Research Article
Machine Learning and Reverse Methods for a Deeper Understanding of Public Roadway Improvement Action Impacts during Execution
Table 9
Statics of AvgR and EBTI.
| Type | Case studies | Case Study I (I-66 W) | Case Study II (I-81 S) | Case Study III (I-64 W) | Mean of AvgR1 | Mean of EBTI 2 | Mean of AvgR | Mean of EBTI | Mean of AvgR | Mean of EBTI |
| Both | 0.9631 | 0.0648 | 1.0232 | 0.0102 | 0.5856 | 0.7084 | On-peak collision | 0.8877 | 0.2385 | 0.7975 | 0.3147 | 0.8186 | 0.1984 | Off-peak collision | 0.8557 | 0.2606 | 0.7552 | 0.2900 | 0.8596 | 0.1699 | On-peak improvements | 0.9362 | 0.0719 | 0.9498 | 0.0199 | 0.9451 | 0.0667 | Off-peak improvements | 1.0004 | 0.0696 | 1.0014 | 0.0202 | 0.9951 | 0.0612 | None | 1.0012 | 0.0688 | 1.0003 | 0.0249 | 1.0019 | 0.0515 |
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1Average of consecutive speed ratios, 2Extra Buffer Time Index.
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