ResearchArticle A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays Yaiza Montero-Lamas , 1 Margarita Novales , 1 Alfonso Orro , 1 and Graham Currie 2 1 UniversidadedaCoruña,GroupofRailwaysandTransportationEngineering,ETSIngenierosdeCaminos,CanalesyPuertos, Elviña, 15071 A Coruña, Spain 2 Public Transport Research Group, Monash University, Melbourne, Australia Correspondence should be addressed to Yaiza Montero•Lamas; y.montero@udc.es Received 6 December 2022; Revised 3 April 2023; Accepted 24 April 2023; Published 11 May 2023 Academic Editor: Socrates Basbas Copyright © 2023 Yaiza Montero•Lamas et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tis paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed trafc to an exclusive bus lane, using a big data approach. Te main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many diferent situations with a high degree of spatial and temporal detail. Tese data allow ready adjustment of calculations to the specifc reality measured in each case. In this way, we propose a novel methodology of general application to estimate the potential passenger savings instead of using simulation or analytical methods already present in the literature. For that purpose, in the frst place, a travel time prediction model per vehicle trip has been developed. It has been calibrated and validated with a historical series of observations in real•world situations. Tis model is based on multiple linear regression. Te estimated bus delay is obtained by comparing the estimated bus travel time with the bus travel time under free•fow conditions. Finally, estimated bus passenger time savings would be obtained if an exclusive bus lane had been implemented. An estimation of the passenger’s route in each vehicle trip is considered to avoid average value simplifcations in this calculation. A case study is conducted in A Coruña, Spain, to prove the methodology's applicability. Te results showed that 18.7% of the analyzed bus trips underwent a delay exceeding 3 min in a 2,448 m long corridor, and more than 33,000 h per year could have been saved with an exclusive bus lane. Understanding the impact of diferent factors on transit and the benefts of a priority bus system on passengers can help city councils and transit agencies to know which investments to prioritize given their limited budget. 1. Introduction Improving bus systems to attract new users is essential to achieving more sustainable mobility. Trafc delay is a critical factor afecting bus travel time performance [1, 2]. As trafc in cities grows, trafc congestion will cause a rise in the number of transit vehicles required to maintain headway and, therefore, an increase in the operation costs [3]. Te increase in travel time for transit users will also result in ridership loss [2]. Advances in big data availability provide much potential to improve our understanding of trafc impacts on bus travel time [4]. Tis paper proposes a new methodology for calculating the delay in bus travel time due to general trafc, bus ridership, and accumulated rainfall. Furthermore, the methodology determines the bus user time savings that the implementation of a dedicated or exclusive bus lane (DBL) can generate. An accurate evaluation of these savings can only be made in before•and•after studies, but an estimation of its value is necessary for planning purposes. Analytical methods based on trafc theory or simulation studies can be used, but the proposed methodology, which has general applicability and is based on automatically collected big data sources, allows estimation for each corridor or street section employing real performance information in local conditions and confgurations. Tis methodology provides data on the efect of mixed trafc on the transit travel time and, consequently, on bus user time. Similarly, it quantifes the estimated savings and Hindawi Journal of Advanced Transportation Volume 2023, Article ID 4082587, 15 pages https://doi.org/10.1155/2023/4082587