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Crash cost estimates are essential for evaluating road safety management policies and assessing the economic benefits of safety improvements. Existing studies often rely on aggregated crash data, assuming an even distribution of incidents, which overlooks significant spatial variations influenced by road characteristics and traffic conditions. This research presents a methodological framework for link-based crash cost analysis that considers both internal and external costs, enabling detailed quantification at a localized level. By employing safety performance functions and ordered probit models, we estimate on-road crash rates by crash type and injury severity, distinguishing between internal costs borne by individuals involved in crashes and external costs that impact victims, insurers, and government agencies. This framework is applied to the Minneapolis-St. Paul metropolitan area for a proof-of-concept. Our findings reveal that the costs incurred by drivers are higher than those imposed on others, and that highways are generally safer than surface streets. However, these crash costs are too low compared to the value of travel time to significantly influence route choices, even when drivers are aware of these costs. To enhance effective decision-making, related policies should consider offering incentives for safe driving practices. Future research on the practical applications of this framework is encouraged to maintain a dynamic dataset that reflects ongoing changes in road safety conditions. [ABSTRACT FROM AUTHOR]

The American Sociological Association (ASA) used social science research and data informed approaches to engage community college faculty in the discipline.

This perspective paper analyzes selected policy strategies for transforming transport. It identifies four primary objectives: enhance economic efficiency, increase equity, reduce negative externalities, and improve the user experience (4Es). It then develops the framework of persuasion, police, purse, and platform powers (4Ps), which are available to governments to implement change and pursue their objectives. In a series of cases, it illustrates those powers, particularly the underappreciated platform powers, the formation and promulgation of standards, which are themselves the key technology for connecting institutions, showing how the establishment of technical standards transforms existing transport and lays the groundwork for new opportunities. [ABSTRACT FROM AUTHOR]

Objective: The prevalence of Driving Under the Influence (DUI) of alcohol or drugs has become a prominent factor in the occurrence of severe road crashes worldwide. Driving often occurs after visiting, and presumably drinking, at Alcohol-Serving Establishments (ASEs), and is thus of interest as a possible source of DUI events. Methods: We apply statistical and machine learning models to the Victorian Integrated Survey of Travel and Activity (VISTA) to identify factors that contribute to driving in trips from ASEs in Australia's state of Victoria. Results: Our results highlight that approximately 10% of individuals who traveled to ASEs as car passengers switched to driving after leaving there. It was also observed that travel distance shorter than 1 km and activity duration between 3 and 4 h positively impacts the mode switching from car driver to other modes in ASEs trips. Further findings illustrate a decline in driving after midnight, with an increase in the use of public transport and taxis. Individuals prefer driving for long-distance ASEs trips and walking for short distances. Going home also increased the likelihood of driving, whereas engaging in other social activities did not. Longer stays at ASEs and leaving vehicles overnight reduce the propensity to drive, likely due to increased alcohol consumption during these times. Conclusions: These findings suggest behavioral adjustments that can mitigate driving under the influence. Specifically, people may walk for short-distance trips and use public transport or taxis for longer ASEs trips. [ABSTRACT FROM AUTHOR]