Human-Centered Design of an Acc-With-Braking and Forward-Crash-Warning System

Fancher, Paul S.; Bareket, Z; Ervin, R D

doi:10.1076/vesd.36.2.203.3557

Cited by 77 publications

(28 citation statements)

References 4 publications

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“…These THW consequences are all within a safety margin to react to unexpected events (Hoedemaeker, 2000;Fancher et al, 2001). TTC, sampled at the end of each failure, indicates the collision likelihood if the vehicles maintained the same velocities.…”

Section: Adaptive Cruise Controlmentioning

confidence: 99%

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Making adaptive cruise control (ACC) limits visible

Seppelt

Lee

2007

International Journal of Human-Computer Studies

203

104

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Previous studies have shown adaptive cruise control (ACC) can compromise driving safety when drivers do not understand how the ACC functions, suggesting that drivers need to be informed about the capabilities of this technology. This study applies ecological interface design (EID) to create a visual representation of ACC behavior, which is intended to promote appropriate reliance and support effective transitions between manual and ACC control. The EID display reveals the behavior of ACC in terms of time headway (THW), time to collision (TTC), and range rate. This graphical representation uses emergent features that signal the state of the ACC. Two failure modes-exceedance of braking algorithm limits and sensor failures-were introduced in the driving contexts of traffic and rain, respectively. A medium-fidelity driving simulator was used to evaluate the effect of automation (manual, ACC control), and display (EID, no display) on ACC reliance, brake response, and driver intervention strategies. Drivers in traffic conditions relied more appropriately on ACC when the EID display was present than when it was not, proactively disengaging the ACC. The EID display promoted faster and more consistent braking responses when braking algorithm limits were exceeded, resulting in safe following distances and no collisions. In manual control, the EID display aided THW maintenance in both rain and traffic conditions, reducing the demands of driving and promoting more consistent and less variable car-following performance. These results suggest that providing drivers with continuous information about the state of the automation is a promising alternative to the more common approach of providing imminent crash warnings when it fails. Informing drivers may be more effective than warning drivers. r

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Section: Adaptive Cruise Controlmentioning

confidence: 99%

“…THW, TTC, and range rate indicate the distance (m) and speed (m/s) that defines the state of the two vehicles. These variables provide the basic information needed to control speed and distance in highway driving (Fancher et al, 2001). Each variable is mapped onto the display in the following manner (see Fig.…”

Section: Eid For Adaptive Cruise Controlmentioning

confidence: 99%

Making adaptive cruise control (ACC) limits visible

Seppelt

Lee

2007

International Journal of Human-Computer Studies

203

104

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“…As for what concerns the longitudinal control, the accelerations used in human driving may also be found in some previous studies of Adaptive Criuse Control (ACC) systems [39,40], while correlations between longitudinal and lateral acceleration are pointed out in other papers [28,[41][42][43]. The data collected and presented in the present work will be compared to this literature references in the following sections.…”

mentioning

confidence: 87%

On the human control of vehicles: an experimental study of acceleration

Bosetti

Lio

Saroldi

2013

Eur. Transp. Res. Rev.

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This paper presents an experimental investigation of human control of vehicles carried out on the basis of general theories on human movement. The longitudinal and lateral accelerations are studied, and their relations with theories of motor optimality principles, such as minimum jerk, minimum variance, and the two-thirds power law are highlighted. Data have been collected during the final experimental phase of the EU interactIVe project, in which a vehicle developed by Centro Ricerche Fiat has been used to demonstrate driver continuous support produced by an artificial codriver, within a shared initiative framework. 24 subjects drove the vehicle on a test route twice: once with the system active, the other with the system silent. The test route is composed of urban arterials, extra urban and motorway roads, and takes approximately 40-45 min to be driven. The total database thus amounts to~35 h of driving data recordings, for a total of 1.2 M samples per signal. Statistical summary data are presented, which describe human preferred accelerations, correlation between acceleration, curvature, and speed, and between longitudinal and lateral acceleration. Different driving modalities, corresponding to different motor strategies and primitives, are revealed. Comparisons with literature data are also made and discussed. The summary statistics may be useful for the design of future ADAS systems, and indeed they have been collected for the final tuning of the interactIVe co-driver.

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“…<1 s) where the following driver has to apply hard braking to avoid rear-end collisions. Many studies have been reported about ACC impacts on reducing rear-end collisions (Koziol et al, 1999;Touran, 1999;Fancher et al, 2001;Martin and Burgett, 2001). In ICC FOT studies, field operation test data were input to Monte Carlo simulation model, and it was estimated that ACC can reduce rear-end collisions by 17% (Koziol et al, 1999).…”

Section: Safety Issuesmentioning

confidence: 99%