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While Bus Rapid Transit (BRT) systems are widely implemented to enhance passenger mobility and reduce emissions, their implications for urban freight movement remain understudied. This paper presents a framework for evaluating the impacts of BRT infrastructure and policies on road freight emissions, bottlenecks, and shifts in freight movement patterns. The proposed framework is based on telematics big data and includes a data processing pipeline incorporating data fusion techniques to integrate GPS trajectories, freight vehicle characteristics, and fuel consumption data. The impact of BRT on edge-level emissions is evaluated with a proposed fuel disaggregation model. The framework analyzes shifts in freight origin–destination patterns due to BRT, with statistical validation through permutation testing. Additionally, the framework offers a novel Network-level Spatial–Temporal Freight Bottleneck Impact Index (NSTFBII) to quantify the impact of BRT on the topology of freight bottlenecks. A case study of the Boston Columbus Avenue BRT project is conducted with a month-to-month analysis and an interrupted time series analysis (ITSA) with a control corridor. The findings show that BRT lanes reduce freight flow and emissions, leading to fragmented bottleneck structures and decreased diversity in origin–destination (OD) pairs along the corridor. Additionally, changes in freight movement and emissions in adjacent corridors differ significantly from general traffic, with impacts more pronounced during construction than post-implementation. The findings provide insights for policymakers, offering recommendations that minimize the negative impact on freight while enhancing the benefits of BRT systems.
Ma et al. (Wed,) studied this question.