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On the tradeoff between sensitivity and specificity in bus bunching prediction

Abstract Bus bunching resulting from initially small headway irregularities is a widely-known and studied problem. A variety of headway-prediction approaches, as well as corrective strategies, have been developed to identify and correct headway irregularity in real time. Instead of predicting an exact value for future headways, this study explores a probabilistic predictive methodology to forecast whether or not a bus will be bunched during its dwelling at a downstream stop, using a logistic regression model based on GPS records of buses at least k stops upstream to allow for sufficient time to possibly implement control strategies. A case study is conducted on a circular bus route in Kyoto City. Compared to two headway-based prediction approaches using linear regression and support vector machine, the superior performance of the proposed tool in detecting bunching is illustrated by Receiver Operator Characteristic (ROC) analysis. The high reliability in long-term prediction gives adequate time for operators to employ countermeasures. Besides, the proposed method provides operators with tradeoff options. We find that a bunching-averse operator can obtain 95% “sensitivity”, that is the ratio of correctly identified bunching events, at the cost of decreasing “specificity”, which is the ratio of correct non-bunching predictions over all events. This is true even if the prediction horizon is more than 10 stops.