A data model for trip planning in multimodal transportation systems (original) (raw)

An Object-Oriented Model of a Heterogeneous Transportation Network for Journey Planning Systems

IFAC Proceedings Volumes, 1997

The paper presents an approach adopted in the design and development of an information system for a public transportation network. This approach integrates different transportation means into one, easy-to-use and efficient computer program. The transportation means covered by the system include railways, airlines and (in a limited scope) city transport. The system exploits the classical graph-theory algorithms to timerelated heterogeneous networks. The model of the transportation network used is based on the object-oriented paradigm, which proved to be well-suited for such applications.

Object modeling and path computation for multimodal travel systems

European Journal of Operational Research, 2006

This paper describes a multimodal travel system (MTS) designed to address the needs of a variety of demand-responsive transport. An origin-destination (O-D) trip in transportation network can be accomplished by using multiple modes. In urban network passengers may boarding buses or metros to go from one place to another, and modes as autobus or trains are used by passengers to travel between cities. The work focuses on the network object modeling and multimodal shortest path algorithm. A solution to the problem of long-run planning of transit on multimodal network has been implemented and tested. The work presents the general results found, and the proposed algorithm recognizes the set of constraints related to the time schedule and the sequence of used modes in a O-D trip. The aim is to provide a tool for detecting the facilities of using different travel modes through a transportation network. Routings may include distinct combination of rail, and route. Geographic Information Systems (GIS) were invaluable in the cost-effective construction and maintenance of this work and the subsequent validation of mode sequences and paths selections. Attention is devoted to the multimodal path operator as well as to the use of GIS-transit planning.

A Multimodal Trip Planning System With Real-Time Traffic and Transit Information

Journal of Intelligent Transportation Systems, 2012

Most transit trip planning systems are based on static schedules and generate trips that do not dynamically respond to delays in transit operation caused by traffic congestion or accidents. In addition, the driving-parking-then-transit travel mode is common in metropolitan areas. However, very few transit trip planners incorporate real-time transit data into this mode. This article describes a multimodal trip planning system for multiple modes: driving, transit, and driving-parking-then-transit. The system considers the real-time transit arrival time, which is estimated by a prediction model. Both Web-based and mobile phone-based clients are used to access the system. Case studies show that the multimodal trip planning system works well in real-life situations.

TARSIUS: A system for traffic-aware route search under conditions of uncertainty

2011

This demo presents TARSIUS-a system for traffic-aware route search. In a traffic-aware route search (TARS), the user provides start location, target location and search terms, which specify types of geographical entities that should be visited along the route. A TARS query may include additional temporal constraints and limitations on the order by which entities are visited. The goal is to find the fastest route from the start location to the target, via entities of the specified types, while taking into account variations in the travel speed, due to changes in traffic conditions. Planning a route under conditions of uncertainty requires the system to also take into account the possibility that some visited entities will not satisfy the user requirements so that the route may need to go via several entities of the same type. In the demonstration we present the system. We demonstrate a web-based user interface that facilitates the formulation of TARS queries. We show how queries are posed and evaluated over a database that contains real traffic data. Since answering a TARS query is NP-hard, we present three heuristics to the problem. Using the system, we illustrate the routes that are computed by these heuristics.

Computing Multi-Modal Journey Plans under Uncertainty

Journal of Artificial Intelligence Research, 2019

Multi-modal journey planning, which allows multiple types of transport within a single trip, is becoming increasingly popular, due to a strong practical interest and an increasing availability of data. In real life, transport networks feature uncertainty. Yet, most approaches assume a deterministic environment, making plans more prone to failures such as missed connections and major delays in the arrival. This paper presents an approach to computing optimal contingent plans in multi-modal journey planning. The problem is modeled as a search in an and/or state space. We describe search enhancements used on top of the AO* algorithm. Enhancements include admissible heuristics, multiple types of pruning that preserve the completeness and the optimality, and a hybrid search approach with a deterministic and a nondeterministic search. We demonstrate an NP-hardness result, with the hardness stemming from the dynamically changing distributions of the travel time random variables. We perform...

Graph Traversal-based Solutions for Trip Planning in Public Transportation Graph

The public transportation graph facilitates efficient trip planning considering various passenger requests such as distance, waiting time, travel time, self-transportation, and number of transfers. This paper proposes an approach to normalize the edge weight in the public transportation graph and presents examples of graph traversal-based solutions to solve trip planning problems in public transportation. The proposed solutions are implemented and tested on the synthetic data to show the improvements and apply the algorithms.

Dynamic Transit Path Choice Modelling for a Traveller Tool with ATIS and Trip Planner

The paper reports the first results of a research project for the definition of a Traveller Tool for multimodal networks. The system, designed for mobile applications, gives dynamic real time information to the user for the best path choice from the traveller's utility point of view. The project at the current stage has developed a trip planner to support the user on transit networks with personalised pre-trip information based on user's preferences. The first part the paper describes the user needs and the architecture of the transit component of the system. The second part deals with the dynamic path choice model used to support the path choice set individuation and ranking, and with the user preference learning procedure. Finally, experimental applications of the system to support transit users with pre-trip personalised information are presented.

Multimodal Public Transit Trip Planner with Real-time Transit Data

Procedia - Social and Behavioral Sciences, 2013

Trip planner is a smart travel assistance tool which provides pre-trip travel plan information to the commuter for the given origin and destination stops. It is built-up with information such as road network and vehicles' schedule from various transport agencies. The schedules are static and deviates much in actual due to delays caused by dwell time, traffic congestion and accidents etc. Therefore, many real-time trip planners were developed to produce more accurate plans in terms of time and transit vehicles which use data from Global Positioning System (GPS) enabled vehicles. However, the methodologies for vehicle positioning in real-time, dealing with interrupted GPS signals and just-in-time update of transit network is still not crystallized. Mostly the vehicle positioning is handled by a third party. In addition, most of the real-time planners do not consider arterial routes. In this paper we present development of a multimodal intracity transit trip planner using public transport. It incorporates the delays into the transit network at real-time to minimize the gap of our prediction model. Kshortest path algorithm is being used to compute multi-criterion optimal plans. Here we consider both delays in all routes including arterial ones and frequently missing GPS signals. Our system handles all these with some heuristics and simulation. Besides the web interface, trip planning can also be done by sending Short Messaging Service (SMS) from any mobile phone to the server. The results have shown that the system produces plans which are acceptable in terms of response time, feasibility and accuracy.

Route planning based on uncertain information in transport networks

Transport, 2012

The goal of this paper is to find a solution for route planning in a transport network where the network type can be arbitrary: a network of bus routes, a network of tram rails, a road network or any other type of a transport network. Furthermore, the costs of network elements are uncertain. The concept is based on the Dempster–Shafer theory and Dijkstra's algorithm which helps with finding the best routes. The paper focuses on conventional studies without considering traffic accidents or other exceptional circumstances. The concept is presented by an undirected graph. In order to model conventional real transport, the influencing factors of traffic congestion have been applied in the abstract model using uncertain probabilities described by probability intervals. On the basis of these intervals, the cost intervals of each road can be calculated. Taking into account the uncertain values of costs, an algorithm has been outlined for determining the best routes from one node to all other nodes comparing cost intervals and using decision rules that can be defined by the end user, and if necessary, node by node. The suggested solution can be applied for both one type of network as well as for a combination of a few of those.

An extended model and procedural framework for planning multi-modal passenger journeys

Transportation Research Part B: Methodological, 2003

This paper is concerned with the planning of multiple-leg journeys using public transport services, typically (but not necessarily) in an intra-urban context. The repertoire of transport services may include walking, fixed-route public transport, and demand-responsive modes such as taxis. A journey-planning problem is defined by a request to travel at minimal generalised cost from a given origin to a given destination, subject to timing constraints. The paper presents a comprehensive cost-minimising formulation for such problems, allowing for the possibility of non-linear generalised-cost functions. An optimisation procedure is outlined for problems involving an ''early-departure'' style of travel. The new procedure is based on DijkstraÕs label-setting shortest-path algorithm, and can be inverted to meet the needs of a ''latearrival'' style of travel. An adaptation to a dilatory or ''sightseeing'' style of travel is also possible, but may be problematic with respect to computational performance.