This paper critically reviews models to predict the performance of flexibly routed transfortation services such as taxi and dial-a-ride. Models of these services have been developed to assist in system design, in evaluation of alternatives, and in regulation. The approaches to modelling such services have been simulation, empirical, deterministic queuing and stochastic processes. Application of several models is illustrated by forecasting the level-of-service on six existing systems. While a good deal of effort has gone into model development and while some of the models appear to be quite accurate, an open question remains as to the acceptance and use of these models by planning and operating agencies.

Performance models of flexibly routed transportation services

Activity-based modelling is a modern agent-based approach to travel demand modelling, in which the transport demand is derived from the agent’s needs to perform certain activities at specific places and times. The agent’s mobility is considered in a broader context, which allows the activity-based models to produce more realistic trip chains, compared to traditional trip-based models. The core of any activity-based model is an activity scheduler – a software component producing sequences of agent’s daily activities interconnected by trips, called activity schedules. Traditionally, activity schedulers used to rely heavily on hard-coded knowledge of transport behaviour experts. We introduce the concept of a Data-Driven Activity Scheduler (DDAS), which replaces numerous expert-designed components and their intricately engineered interactions with a collection of machine learning models. Its architecture is significantly simpler, making it easier to deploy and maintain. This shift towards data-driven, machine learning based approach is possible due to increased availability of mobility-related data. We demonstrate DDAS concept using our own proof-of-concept implementation, perform a rigorous analysis and compare the validity of the resulting model to one of the rule-based alternatives using the Validation Framework for Activity-Based Models (VALFRAM).

Data-driven activity scheduler for agent-based mobility models

Impacts of replacing a fixed public transport line by a demand responsive transport system: Case study of a rural area in Amsterdam

Even though the agent-based simulation modelling has become a standard tool in transport research, current implementations still treat travellers as passive data structures, updated synchronously at infrequent, predefined points in time, thus failing to cover within-the-day decision making and negotiation necessary for cooperative behaviour in a dynamic transport system. Leveraging the fully agent-based modelling approach, we have built large-scale activity-based models of multimodal mobility covering areas up to thousands of square kilometres and simulating populations of up to millions of inhabitants of several European cities. Citizens are represented by autonomous, self-interested agents which schedule and execute their activities (work, shopping, leisure, etc.) and trips in time and space. Individual decisions are influenced by agent's demographic attributes and modelled using the data from mobility surveys. The model is statistically validated against origin-destination matrices and travel diary data sets.

Fully agent-based simulation model of multimodal mobility in European cities

We present a modeling system for simulation of dial-a-ride services. It can be used as a tool for understanding and study how different designs, and different ways to operate a dial-a-ride service, ...

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A modeling system for simulation of dial-a-ride services

CARS is s system designed to provide a taxi-like service at a mass transit-like cost. It allows potential passengers to request service from their via telephone, with calls being processed by a central computer facility. The computer periodically executes a routing algorithm which assigns vehicles to passengers and communicates this routing information to the vehicles. The system is 'real time' in that it will pick up a passenger and shortly after a request will deliver him to his destination within a guaranteed time (with a minimum number of deviations for collecting and delivering other passengers). The key to CARS is the routing algorithm. Since labor and vehicular costs are a major portion of the total system cost, an algorithm is required which can provide an effective dynamic service with a minimum number of vehicles. A variety of such algorithms have been proposed, but these algorithms can not be evaluated in an analytic fashion. Hence, a comprehensive simulation model has been developed to test and compare these routing algorithms. The model facilitates the investigation of relationships between such parameters as number of vehicles and quality of service. This paper describes the methodology of the simulation model and the economic gains (in terms of the need for fewer vehicles) realized through its use. The use of an ARDS storage tube display to produce graphical output from the model is also discussed.

B. T. Hignnet

Papers

Simulation of a Computer Aided Routing System (CARS)