Online Predictive Optimization Framework for Stochastic Demand-Responsive Transit Services

This study develops an online predictive optimization framework for dynamically operating a transit service in an area of crowd movements. The proposed framework integrates demand prediction and supply optimization to periodically redesign the service routes based on recently observed demand. To predict demand for the service, we use Quantile Regression to estimate the marginal distribution of movement counts between each pair of serviced locations. The framework then combines these marginals into a joint demand distribution by constructing a Gaussian copula, which captures the structure of correlation between the marginals. For supply optimization, we devise a linear programming model, which simultaneously determines the route structure and the service frequency according to the predicted demand. Importantly, our framework both preserves the uncertainty structure of future demand and leverages this for robust route optimization, while keeping both components decoupled. We evaluate our framework using a real-world case study of autonomous mobility in a university campus in Denmark. The results show that our framework often obtains the ground truth optimal solution, and can outperform conventional methods for route optimization, which do not leverage full predictive distributions.Comment: 34 pages, 12 figures, 5 table

Integrated urban freight logistics combining passenger and freight flows - Mathematical model proposal

The aim of this research is to propose an urban logistics distribution service which benefits from the already installed passenger transport network. This service is based upon the concept of integration of the existing passenger transport network with the urban freight process. The aim is to reduce the number of fossil combustion powered commercial vehicles traveling within city boundaries, solely for goods transportation, thus contributing to reduce negative effects of urban logistics activities, namely pollution, noise, traffic congestion and accidents. Also, integrating goods and passenger flows will promote higher efficiency rates for the passenger transport network and enhance living conditions within major urban centers. A mathematical model for the operational planning of the proposed urban logistics distribution service is proposed. This model consists of assigning origins loads (or requests) to inbound hubs (bus operator centers), transferring the inbound hubs loads to a bus service, and transferring the bus loads to bus stops, to be collected by micro-logistics operators operating environmentally friendly vehicle fleets. The objective is to minimize the total service time while assuring services synchronization along the network and balancing the loads with the system capacities.(undefined

Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Vehicle Dispatching and Routing of On-Demand Intercity Ride-Pooling Services: A Multi-Agent Hierarchical Reinforcement Learning Approach

The integrated development of city clusters has given rise to an increasing demand for intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading traditional intercity bus services by implementing demand-responsive enhancements. Nevertheless, its online operations suffer the inherent complexities due to the coupling of vehicle resource allocation among cities and pooled-ride vehicle routing. To tackle these challenges, this study proposes a two-level framework designed to facilitate online fleet management. Specifically, a novel multi-agent feudal reinforcement learning model is proposed at the upper level of the framework to cooperatively assign idle vehicles to different intercity lines, while the lower level updates the routes of vehicles using an adaptive large neighborhood search heuristic. Numerical studies based on the realistic dataset of Xiamen and its surrounding cities in China show that the proposed framework effectively mitigates the supply and demand imbalances, and achieves significant improvement in both the average daily system profit and order fulfillment ratio

Framework for integrated planning of bus and paratransit services in Indian cities

Public transport services in India and many other developing countries are provided by a combination of formal-Government led public transport systems and informal paratransit or Intermediate Public Transport (IPT) systems, which offer shuttle services along high demand corridors with passengers boarding and alighting at multiple points. Despite limited Government support, paratransit systems continue to thrive in many cities serving a crucial shared mobility need of users, without which cities would have more private vehicle usage. Due to their informal nature and the perceived competition to formal public transport systems, they have traditionally been either excluded from the public transport planning processes or designed as a feeder service to the formal transit system. The current thesis recognises paratransit’s role in serving end to end travel demand needs, particularly in developing economies with limited public transport supply and not just being a feeder to the formal public transport system. Hence, we develop an integrated planning framework that enables formal and informal public transport systems to operate as complementary systems towards meeting the mobility needs of the city. We proved an integrated planning framework based on comprehensive understanding of the demand and supply characteristics of both formal and informal systems which currently operate independently to realign services and complement each other. The tactical planning stage of public transport planning i.e. frequency setting was identified as the ideal stage of planning for integration of the two types of services. This will ensure continuity of their existing route networks and at the same time allow for paratransit services’ flexibility to switch operations between routes. Visakhapatnam, a representative medium sized Indian city with a significant presence of formal public transport in the form of city bus services and paratransit services provided by three-wheeler auto-rickshaws with a seating capacity of three to six passengers, was selected as the case city to demonstrate the methodology. A household survey based data collection and analysis methodology was adopted to analyse the socio-economic and travel demand characteristics of city bus and paratransit users. The variables impacting users’ choice between these two systems were derived through binary logistic regression. The high frequency and low occupancy paratransit systems were more popular among shorter trips, while longer trips preferred the fixed table bus systems. The operational characteristics of bus and paratransit systems were derived through a combination of primary surveys with paratransit operators and secondary data on the city bus operations. Data regarding their network of operation, services offered, passenger demand and revenue generated were collected for analysis. Buses perform a service function in the city by operating throughout the day and on a wider network, while paratransit operates with a profit motive only on high demand corridors and during peak hours. A Data Envelopment Analysis (DEA) based methodology was adopted to compare the performance efficiency of the two systems using a set of input and output indicators that define the performance of the two systems. Paratransit operations were identified to be more efficient compared to buses, due to their demand responsive operations. The lower efficiency of buses was also due to their service obligation to the city to provide affordable services throughout the day, even in areas with low demand. A bi-level transit assignment and frequency optimisation framework is developed to integrate formal bus and paratransit services. The lower-level of the model solves for the multi- modal transit assignment problem while the upper level solves for the integrated frequency optimisation problem. The transit assignment problem was solved from the users perspective i.e. to minimise their travel time through the user-equilibrium method. The frequency optimisation problem was solved using an integer programming formulation with the objective of minimising operational cost of bus and paratransit systems while meeting constraints like the travel demand on any link. The outputs from the optimisation exercise were used to quantify the impact of the public transport system at various levels i.e. users total travel time spent in the system, operators cost of providing the services and the overall impact on the society by estimating its road space requirement and emissions. Alternative user demand and transit supply scenarios were tested to assess their impacts on the society. The results show significant operational cost benefits of an integrated transit assignment and frequency planning approach where paratransit provides demand responsive services for short distance trips while formal public transport provides fixed schedule services on with broader network coverage. The analysis established the complimentary role played by bus and paratransit systems in meeting users travel demands. Therefore, it is recommended that cities harness both the systems towards meeting increasing travel needs of developing economies. Formal transit will continue to be the core of the public transport system, providing fixed route services, while paratransit can augment its capacity on high demand corridors and during peak hours. The planning and frequency optimisation framework developed in this thesis can help cities in identifying the modal-mix of fixed route public transport and on-demand services

Limited Stop Services Design Considering Variable Dwell Time and Operating Capacity Constraints

This article proposes an optimization model to set frequencies, vehicle capacities, required fleet and the stops serving each route along a transit corridor which minimize the total user and operating costs. The optimization problem is solved by applying the ?Black Hole? algorithm, which imitates the movement of stars (solutions), towards a black hole (Best solution). The main contributions of the model are based on incorporating variable dwell times depending on bus stop demand not only to the passenger perceived journey times but also to the bus cycle times and on considering capacity constraints in both vehicles and bus tops. This led to a more accurate and realistic operating times and user perceived journey times. The application of the model to two case studies and the sensitivity analysis carried out demonstrate that for low levels of demand, constant dwell times can be assumed but being these times different between the different stops of the corridor, considering their demand. However, with high level of demand the difference found in operating costs and travel times strongly recommend incorporating variable dwell times in the model in order to achieve a more realistic design of transit corridor strategies