Joerg Schweizer

Optimum Vehicle Flows in a Fully Automated Vehicle Network

This paper provides a novel assignment method and a solution algorithm that allows to determine the optimum vehicle flows in a fully automated vehicle network. This assignment method incorporates the following specific features: (1) optimal redistribution of occupied and unoccupied vehicles; (2) inter-vehicle spacing is adapted to meet the minimum safe distance criteria on congested link, (no collision in the worst failure case); (3) trip-time minimization of all traffic participants by a centralized vehicle routing. The latter feature allows the realization of a so called system optimum solution, which minimizes the total time of all trips. This assignment method is applied to two, topologically different, test networks at different travel demand levels, in order to determine: the share of unoccupied vehicle, the minimum number of required vehicles, the share of congested links, the lost trip-time of occupied vehicles due to the presents of unoccupied vehicles. Furthermore, the advantage of a centralized vehicle routing is quantified by comparing the total trip-times of a scenario using a system optimum solution with a scenario applying the user equilibrium solution, without considering unoccupied vehicle flows. Regarding the investigated scenarios, the share of unoccupied vehicle flows with centralized vehicle routing in a uniform, random demand scenario is approximately 11%−14%.

PRT Mode Share Estimations Using a Direct Demand Stated Preference Method

Contrary to the widespread assumption that car use is inflexible, we find that a vast majority of the population are in fact ready to change to public transport (PT), if its service characteristics feature an easily accessible, clean, frequent transport without transfers and with seated comfort – characteristics that have proven impossible to satisfy with conventional collective transport. Personal Rapid Transit (PRT) can provide all of these features. In the BICY project, our direct-demand estimate finds that PRT share would become dominant after the provision of a citywide PRT network, and that more than half of the 10 cities, private transport (car and motorcycle) would drop below 15%. We also find PRT ridership will depend strongly on the level of present PT usage: a high current share of PT usage results in a high potential share of PRT ridership, once introduced. This confirms previous findings of studies on PRT mode shares. The difference is that the present study, using direct demand estimation, shows generally higher PRT (and therefore PT) shares.

SUMOPy: An Advanced Simulation Suite for SUMO

SUMOPy is intended to (1) expand the user-base of SUMO - Simulation of Urban MObility: by providing a user-friendly, yet flexible simulation suite for SUMO, including a GUI and scripting; (2) enhance the demand modeling capacity, in particular by providing an activity-based demand modeling and making more extensive use of the attributes provided by the OpenStreetMap database; (3) easier management of existing vehicle types such as bicycles as well as new vehicle types like Personal Rapid Transit (PRT). The vision of SUMOPy is to simulate a synthetic population in a multi-modal transport environment, because it is believed that only in this way the net-effect of new transport modes and technologies can be assessed. The basic architecture and principles of operation are explained and some examples on how to use SUMOPy through both, GUI and scripting are presented. SUMOPy is still in an early stage of development and many of the current SUMO capabilities are not yet implemented. However this article explains which features will be added in the near future and how they fit in the existing structure.