Sustainable public transportation using Markov Chains: Case study Hamburg public transportation

Purpose: Intelligent public transportation systems have been largely focused on improving the planning, and monitoring the transportation flows during recent years. Advancements in public transportation systems increase service levels and encourage more usage of public transportation. The forecast of buses' arrival time to stations and having a dynamic system to anticipate the real-time possible events for users, significantly increase passenger satisfaction. This paper has studied the literature considering dynamic public transportation systems and also matters of environmental emissions. Methodology: The paper has developed a method to predict bus arrivals at stations by considering the buses' operation parameters and variables with stochastic characteristics by applying Markov Chains. The paper also applied the assignment problem technique and multi-objective planning to enable a framework for public transportation resource assignment considering the perspectives mentioned earlier. Findings: The real data of Hamburg public transportation has been used to verify the capabilities of the platform. The findings show that the model validity of the platform and enabled effective strategic planning for public resource assignment. Originality: This paper has studied the related literature and discussed the considerable gap for proposing a dynamic public transportation system that brings satisfaction from the side of the users and also mutually minimizing environmental emissions

Public sustainable transportation planning with service level efficiency: Hamburg case study

Purpose: Public transportation in large cities has significant impacts on the environmental, social, and economical perspectives. However, the proper assignment of re-sources in public transportation creates paradoxical challenges since by increasing service level efficiency, the environmental criteria will be violated. This paper has studied the literature and discussed the considerable gap for the fulfillment of the mutual service level satisfaction and environmental emission considerations. Methodology: The paper has applied the well-known assignment problem tech-nique and multi-objective planning to propose a novel framework for public transportation resource assignment fulfilling the aforementioned perspectives mutually. The model is capable of analyzing the tradeoffs for increasing public service satisfactions and meanwhile to control the environmental emissions. Using the multi-objective analytical capabilities, the proposed model improves the overall citizens' satisfaction and also manage the operational costs related to the produced emission by transportation resources. Findings: The real data of Hamburg public transportation has been used to verify the capabilities of the proposed model. The findings first validate the model formulation and also gives insights for effective strategic planning for public resource assignment. The analysis emphasizes on establishing control mechanism for passenger's arrival rate as it affects both waiting times in bus stops and also the transportation vehicle weights which drastically affect the environmental factors. Originality: This paper has studied the related literature and discussed the gap for the mutual fulfillment of passenger's service level satisfaction using public transportation and also controlling environmental emissions of public transportation