A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays

This paper presents a new method to quantify the potential user time savings if urban bus is given preferential treatment, changing from mixed traffic an exclusive lane, using big data approach. The main advantage of proposal use high amount information that automatically collected by sensors and management systems in many different situations with degree spatial temporal detail. These allow ready adjustment calculations specific reality measured each case. In this way, we propose novel methodology general application estimate passenger instead simulation or analytical methods already present literature. For purpose, first place, travel prediction model per vehicle trip has been developed. It calibrated validated historical series observations real-world situations. based on multiple linear regression. estimated delay obtained comparing under free-flow conditions. Finally, would be lane had implemented. An estimation passenger’s route considered avoid average value simplifications calculation. A case study conducted Coruña, Spain, prove methodology's applicability. results showed 18.7% analyzed trips underwent exceeding 3 min 2,448 m long corridor, more than 33,000 h year could have saved lane. Understanding impact factors transit benefits priority system passengers can help city councils agencies know which investments prioritize their limited budget.