Dream-Based Classification of Driver Behavioural Patterns in Nigerian Road Traffic Accidents
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Road traffic accidents remain a leading cause of mortality and morbidity in Nigeria, yet structured analysis of the behavioral patterns underlying crash causation is largely absent from the literature. This study applies the Driver Reliability and Error Analysis Method (DREAM) to classify driver behavioral patterns from Nigerian road traffic accident records sourced from three national newspaper outlets. A total of 65 accident records were extracted, spanning all geopolitical zones and involving five vehicle categories: trucks (41.5%), buses (38.5%), cars (32.3%), three-wheeled vehicles (12.3%), and two-wheeled vehicles (3.1%). Each record was independently coded by two analysts using the DREAM taxonomy, identifying the observable driver critical events and its underlying causal behavioral and situational contributors. Cumulative DREAM charts were constructed for each critical event by accumulating causal pathways across the dataset. Too High Speed was the most prevalent, accounting for 41.5% of records, followed by Insufficient Force, 20.0%; Wrong Direction, 18.5%; No Action, 15.4% and Too Late Action 4.6%. Across all 65 records, 32 distinct genotype codes were identified. The dominant genotypes were Misjudgment of situation, n = 27; Habitually stretching rules, n = 26; Equipment failure, n = 25; and Inadequate vehicle maintenance, n = 24. 58.5% involved collisions with motorized counterparts and 10 (15.4%) involved non-motorized road users. The findings reveal that Nigerian road crashes are driven by a convergence of deliberate norm violation, cognitive misjudgment, driver skill deficits, and systemic vehicle maintenance failures, providing an evidence base for targeted road safety interventions in Nigeria and comparable low- and middle-income country contexts.
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