Domokos Esztergár-Kiss

Evaluation of Multimodal Journey Planners and Definition of Service Levels

The demand for prior planning of travel chains and more available information during the journey is induced by the passengers’ growing requirements. Many journey planners are already available on the internet, but these often provide only partially comprehensive solutions and are difficult to be compared. For analysis and evaluation of the multimodal journey planners a framework of aspects has been developed, so that they can be compared in a quantitative way and ranked by functional, operational and visualization features. In the course of comparison some top features of the planners have been highlighted, too. Furthermore, development directions were determined, which are the following: multimodality, real-time data, location-based services and personalized recommendations for all transport modes. Hence the journey planners can be ordered into service levels.

Extensions of the Activity Chain Optimization Method

ABSTRACT For the optimization of daily activity chains a novel method has been elaborated, where flexible demand points were introduced. Some activities are not necessarily fixed temporally and spatially, therefore they can be realized in different times or locations. By using flexible demand points, the method is capable of finding new combinations of activity chains and choosing the optimal set of activities. The optimization algorithm solves the TSP-TW (Traveling Salesman Problem – Time Window) problem with many flexible demand points, which resulted in high complexity and long processing times. Therefore, two extensions were developed to speed up the processes. A POI (Point Of Interest) search algorithm enabled to search demand points in advance and store them in an offline database. Furthermore GA (genetic algorithm) was applied and customized to realize lower optimization times. During the implementation, three different transportation modes were defined: car, public transport, and combined (public transport with car-sharing opportunity). The simulations were performed on arbitrarily chosen test networks using Matlab. Promising test results were obtained for all transportation modes with total travel time reduction of 10–15 percent. The application of the extended optimization method produced shorter activity chains and decreased total travel time for the users.

System architecture of the activity chain optimization application

In order to optimize daily activity chains a new approach has to be followed when creating the method and the connected systems architecture. The elaborated method builds on the flexibility of activities, which can be spatial or temporal. With the introduction of flexibility new locations of the activities are suggested to the travellers, so that the optimization can be realized and shorter travel times can be achieved. But having a novel algorithm is not sufficient, as the framework of the implementation needs to be elaborated. The system architecture of the application was designed, which provides a structure for the elaborated optimization module. The core of the system architecture is the optimization module, which contains the logic of the optimization algorithm. In the elaborated structure the following main elements were identified: mobile application, database server, application server and external databases. The functionalities and connections among the main elements were described. Furthermore the update frequencies of the external databases for proper functioning were specified.

A concept of an energy optimal public transportation network

Nowadays the growing attention to environmental issues has produced a higher interest on the transport service energy consumption. The main objective of this article is to explain the development phase of a driver advisory system (DAS) for public transportation, thus enhancing the energy effectiveness driving of trams and busses. The basis of energy consumption reduction is the control and management of vehicle acceleration. DAS takes into account the condition of the path and gives suggestions to the driver about the optimal speed and reaching it by using a minimal amount of energy. The system is based on a non-built-in solution, which can be flexibly adapted to the specific transport systems of a city, using different vehicles and data transmission models.

Simulation results for a daily activity chain optimization method

A growing trend, especially in urban environments, is observable towards flexibility in times and locations of activities performed during the day by passengers. In order to optimize the organization of daily activity chains a novel method was elaborated, which introduces flexible demand points. The main idea is that some activities are not necessarily fixed temporally and spatially, therefore they can be realized in different times or locations. Using flexible demand points the method finds all possible combinations and chooses the optimal set of activities by implementing TSP-TW algorithm. The optimum criterion was set as the minimum travel time. The algorithm takes into consideration many constraints, as opening times of the shops or maximum waiting times before the planned arrival. The application of the method results in shorter activity chains and a decrease of travel time for passengers, which has also economical and sociological benefits in long term.

Data analysis opportunities of electronic fare collection systems

Collecting data from the executed travels on the transportation network a database can be produced, which provides relevant information and statements for the operators. With the developed application the movements of the passengers are observable, thus travel demands can be revealed. Also the performance of the operators, such as effectiveness and utilization, and the traffic volume on the network can be presented. According to the high degree of parameterization, specific data can be retrieved from the database, e.g. in a form of tables and diagrams or map views. During the development of the application the aim was to construct easy and expressive results for the operator, thus facilitating the organization and planning of transportation networks.