Automated Generation of Traffic Incident Response Plan Based on Case-Based Reasoning and Bayesian Theory

<table>The <svg height="15.8375" id="M11" style="vertical-align:-0.1092pt" version="1.1" viewbox="0 0 17.4 15.8375" width="17.4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g transform="matrix(.012,-0,0,-.012,11.013,7.475)"><path d="M153 550l-26 -186q79 31 111 31q90 0 141.5 -51t51.5 -119q0 -93 -89 -166q-85 -69 -173 -71q-32 0 -61.5 11.5t-41.5 23.5q-18 17 -17 34q2 16 22 33q14 9 26 -1q61 -50 124 -50q60 0 93 43.5t33 104.5q0 69 -41.5 110t-121.5 41q-53 0 -102 -20l38 305h286l6 -8
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</svg> model of Case-Based Reasoning.</table>

Discrete Dynamics in Nature and Society

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Figure 1

Figure 1: Automated Generation of Traffic Incident Response Plan Based on Case-Based Reasoning and Bayesian Theory 