Analytic Assessment of Collision Avoidance Systems and Driver Dynamic Performance in Rear-End Crashes and Near-Crashes

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dc.contributor.authorMcLaughlin, Shane Brendanen
dc.contributor.committeecochairNussbaum, Maury A.en
dc.contributor.committeecochairDingus, Thomas A.en
dc.contributor.committeememberHankey, Jonathan M.en
dc.contributor.committeememberSmith-Jackson, Tonya L.en
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2014-03-14T20:18:29Zen
dc.date.adate2007-12-10en
dc.date.available2014-03-14T20:18:29Zen
dc.date.issued2007-10-30en
dc.date.rdate2007-12-10en
dc.date.sdate2007-11-13en
dc.description.abstractCollision avoidance systems (CASs) are being developed and fielded to reduce the number and severity of rear-end crashes. Kinematic algorithms within CASs evaluate sensor input and apply assumptions describing human-response timing and deceleration to determine when an alert should be presented. This dissertation presents an analytic assessment of dynamic function and performance CASs and associated driver performance for preventing automotive rear-end crashes. A method for using naturalistic data in the evaluation of CAS algorithms is described and applied to three algorithms. Time-series parametric data collected during 13 rear-end crashes and 70 near-crashes are input into models of collision avoidance algorithms to determine when the alerts would have occurred. Algorithm performance is measured by estimating how much of the driving population would be able to respond in the time available between when an alert would occur and when braking was needed. A sensitivity analysis was performed to consider the effect of alternative inputs into the assessment method. The algorithms were found to warn in sufficient time to permit 50–70% of the population to avoid collision in similar scenarios. However, the accuracy of this estimate was limited because the tested algorithms were found to alert too frequently to be feasible. The response of the assessment method was most sensitive to differences in assumed response-time distributions and assumed driver braking levels. Low-speed crashes were not addressed by two of the algorithms. Analysis of the events revealed that the necessary avoidance deceleration based on kinematics was generally less than 2 s in duration. At the time of driver response, the time remaining to avoid collision using a 0.5g average deceleration ranged from â 1.1 s to 2.1 s. In 10 of 13 crashes, no driver response deceleration was present. Mean deceleration for the 70 near-crashes was 0.37g and maximum was 0.72g. A set of the events was developed to measure driver response time. The mean driver response time was 0.7 s to begin braking and 1.1 s to reach maximum deceleration. Implications for collision countermeasures are considered, response-time results are compared to previous distributions and future work is discussed.en
dc.description.degreePh. D.en
dc.identifier.otheretd-11132007-143951en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11132007-143951/en
dc.identifier.urihttp://hdl.handle.net/10919/29561en
dc.publisherVirginia Techen
dc.relation.haspartMcLaughlin_Dissertation_Final.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectcollision avoidanceen
dc.subjectalert algorithmen
dc.subjectreaction timeen
dc.subjectrear-end crashen
dc.subjectdriver decelerationen
dc.subjectfalse alarmen
dc.subjectvehicle brakingen
dc.subjectnaturalistic drivingen
dc.titleAnalytic Assessment of Collision Avoidance Systems and Driver Dynamic Performance in Rear-End Crashes and Near-Crashesen
dc.typeDissertationen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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