Automated Fare Collection (AFC) System

Posted: August 27th, 2021

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Automated Fare Collection (AFC) System

Managing public transport is one of the most critical challenges facing large cities. The use of substandard vehicles can cause pollution, hence not safe (Monsalve et al. 12). Therefore, there is an urgent need for public transport companies to provide less complex and user-friendly services. The Automatic Fare Collection System (AFC) is a critical factor for ensuring high-quality and sustainable urban transport services (Green et al. 17). Further, it significantly improves the interaction between transport services and users. Hence, the data collected using the Automatic Fare Collection (AFC) would provide benefits to operators besides being utilized in several ways to improve all traffic performance.

Data Description

The distribution of passenger traffic in an urban network plays a vital role in analyzing passenger traffic, which forms urban operations. The traditional bus delivery model is becoming more complex and inefficient. Hence, the need to develop an algorithm for implementing this procedure and apply it to service provider data. The data is integrated into the automated vehicle status system, which records each passenger’s transactions on the bus. Hence, detailed information captured includes detailsabout the route, vehicle, travel card, and the start time and place.

Methodology

The methodology describes methods utilized in estimating passenger trips based on data from an automatic fare collection system. A new spatial recognition feature has been proposed to improve the accuracy of targeting results and test the underlying parent and target hypotheses in subsequent literature. Therefore, this method only applies to system configurations of items with a distance-based pricing structure. Its purpose is to optimize the raw automatic fare collection data for individual trips.

Estimation of Results

Individual journeys are registered, and tickets can be verified on board. However, this method’s new seat authentication features can also be included. Consequently, it was concluded that the classification method is useful in assessing destinations at the classification level and can identify reliable false alarms.

Implications of Findings

The routes that connect the destination and origin are related to the observed transit time and the pure transit time. This information is a timeline inserted from the automated fare collection data. The extractor is used to activate clusters between the new pure and observed transit time cluster algorithm, including specified destination and origin pairs. Hence, in addition to the original application, it also provides a way to determine the maximum theoretical accuracy.

Conclusion

Automated fare collection is a solution that can automate ticket or fare systems in the transport sector. Therefore, this solution improves the efficiency and effectiveness of ticketing system transactions. By installing an automated fare collection system, the traffic administration can provide better services to end-users.

Work Cited

Barry, James J., et al. “Origin and destination estimation in New York City with automated fare system data.” Transportation Research Record 1817.1 (2002): 183-187.

Green, Julie, et al. “Automated fare collection system.” U.S. Patent No. 6,957,772. 25 Oct. 2005.

Krishna, A. S., et al. “Automatic Fare Collection System for Public Transport Corporation Using Fingerprint Recognition with UIDAI.” 2019 IEEE International Conference on Electrical, Computer, and Communication Technologies (ICECCT), 2019.

Monsalve, Maria Carolina, et al. Public transport automatic fare collection interoperability assessing options for Poland. No. 107014. The World Bank, 2016.