible to develop implementations that account 

for such individual differences with configurable control system parameters. Other approaches, 

such as the active, cable-type EPS system discussed earlier (Sakai et al., 2004), have shown that it 

is also possible to design systems that are relatively robust to individual differences in certain 

human response variables, such as the operator reaction time. 

Perhaps the most critical step toward improving control in VGR systems will likely come as 

systems researchers and designers gain an increasingly comprehensive understanding of the 

intricate relationships between the sources of variability. That is, it is very likely that constructs 

such as “driving style” are not best conceived as static personality characteristics of an individual 

driver but can vary according to other characteristics of that driver, such as level of experience 

with a given platform, basic neuromotor control capabilities, level of fatigue, and other factors. 

In addition, environmental variables can and do interact with vehicle performance in terms of 

sensor performance, surface traversibility, presence of potentially crippling hazards, and so on. 

Finally, the vehicle’s dynamics are changed as a result of how the driver drives the vehicle. 

Better understanding of these types of interactions between driver environment and vehicle 

will continue to push the refinement of control systems to greater levels of sophistication. 

7. Summary 

Modern vetronics technology is at the forefront of U.S. Army efforts to establish an unparalleled 

future force that increases effectiveness while reducing the costs of military engagement. As such, 

the need for solutions to the technologic challenges that are slowing the advancement of intelligent 

systems has become critical. This review was intended to examine performance issues associated 

with the shaping function that defines the vehicle response to steering input. The overall purpose 

of our efforts is to support the identification of design parameters critical to improving the 

implementation of by-wire systems within military tactical vehicles and ultimately, to optimize 

system performance for execution of secure mobile operations. 

Among the issues associated with the selection of an HMI appropriate to control specialized 

military vehicles is the relationship between vehicle motion and the operator’s ability to control 

that motion. Main factors affecting the ability of the operator to control vehicle motion in by-wire 

implementations include the overall range of motion (throw) of the HMI, the relationship of 

angular displacements specified through the device and the response of the vehicle, and modifications of this relationship because of vehicle motion characteristics (speed, lateral acceleration). 

Variations in driver-vehicle performance are a consequence of dynamic characteristics of the 
19 

operator, the vehicle, and most importantly, their interaction. If nothing else, this review has 

clearly depicted the shaping function as a central component of influence over system 

performance. Moreover, it is apparent that no single shaping function will suffice across all 

driving scenarios. For instance, as the basis of an nVGR system, a shaping function that is 

constant across vehicle speed is unlikely to be as robust as one that has sVGR characteristics. 

Figure 6 provides an example of how both speed and input angle could be accounted for with a 

dynamic shaping function, effectively inte-grating nVGR with sVGR characteristics (Andonian et 

al., 2003). Based on the current review, it appears as if the ideal shaping function would not only 

vary according to HMI input angle and vehicle speed but would also adapt appropriately to 

lateral/yaw accelerations as well as the task for which the current vehicle is being used. 

Figure 6. Joystick sensitivity as a function of joystick angle and simulated speed. (Image adapted 

from Andonian et al., 2003, figure 6, p. 5.) 

8. Conclusions and Future Directions 

To date, vehicle control characteristics and how they impact operator performance in secure 

mobile operations remain a primary focus of the collaborative program at TARDEC and ARL. 

Thus far, a small number of well-controlled studies have begun to disentangle the web of issues 

underlying the optimization of driver-vehicle performance for military tasks. Early efforts 
20 

identified minimum linear steering ratios during certain high-speed tasks such as lane keeping and 

during a double lane change (McDowell, Paul, & Alban, 2007). Careful design decisions are 

needed since driver performance remains compromised at higher vehicle speeds and when 

nonstandard HMI devices, such as joysticks, are implemented. The results of the experimental 

studies that have been completed thus far are providing important information specific enough to 

facilitate the establishment of design guidelines for intelligent military vehicles. Further research 

is needed to extend the current understanding so as to establish how steering control must be 

varied through an adequately defined shaping function to identify solutions for performance issues 

that persist beyond those that can be addressed through the shaping function. 

However, understanding shaping function solutions will not, on its own, be sufficient in our goal 

of improving and optimizing driver performance. A number of other important areas of by-wire 

systems and human performance continue to justify examination. In particular, research needs to 

build toward increasingly sophisticated solutions to the problems of vehicle control that incorporate 

many of the technologies that have fostered advancements within the civilian automotive industry. 

Four areas for future research that we have identified as particularly relevant include 

• Assessing the utility of force feedback to the operator through the HMI in order to facilitate 

a “natural steering feel” as if the vehicle were actuated through mechanical linkages; 

• Determining an appropriate means for compensating the lag in information flow between 

driver input at the HMI and feedback regarding vehicle motion, for example, inclusion of 

augmented visual displays that indicate predicted vehicle motion based on current state and 

input; 

• Determining a means for compensating biodynamic feedthrough to minimize unintended 

steering inputs, for example, incorporation of sensors measuring physical displacements of 

the operator and subtracting from the command input those elements attributable to 

vehicle-induced motion; 

• Facilitating ease of operator interaction with an ergonomic work station while decreasing 

physical and cognitive workload. 

Although dramatic strides are being made through research in automotive technology, advanced 

telerobotics, and autonomous control systems, the continued integration of these advancements 

with military applications presents challenges that are yet to have any clear solution. Despite the 

need for continued research and development, observations of current by-wire implementations 

within military test bed vehicles remain encouraging and the clear potential for future functionality 

in secure mobile operations becomes increasingly apparent with each insight gained through 

careful experimentation. 
21 

9. References 

Ackermann, J. Active Steering For Better Safety, Handling, and Comfort. In Advances in 

Vehicle Control and Safety (pp. 1-10), 1998. 

Ackermann, J.; Bunte, T. Yaw Disturbance Attenuation by Robust Decoupling of Car Steering. 

Control Engineering Practice 1997, 1131-1136. 

Allen, T. J.; Proske, U. Effect of Muscle Fatigue on The Sense of Limb Position and Movement. 

Experimental Brain Research 2006, 170, 30-38. 

Andonian, B.; Rauch, W.; Bhise, V. Driver Steering Performance Using Joystick vs. Steering 

Wheel Controls. In SAE 2003 World Congress & Exhibition (pp. 1-12). Warrendale, PA: 

Society of Automotive Engineers Inc, 2003. 

Azzalini, M.; Gissinger, G. L.; Boussouar, V.; Coutant, P. Computation of a Variable Steering 

Ratio With a Fuzzy Logic Method. In IV'2002 IEEE Intelligent Vehicle Symposium (pp. 

259-267), 2002. 

Chiappero, A.; Back, D. Driving by Wire. Design News 2002, October 7, 84-88. 

DeMeis, R. BMW Opts for Hybrid Steering System. Design News [On-line]. Retrieved, 1-2-

2008, from http://www.designnews.com/article/CA330639.html, 2003. 

Fowler, D. Down to the Wire. The Engineer 2003, 29-30. 

Huang, P.; Smakman, H.; Guldner, J. Control Concepts For Lateral Vehicle Guidance Including 

HMI Properties. In 2004 IEEE International Conference on Systems,Man,and Cybernetics

(pp. 1-6), 2004. 

Jagacinski, R. J.; Flach, J. M. Control Theory For Humans: Quantitative Approaches To 

Modeling Performance. Mahwah, NJ: Lawrence Erlbaum Associates, 2002. 

Kasselmann, J.; Keranen, T. Adaptive Steering. Bendix Technical Journal 1969, 2, 26-35. 

Kelber, C. R.; Webber, W.; Gomes, G. K.; Lohmann, M. A.; Rodrigues, M. S.; Ledur, D. Active 

Steering Unit With Integrated ACC Of X-By-Wire Vehicles Using A Joystick As H.M.I. In 

2004 IEEE Intelligent Vehicles Symposium (IEEE Cat. No.04TH8730) (pp. 173-177), 2004. 

Keller, J. Vetronics Of The Future Combat System. Military & Aerospace Electronics [Online]. Retrieved, 12-11-2007, from 

http://mae.pennnet.com/Articles/Article_Display.cfm?ARTICLE_ID=213965, 2004. 

Limpibunterng, T.; Fujioka, T. Bilateral Driver Model For Steer-By-Wire Controller Design. 

Vehicle System Dynamics 2004, 41, 381-390. 
22 

Mammar, S.; Sainte-Marie, J.; Glaser, S. On The Use Of Steer-By-Wire Systems In Lateral 

Driving Assistance Applications. In 10th IEEE International Workshop on Robot and 

Human Interactive Communication, 2001. 

McDowell, K.; Nunez, P.; Hutchins, S.; Metcalfe, J. S. Secure Mobility and the Autonomous 

Driver. IEEE Transactions on Robotics 2008, Manuscript accepted for publication. 

McDowell, K.; Oie, K. S.; Tierney, T. M.; Flascher, O. M. Addressing Human Factors Issues 

For Future Manned Ground Vehicles (MGVs). Army AL&T, Jan - Mar, 20-23, 2007. 

McDowell, K.; Paul, V.; Alban, J. Reduced Input Throw and High-Speed Driving. In Driving 

Simulation Conference - North America 2007. 

McGovern, D. E. Technology Assessment For Command and Control of Teleoperated Vehicles; 

Rep. No. SAND87-1225; Sandia National Labs: Albuquerque, NM, 1987. 

Olson, P. L.; Thompson, R. R. The Effect of Variable-Ratio Steering Gears on Driver 

Preference and Performance. Human Factors 1970, 12, 553-558. 

Östlund, J.; Peters, B. Manoeuverability Characteristics of Cars Operated by Joysticks; Rep. 

No. VTI report M860A; VTI Swedish National Road and Transport Research Institute: 

Linköping, SE, 1999. 

Parasuraman, R.; Riley, V. Humans and Automation: Use, Misuse, Disuse, Abuse. Human 

Factors 1997, 39, 230-253. 

Parasuraman, R.; Sheridan, T. B.; Wickens, C. D. A Model for Types and Levels of Human 

Interaction with Automation. IEEE Transactions on Systems Man and Cybernetics Part A - 

Systems and Humans 2000, 30, 286-297. 

Parikh, S. P.; Grassi Jr., V.; Kumar, V.; Okamoto Jr., J. Integrating Human Inputs with 

Autonomous Behaviors On An Intelligent Wheelchair Platform. IEEE Intelligent Systems 

2007, 22, 33-41. 

Peters, B.; Östlund, J. Joystick Controlled Driving for Drivers with Disabilities; Rep. No. VTI 

Report R506A; VTI, Swedish National Road and Transport Research Institute: Linköping, 

SE, 2005. 

Plamondon, R.; Alimi, A. M. Speed/Accuracy Trade-Offs in Target-Directed Movements (W 

Open-Peer Commentary). Behavioral and Brain Sciences 1997, 20, 279-349. 

Rajamani, R.; Zhu, C. Semi-Autonomous Adaptive Cruise Control Systems. IEEE Transactions 

on Vehicular Technology 2002, 51, 1186-1192. 

Riley, M. A.; Turvey, M. T. Variability and Determinism in Motor Behavior. Journal of Motor 

Behavior 2002, 34, 99-125. 
23 

Rossetter, E. J.; Switkes, J. R.; Gerdes, J. C. Experimental Validation of the Potential Field 

Lanekeeping System. International Journal of Automotive Technology 2004, 5, 95-108. 

Sakai, K.; Yoneda, A.; Shimizu, Y. Proposal on Variable Gear Ratio Characteristics of CableType EPS with Active Torque Control in Over-Steer Situation. Vehicle System Dynamics 

2004, 41, 192-201. 

Sawyer, C. Nearly Steer-by-Wire. Automotive Design and Production [On-line]. Retrieved, 1-

2-2008, from http://www.autofieldguide.com/columns/1103pb.html, 2003. 

Schmidt, R. A.; Lee, T. D. Motor Control and Learning: A Behavioral Emphasis. (3 ed.) 

Champaign: Human Kinetics, 1999. 

Schulze, B. G. The Application of Ergonomic Principles in the Design of Operating Controls. 

In D. J. Oborne & J. A. Levis (Eds.), Human factors in transport research. Transport 

systems, workspace, information and safety (pp. 337-344). London: Academic Press, 1981. 

Sellner, B.; Heger, F. W.; Hiatt, L. M.; Simmons, R.; Singh, S. Coordinated Multiagent Teams 

and Sliding Autonomy for Large-Scale Assembly. Proceedings of the IEEE 2006, 94, 1425-

1444. 

Seow, S. C. Information Theoretic Models of HCI: A Comparison of the Hick-Hyman Law 

And Fitt's Law. Human-Computer Interaction 2005, 20, 315-352. 

Sheridan, T. B. Telerobotics, Automation, and Human Supervisory Control. Cambridge, MA: 

The MIT Press, 1992. 

Sheridan, T. B. Space Teleoperation Through Time Delay: Review and Prognosis. IEEE 

Transactions on Robotics and Automation 1993, 9, 592-606. 

Shoemaker, C.; Bornstein, J.; Myers, S.; Brendle, B. Demo III: Department Of Defense Testbed 

For Unmanned Ground Mobility. In Proceedings of SPIE: AeroSense Session on Unmanned 

Ground Vehicle Technology (Ed.), 1999. 

Sirouspour, M. R.; Salcudean, S. E. Robust Controller Design for Cancelling Biodynamic 

Feedthrough. In B. Siciliano & P. Dario (Eds.), 8th International Symposium ISER02 (pp. 

123-135). Berlin Heidelberg, Germany: Springer-Verlag, 2003. 

Sövényi, S.; Gillespie, R. B. Cancellation of Biodynamic Feedthrough in Vehicle Control Tasks. 

IEEE Transactions on Control Systems Technology 2007, 15, 1018-1029. 

Stanton, N.; Marsden, P. Drive-By-Wire Systems: Some Reflections on the Trend to Automate 

the Driver Role. Proceedings of the Institution of Mechanical Engineers -- Part D -- Journal 

of Automobile Engineering 1997, 211, 267-276. 

Stanton, N.; Young, M. S. Vehicle Automation and Driving Performance. Ergonomics 1998, 

41, 1014-1028. 
24 

Todorov, E.; Jordan, M. I. Optimal Feedback Control as a Theory of Motor Coordination. 

Nature Neuroscience 2002, 5, 1226-1235. 

Tongue, B. Two Brains, One Car - Actively Controlled Steeering. IEEE Control Systems 

Magazine 2005, 5, 14-16. 

Treffner, P.; Barrett, R.; Petersen, A. Stability and Skill in Driving. Human Movement Science 

2002, 21, 749-784. 

Walker, G. H.; Stanton, N. A.; Young, M. S. The Ironies of Vehicle Feedback in Car Design. 

Ergonomics 2006, 49, 161-179. 

Walsh, L. D.; Hesse, C. W.; Morgan, D. L.; Proske, U. Human Forearm Position Sense After 

Fatigue of Elbow Flexor Muscles. The Journal of Physiology 2004, 558, 705-715. 

Wickens, C. D.; Hollands, J. Engineering Psychology and Human Performance. (3 ed.) New 

Jersey: Prentice Hall, 2000. 

Wohl, J. G. Man-Machine Steering Dynamics. Human Factors 1961, 3, 222-228. 

Yih, P.; Gerdes, J. C. Modification of Vehicle Handling Characteristics Via Steer-By-Wire. 

IEEE Transactions on Control Systems Technology 2005, 13, 965-976. 
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