Highway Traffic Flow Simulation Under Accident Conditions Using Cellular Automata Model

Through cellular automata-based simulation of highway traffic flow under accident conditions, we can model various scenarios using different vehicle size ratios and traffic flow parameters to output traffic conflict metrics for road safety assessment. The implementation typically involves defining cell states (empty/occupied), velocity rules, and stochastic deceleration mechanisms to simulate vehicle interactions. By analyzing diverse traffic patterns and vehicle types, we can investigate congestion triggers and potential flow optimization strategies. The model incorporates accident simulation through localized rule modifications, such as forced stopping or reduced capacity cells. To enhance realism, integration with real-case data and historical accident statistics allows deeper analysis of traffic-incident correlations. Based on these simulations, we can propose effective safety measures—like dynamic speed limits or lane management algorithms—to reduce accident rates. Overall, cellular automata-based highway simulation provides valuable insights for traffic management systems, with code implementations often featuring grid initialization, neighbor state checks, and parallel state updates for efficient large-scale simulations.