The Influence of Multi-agent Cooperation on the Efficiency of Taxi Dispatching

The paper deals with the problem of the optimal collaboration scheme in taxi dispatching between customers, taxi drivers and the dispatcher. The authors propose three strategies that differ by the amount of information exchanged between agents and the intensity of cooperation between taxi drivers and the dispatcher. The strategies are evaluated by means of a microscopic multi-agent transport simulator (MATSim) coupled with a dynamic vehicle routing optimizer (DVRP Optimizer), which allows to realistically simulate dynamic taxi services as one of several different transport means, all embedded into a realistic environment. The evaluation is carried out on a scenario of the Polish city of Mielec. The results obtained prove that the cooperation between the dispatcher and taxi drivers is of the utmost importance, while the customer–dispatcher communication may be reduced to minimum and compensated by the use of more sophisticated dispatching strategies, thereby not affecting the quality of service

Benchmarking minimum passenger waiting time in online taxi dispatching with exact offline optimization methods

This paper analyses the use of exact offline optimization methods for benchmarking online taxi dispatching strategies where the objective is to minimize the total passenger waiting time. First, a general framework for simulating dynamic transport services in MATSim (Multi-Agent Transport Simulation) is described. Next, the model of online taxi dispatching is defined, followed by a formulation of the offline problem as a mixed integer programming problem. Three benchmarks based on the offline problem are presented and compared to two simple heuristic strategies and a hypothetical simulation with teleportation of idle taxis. The benchmarks are evaluated and compared using the simulation scenario of taxi services in the city of Mielec. The obtained (approximate) lower and upper bounds for the minimum total passenger waiting time indicate directions for further research

Impact assessment of autonomous DRT systems

The market entrance of shared autonomous vehicles (SAV) may have disruptive effects on current transport systems and may lead to their total transformation. For many small and medium-sized cities, a full replacement of public transport services by these systems seems to be possible. For a transport system operator, such a system requires a bigger fleet of vehicles than before, however, vehicles are less expensive and fewer staff is needed for the actual operation. In this paper, we are using a simulation-based approach to evaluate the service quality and operating cost of a demand responsive transit (DRT) system for the city of Cottbus (100 000 inhabitants), Germany. The simulation model used is based on an existing MATSim model of the region that depicts a typical work day. Results suggest, that the current public transport system may be replaced by a system of 300 to 400 DRT vehicles, depending on their operational mode. Compared to previous, schedule based public transport, passengers do not need to transfer, and their overall travel times may be reduced significantly. Results for the cost comparison are preliminary, but results suggest that an autonomous DRT system is not necessarily more expensive than the current public transport system

Towards a Testbed for Dynamic Vehicle Routing Algorithms

Since modern transport services are becoming more flexible, demand-responsive, and energy/cost efficient, there is a growing demand for large-scale microscopic simulation platforms in order to test sophisticated routing algorithms. Such platforms have to simulate in detail, not only the dynamically changing demand and supply of the relevant service, but also traffic flow and other relevant transport services. This paper presents the DVRP extension to the open-source MATSim simulator. The extension is designed to be highly general and customizable to simulate a wide range of dynamic rich vehicle routing problems. The extension allows plugging in of various algorithms that are responsible for continuous re-optimisation of routes in response to changes in the system. The DVRP extension has been used in many research and commercial projects dealing with simulation of electric and autonomous taxis, demand-responsive transport, personal rapid transport, free-floating car sharing and parking search

Electric Taxis in Berlin – Analysis of the Feasibility of a Large-Scale Transition

Battery operated electric vehicles (BEVs) offer the opportunity of running a zero-emission car fleet. However, due to their current range constraints, electric vehicle operations are mainly attractive for inner-city transport, such as the taxi business. This paper is bringing together facts and assumptions about Berlin’s taxi transport and the current conditions of BEVs in Germany to provide the scope of electrification. Firstly, the necessary amount of fast chargers is determined taking general constraints of Berlin’s taxi business into account. For charging, especially busy days during cold winter days will be critical. Furthermore, a pricing scheme for fast charger usage is introduced. Based on this, operating operation costs of a hybrid electric vehicle and a battery electric vehicle are compared. The authors conclude that BEV operation will only pay off if the vehicle’s battery life can be warranted over a long span or costs of electric energy in Germany drops

Towards Multi-Agent Simulation of the Dynamic Vehicle Routing Problem in MATSim

The paper presents the idea and the initial outcomes of integrating MATSim, a multi-agent transport simulation system, with the DVRP Optimizer, an application for solving the Dynamic Vehicle Routing Problem. First, the justification for the research is given and the state of the art is outlined. Then, MATSim is presented with a short description of the recent results in areas related to the one proposed in the paper, followed up by the discussion on the DVRP Optimizer functionality, architecture and implemented algorithms. Next, the process of integrating MATSim and the DVRP Optimizer is presented, with the distinction of two phases, the off-line and on-line optimization. Then, a description of the off-line optimization is given along with the results obtained for courier and taxi services in urban areas. The paper ends with conclusions and future plans

A Microscopic Simulation Approach for Optimization of Taxi Services

This paper presents a simulation platform along with several on-line dispatching algorithms developed in order to optimize taxi services. First, the issue of simulation-based optimization of modern transport services, especially taxi services, is presented. Next, the proposed approach to microscopically simulate taxi services is explained, followed by a description of the on-line taxi dispatching algorithm framework and three selected dispatching strategies implemented within this framework. The next section presents the simulation scenario of Mielec that the strategies were tested on. Then, the simulation results obtained are analysed and the strategies compared. The paper ends with conclusions on the main properties and other possible applications of the proposed simulation approach, as well as on future plans concerning further improvements of the taxi dispatching algorithms

Reduced Order Modelling for the Simulation of Quenches in Superconducting Magnets

This contributions discusses the simulation of magnetothermal effects in superconducting magnets as used in particle accelerators. An iterative coupling scheme using reduced order models between a magnetothermal partial differential model and an electrical lumped-element circuit is demonstrated. The multiphysics, multirate and multiscale problem requires a consistent formulation and framework to tackle the challenging transient effects occurring at both system and device level

Proactive empty vehicle rebalancing for Demand Responsive Transport services

Worldwide, ridesharing business is steadily growing and has started to receive attention also by public transport operators. With future fleets of Autonomous Vehicles, new business models connecting schedule-based public transport and feeder fleets might become a feasible transport mode. However, such fleets require a good management to warrant a high level of service. One of the key aspects of this is proactive vehicle rebalancing based on the expected demand for trips. In this paper we model vehicle rebalancing as the Dynamic Transportation Problem. Results suggest that waiting times can be cut by around 30 % without increasing the overall vehicle miles travelled for a feeder fleet in rural Switzerland