The Role of the Speeding Fine Function on Driver Coordination on State Highways

Reed, Randal · 2001 · ROSA P / National Transportation Center (U.S.)

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Summary

This paper investigates the relationship between speeding fine structures and driver behavior, specifically aiming to determine how fine functions can be optimized to reduce the variance of highway speeds. The research is motivated by the consensus in transportation literature that variance in road speeds, rather than average speed, is a primary contributor to accident rates. While speed limits are the traditional policy tool, they are often ineffective at controlling speed heterogeneity. The study posits that adjusting the mathematical structure of speeding fines can serve as a more effective mechanism to coordinate driver speeds and improve safety without necessarily lowering average speeds. The methodology employs a theoretical model of driver behavior calibrated to empirical data from four states: Florida, Massachusetts, Vermont, and Washington. Drivers are categorized into two groups: those who minimize expected costs (economic factors) and those who choose speeds based on exogenous non-economic factors (e.g., risk aversion, vehicle limitations). For cost-minimizing drivers, the model calculates the optimal speed by balancing the value of time against the expected cost of a ticket, defined as the probability of being caught multiplied by the fine amount. The study simulates driver speed distributions under various fine functions, including current "base" fines, revenue-equivalent fines, and revenue-maximizing fines. The simulations assume drivers are risk-neutral regarding tickets and utilize quadratic forms for the fine functions to test political feasibility. The results demonstrate that the structure of the fine function significantly influences the distribution of road speeds. By altering the fine parameters, the model shows that it is possible to reduce the variance of speeds while maintaining mean-preserving distributions. The simulations compare the speed density graphs under current state laws against optimized fine structures, revealing that specific fine configurations can narrow the spread of driver speeds. The study highlights that current fine functions often fail to adequately penalize speeding in a way that aligns with safety goals, whereas optimized functions can better coordinate behavior. The findings suggest that fines can be designed to capture the social costs of speeding variance more effectively than current linear or complex state-specific schedules. The significance of this work lies in its proposal for a novel policy instrument to enhance highway safety. The paper concludes that speeding fines can be used as a tool to mitigate the heterogeneity in driver characteristics, thereby reducing accident risks associated with speed variance. It argues that this approach may improve safety without the economic costs associated with lowering speed limits. The study serves as a pilot investigation, recommending future empirical research to validate these simulation results and determine the practical implementation of optimized fine functions. It underscores the potential for economic incentives to shape driver behavior more precisely than traditional regulatory limits.

Key finding

Modifying speeding fine functions can reduce the variance of road speeds without drastically changing average speeds, offering a potential method to improve highway safety.

Methodology

modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• speed choice
• speed management