Passenger bus industry weather information application.

Heppner, Paul; Bell, Brian; Orrego, Andres; Wise, Joshua; Pucci, Julian · 2011 · ROSA P / United States. Joint Program Office for Intelligent Transportation Systems

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Summary

This report details the development and findings of the Passenger Bus Industry Weather Information Application (PBI WxApp), a project sponsored by the U.S. Department of Transportation’s Federal Highway Administration (FHWA). The research addresses the significant impact of adverse weather on the passenger bus industry, which generates over $55 billion annually and facilitates hundreds of millions of trips. Weather-related hazards such as snow, ice, and fog compromise operational efficiency, occupant safety, and service costs. The primary objective was to create a software application that integrates mobile platform environmental observations with fixed-site data from airports (ASOS) and road-weather stations (Clarus system). This integration aims to provide drivers, dispatchers, and passengers with enhanced situational awareness along commercial vehicle routes, filling gaps in coverage where fixed-site equipment is absent. The application was developed by Global Science & Technology, Inc. using an iterative Agile software engineering methodology known as Scrum. The project involved three development sprints between November 2010 and March 2011. Data sources included the FHWA Clarus system, NOAA ASOS stations, and mobile platform data collected by Greyhound Bus Lines via the Mobile Platform Environmental Data (MoPED) system. The development process focused on integrating these disparate data streams into a web-based interface optimized for desktop and mobile displays. Key technical challenges included reconciling data attributes from different systems, such as varying definitions of temperature, and managing data conflicts when multiple sensors reported significantly different values for the same attribute. The final application displayed weather icons, maps, and detailed text descriptions of conditions along user-selected bus routes, with features prioritized based on stakeholder feedback regarding ease of use and relevance to high-impact weather events. The findings indicate that fixed-site station data are generally available and reliable, while mobile platform data, though limited during the development period, proved to be reliable and of good quality. The integration of mobile data provided a more complete "weather window" than any single source, offering dynamic insights into rapidly changing conditions like storms and precipitation. However, the study noted that data inaccuracies can occur across all reporting sites, and the application did not filter observations, passing data as reported by source systems. The development process highlighted the necessity of understanding metadata and reconciling attribute expressions from disparate systems to ensure accurate interpretation. Additionally, the application successfully linked to National Weather Service warnings, placing observational data within the context of broader forecasted hazards. The significance of this work lies in its demonstration of the viability of combining mobile and fixed-site data to improve road-weather forecasting and decision support. The PBI WxApp serves as a proof of concept for enhancing safety and operational efficiency in the passenger bus industry and potentially other transit sectors. The report recommends future developments, including the integration of mobile platform observations into the Clarus system, the highlighting of specific impact areas triggered by observational data, and the development of monitoring and notification tools. By providing more timely and accurate weather information, such applications can reduce weather-related accidents, delays, and economic disruptions, benefiting both commercial operators and the traveling public.

Key finding

Mobile platform data are reliable and provide a more complete weather window than any single source of data.

Methodology

other

Provenance

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

Topics

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• weather rain fog snow