A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.Comment: arXiv admin note: substantial text overlap with arXiv:1912.0198

A user-operator assignment game with heterogeneous user groups for empirical evaluation of a microtransit service in Luxembourg

We tackle the problem of evaluating the impact of different operation policies on the performance of a microtransit service. This study is the first empirical application using the stable matching modeling framework to evaluate different operation cost allocation and pricing mechanisms on microtransit service. We extend the deterministic stable matching model to a stochastic reliability-based one to consider user's heterogeneous perceptions of utility on the service routes. The proposed model is applied to the evaluation of Kussbus microtransit service in Luxembourg. We found that the current Kussbus operation is not a stable outcome. By reducing their route operating costs of 50%, it is expected to increase the ridership of 10%. If Kussbus can reduce in-vehicle travel time on their own by 20%, they can significantly increase profit several folds from the baseline

Which service is better on a linear travel corridor: Park & ride or on-demand public bus?

This paper develops an analytical model to support the decision-making for selection of a public transport service (PTS) provision between park & ride and on-demand public bus (ODPB). The objective of the model is to maximise the total social welfare, which includes consumer surplus and operator’s net profit. The model is solved by a heuristic solution procedure and tested on an idealized linear travel corridor. The case study considers the effects from population density, density distribution, size of residential area, P&R station location, distance from the residential area to centre business area (CBD), as well as the changes of residential area layout and population growth. Results show that P&R fits for low population density area while ODPB is more suitable for high population density area. Population distribution type has little influence on the services’ social welfare. ODPB is a preferable service for the city which does not have advanced metro network. Besides, the investment time for building ODPB service in the planning horizon is discussed with consideration of the development of residential area

RURAL DEMAND RESPONSIVE TRANSPORT An overview of the Italian scenario and analysis of Antola-Tigullio inner area case study

Over time, a car-centred mobility system has contributed to the negative externalities that can be observed today in both urban and rural areas: congestion of transport infrastructures, air and noise pollution, reduced urban space for pedestrians and cyclists, lack of parks, etc. All this has led policy makers to find solutions to shift citizens from cars to public transport and other sustainable modes (walking and cycling). While in urban areas traditional public transport is often an already widespread and effective service that only needs to be transformed to build user confidence, in rural and mountainous areas, where low transport demand and long distances make it economically unviable, it needs to be integrated or completely replaced by innovative forms of mobility. One of the most valid solutions in this regard is on-demand transport technology, which allows transport providers to reduce their costs by rationalizing the supply (e.g. higher vehicles’ load factor) and population of these areas to improve their accessibility to public transport and abandon the use of the car. Over time, research has been done extensively in academic literature on the application of this technology in urban areas, but little has been undertaken in rural contexts: this PhD thesis aims to contribute to research in this field by studying the technical characteristics of these services in the Italian scenario, in order to provide decision-makers with useful information to counter the phenomena of depopulation and economic and social isolation of these territories. First, this paper provides a comprehensive literature review aimed at understanding the strengths and weaknesses of the DRT service in general and in its application in rural areas: from the description of its historical development, the close relationship between the diffusion of this tool and the phases of technological progress emerges. The central chapters of this thesis deal with an in-depth analysis of all rural DRT cases in operation in Italy in the last decade (both temporary and permanent), carried out through a web search, an analysis of the Program Framework Agreements of the Italian regions and sector agencies’ websites, as well as with the planning of some DRT services in the inner area of Antola-Tigullio (Liguria Region): this last work, carried out after an analysis of the socio-demographic data and the travel behavior of the population, helped to identify the best routes, time slots and target user groups to experiment with the DRT service. After 5 months of experimentation, it was possible to carry out an ex-post analysis of the initial results thanks to the data provided by the local Public Transport Authority (PTA), commissioner of the study. The results of this PhD thesis, obtained from the study of the literature and the analysis both at national level and of a single case study, are multiple and provide useful indications to policy makers and transport providers for the implementation of DRT services in hard-to-reach areas with low transport demand, capable of truly satisfying the mobility needs of the inhabitants by favoring the use of public transport and slowing down the processes of depopulation and economic marginalization affecting these contexts

An Online Cost Allocation Model for Horizontal Supply Chains

65A0533 TO 18.1The problem we study in this report focuses on routing in real time a fleet of capacitated vehicles to satisfy requests submitted by a set of customers while assigning the service cost fairly among the requested customers. During each operation, only a subset of the customers request service with some of them known at the beginning of the operation and the rest arriving dynamically during the day. The exact time points of these dynamic requests are unknown at the beginning of the day. We propose a Hybrid Proportional Online Cost Sharing (HPOCS) mechanism to tackle the cost sharing problem and analyze its performance using simulation instances. Although HPOCS does satisfy the desirable properties, namely online fairness, budget balance, immediate response, individual rationality and ex-post incentive compatibility, it has certain drawbacks when the number of dynamic customers is small and does not give sufficient incentive for customers to request early. Therefore, we make two extensions to HPOCS: 1) we extend it to introduce the idea of discounts to encourage customers to submit their request in advance to better facilitate efficient vehicle routing; 2) we extend it to incorporate a dynamic vehicle routing framework that periodically re-optimizes the current vehicle routes. Both extensions include performance analysis and the tradeoff between the performance and the loss of certain desirable properties. In general, our proposed mechanism, along with its extensions can generate efficient cost sharing solutions that satisfy desirable properties, reduce overall operating cost (mainly vehicle miles travelled) and provide sufficient incentives to customers to request service early in support of horizontal cooperation