The Use of Connected Vehicle Technology To Facilitate Multimodal Winter Travel (Phase I)

Akin, Michelle; He, Yaqin; Shi, Xianming · 2018 · ROSA P / University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education

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Summary

This report addresses the challenge of maintaining safety and mobility in multimodal transportation systems during winter weather events, which cause over 300,000 crashes annually in the United States. The research investigates how Connected Vehicle (CV) technology can enhance winter travel by providing real-time, location-specific road weather data and improving situation awareness for drivers, transit operators, and vulnerable road users like pedestrians and cyclists. The study aims to identify operational scenarios where CV data can supplement existing Road Weather Information Systems (RWIS) and support decision-making for roadway maintenance and traveler advisories. The methodology comprised a comprehensive literature review, a nationwide survey of transit agencies, and the development of a Concept of Operations (ConOps). The survey targeted transit operation managers and supervisors, yielding 15 effective responses from agencies across twelve states. Respondents were queried on the impacts of winter storms on operations, current communication methods, the utility of specific road weather data, and the potential benefits and concerns of CV applications. The ConOps chapter synthesized these findings to propose two primary applications: integrating CV data into winter transit operations and disseminating multimodal travel advisories to commuters. Survey results indicated that snow build-up at stops and route delays were the most significant operational impacts of winter storms. While 93% of agencies currently use road weather information, primarily from forecast websites, respondents viewed CV-derived weather data as moderately to extremely useful for improving safety. Among specific CV technologies, pedestrian warning applications for transit vehicles and left-turn assistance warnings were rated as the most beneficial for winter conditions. However, respondents expressed significant concern regarding increased driver distraction, safety consequences of equipment failure, and system performance in poor weather. The proposed ConOps outlines a system where mobile sensors on fleet and private vehicles collect data via CAN-Bus and Automatic Vehicle Location (AVL), which is combined with fixed RWIS data. This processed information would be used by transit operators for route optimization and shared with commuters via smartphone applications to facilitate informed trip planning. The study concludes that CV technology offers a viable pathway to improve multimodal winter travel by filling data gaps between fixed weather stations and providing real-time hazard warnings. The findings lay the foundation for future research, specifically recommending pilot studies to evaluate the efficiency, costs, and benefits of implementing these CV applications in transit and bicycle/pedestrian contexts. By enhancing data connectivity between vehicles and infrastructure, the proposed solutions aim to reduce crash risks and improve the overall reliability of transportation networks during inclement weather.

Key finding

Transit agencies identified pedestrian warning and left-turn assistance as the most valuable connected vehicle applications for improving winter safety and mobility.

Methodology

survey

Sample size: 15

Provenance

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

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• v2x connected vehicle