Impact of ITS on CO ₂ emissions – the contribution of a standardised assessment framework

Wolfermann, Axel; Gade, Kay; Jonkers, Eline · 2015 · Crossref

DOI: 10.1049/iet-its.2014.0146

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Summary

This paper addresses the challenge of accurately quantifying the impact of Intelligent Transport Systems (ITS) on CO₂ emissions. While ITS are recognized for their potential to reduce the carbon footprint of traffic while improving mobility, their complex effects on transport demand and driver behavior make precise prediction difficult. The authors argue that a standardized, transparent assessment methodology is essential for developers, public authorities, and investors to make informed decisions and enable comparable impact estimates across different systems, transport modes, and geographical scales. To develop this framework, the authors conducted a comprehensive user needs assessment involving workshops, online surveys, and in-depth discussions with stakeholders ranging from ITS developers to policy makers. This process identified the requirement for a methodology that covers all surface transport modes (road, rail, inland waterways, and short sea shipping), all system types, and all spatial levels. The core of the proposed approach is a systematic analysis of "transport processes," which are divided into transport demand-related processes (e.g., trip generation, mode choice, route planning) and driver behavior/vehicle-related processes (e.g., speed, headway, driving dynamics). The framework maps how ITS influence these processes and the factors affecting them (such as infrastructure capacity and network load), ultimately leading to changes in traffic flow and CO₂ emissions. The paper details a qualitative assessment methodology applied to over 40 ITS systems to identify potential effects on these transport processes. This involved a literature review and consultations with 25 experts who rated the impact of specific systems on various parameters. The analysis revealed that ITS effects are highly dependent on system design and deployment context. For example, dynamic navigation systems were found to significantly influence route and departure time choices, though their impact on trip generation varied based on functionality. Road section control systems were shown to primarily affect speed, headway, and driving dynamics by promoting homogeneous traffic flow, though advisory limits had negligible impact. The qualitative assessment serves to identify which modeling approaches and data inputs are necessary for subsequent quantitative evaluation. The significance of this work lies in providing a structured foundation for a standardized assessment methodology, developed within the European Amitran project. By dissecting traffic into underlying processes and analyzing effect chains, the framework ensures transparency and helps determine model sensitivities. This approach allows for the comparison of different ITS measures and supports the integration of ITS into sustainable transport strategies. The authors conclude that while qualitative assessment directs attention to crucial effects, detailed quantitative modeling is required for reliable impact estimates, and the proposed framework facilitates the selection of appropriate models for such quantification.

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