Collaboration Decision Methods For Disruption Recovery Service In Public Tram Systems

Trams are playing increasingly important role in today’s public transport systems, as they are punctual, convenient, and friendly to the environment. However, this above-ground light-rail system is prone to disruptions caused by unexpected events such as track misalignment, parking violation, power outage, and natural disasters, which result in inconvenience to passengers and reduced service levels. It is therefore vitally important to have effective disruption handling procedures in place to ensure high-quality passenger service.This research is inspired by the tram systems in several cities in three countries (Boston and San Francisco of the US, Berlin and Munich of Germany, and Dalian, Shanghai of China) with respect to their methods for providing quick recovery service during unplanned disruptions. Our direct communications with several tram operators have revealed that the tram systems’ acutest challenge is to respond to short-term, unplanned disruptions that require real-time and fast recovery decisions. How to provide quick recovery service during tram system disruptions? The research in this area is sparse, and yet the topic is of both of practical and research importance.With concentration on the short-term unplanned disruption, we focused on three replacement tools, namely taxi-only, bus-only and hybrid way, and two strategies which is one-time collaboration and long-term contract based relationship. The study is explored from the following four areas.(1) First of all, we portray a broad sculpture from the worldwide view of tram systems, disruption events, mitigation strategies under use after our survey and investigation in typical regions and cities as Munich, Berlin in German, San Francisco and Boston in USA, and Dalian, Shanghai in China. After comparisons, the issues and key factors involving the decision problems are concluded based on which lead to our research bodies in the following chapters.(2) The one-time typical decision progress in tram company’s disruption recovery is investigated. The models are built for tram recovery service and focused on when to collaborate with the taxi/bus company and how to compensate the recovery service, considers three recovery service methods—taxi rescuing, bus replacement service and taxi-bus hybrid service, and aims to identify the conditions under which one method may be more appropriate than the others. In particular, we investigated the passenger behavior, the additional cost for collaborated taxi or bus companies with the capacity ability constrained are considered, and the measurement of disruption effect, service level and tram company’s benefit. Moreover, we have conducted plenty of new numerical experiments and sensitivity analyses to generate more guidelines for decision making.(3) A long-term contract is designed for the tram company to reserve a number of taxis/buses or both in advance to guarantee the capacity when short-term unplanned disruption happens. The involving parties’decision functions have been developed taking into considerations of the passengers’behaviors, the taxi/bus company’s standby and service costs, and the tram company’s losses, and individual optimal solutions can be derived and obtained from their own decision functions. Additionally, the negotiation process between two individual companies to achieve an agreed-upon number of reserved taxis has been studied. A series of hypothetical numerical and sensitivity studies have been conducted to generate numerous insights that help guide the tram company in decision-making.(4) Finally, for better understanding the models and strategies, we compare the performance of the contract and no-contract strategies. Practically, the real-world cases of the tram system in Dalian China are discussed in order to provide valuable and detailed suggestion for the tram systems continuous running and efficient emergency handling in China.Theoretical speaking, the framework and methods innovated in our research contribute merits in combining the concepts between disruption management, collaboration, and behavior science, and provide quantitative decision tools for efficient system recovery of the public tram system which is tricky and full of uncertainty and complexity. From the practical level, the models, tools and the derived conclusions is applicable in multi regions, and provide plenty implications for efficient and real-time disruption mitigation which can improve the service quality, passengers’satisfaction and finally induce more and more people transfer its transit way to the comfortable and environmental tram lines.