Klaus Bogenberger

Relocation strategies and algorithms for free-floating Car Sharing Systems

During the last years so-called free-floating Car Sharing Systems became very popular. These systems in comparison to the conventional Car Sharing Systems allow short one-way trips. Today, the spatial distribution of vehicles within free-floating Car Sharing Systems is either self-organized, which means it is only dependent on the customers demand or in a few cases the positioning is manually controlled by system operators. None of the real-life free-floating Car Sharing Systems has a clear defined relocation strategy or is even online optimized based on the current demand. Within this paper several relocation strategies are introduced and categorized. For each category known relocation algorithms are described and evaluated. Also a new integrated two-step model for optimal vehicle positioning and relocation is described in detail. This new approach consists of an offline demand clustering that allows for the prediction of demand and thus the prediction of the optimal future state of spatially available vehicles. The online module of the approach measures the differences between optimal vehicle positioning and current positioning. An optimization algorithm finds optimal relocation strategies if necessary. The main focus of this paper is on the description of the Offline Demand Module.

An evolutionary fuzzy system for coordinated and traffic responsive ramp metering

This paper proposes a nonlinear approach for designing traffic responsive and coordinated ramp control using a self adapting fuzzy system. The traffic responsive metering rate is determined every minute by an adaptive fuzzy logic algorithm. The coordination between multiple on-ramps is ensured by the integration of a common input into all ramp controllers upstream of a bottleneck and a periodically update of the fuzzy system every 15 min. By a evolutionary timing process. The objective of the genetic tuning of the fuzzy parameters is to minimize the total time spent in the system. Therefore a modified Payne traffic flow model is used. For testing the developed system a section of 25 km of the A9 Autobahn was simulated with the FREQ model. The results of the simulation of the adaptive fuzzy algorithm are very satisfying and an implementation of the ramp metering system is planned in the very near future.

Relocation Strategies and Algorithms for Free-Floating Car Sharing Systems

During the last two years so-called free-floating Car Sharing Systems became very popular. These systems in comparison to the conventional Car Sharing Systems allow short one-way trips. Today, the spatial distribution of vehicles within free-floating Car Sharing Systems is either self-organized, which means it is only dependent on the customers demand or in a few cases the positioning is manually controlled by system operators. None of the known free-floating Car Sharing Systems has a clear defined relocation strategy or is online optimized based on the current demand. Within this paper several relocation strategies are introduced and categorized. For each category a relocation algorithm is described and evaluated. Also a new integrated two-step algorithm for optimal positioning and strategy selection is described in detail. This new approach consists of an offline demand clustering that allows for strategy pre-selection. The online module of the approach measures the differences between optimal vehicle positioning and current positioning and selects the best relocation strategy for implementation.

Traffic Management Effects of Variable Speed Limit System on a German Autobahn: Empirical Assessment Before and After System Implementation

An empirical study of the traffic flow effects of a variable speed limit (VSL) system on a three-lane German autobahn is presented. The study integrated loop detector data and VSL and driver information provided by overhead dynamic message signs along a 16.3-km section of Autobahn A99 near Munich, Germany. Unlike most VSL deployments, the data sources allowed for a with-and-without analysis to reflect traffic flow and driver behavior in the presence and in the absence of the VSL system. In addition to speed, the primary features of interest were the spatial–temporal extent of the queue (congestion), flow changes caused by identified bottlenecks, the distribution of flow across lanes, the percentage of trucks per lane, and the flow homogeneity between lanes. The analysis recorded bottleneck flow reductions that were balanced across all lanes with an active VSL system. With an inactive VSL system, the flow reductions were slightly lower and occurred primarily in the center and shoulder lanes; there was a small flow increase in the median lane. Further examination indicated that the gain in homogeneity and safety with the system in place was at the cost of capacity. Possible reasons that might explain the differences between the scenarios with and without the VSL system had their basis in the ban against passing by trucks, which was in effect when the driver information system was active.

A neuro-fuzzy algorithm for coordinated traffic responsive ramp metering

This paper proposes a nonlinear approach for designing traffic responsive and coordinated ramp control using a self adapting fuzzy system. An adaptive neuro-fuzzy inference system (ANFIS) is used to incorporate a hybrid learning procedure into the control system. The traffic responsive metering rate is determined in every minute by the neuro-fuzzy control algorithm. Coordination between multiple on-ramps is ensured by the integration of a common input into all ramp controllers upstream of a bottleneck and a periodical update of the fuzzy control system in every 15 min. by a hybrid learning procedure. The objective of the online tuning process of the fuzzy parameters is to minimize the total time spent in the system. Therefore, Paynes traffic flow model and a deterministic queuing model are integrated into the control architecture To assess the impacts of the neuro-fuzzy ramp metering algorithm a section of 25 km of the A9 Autobahn was simulated with the FREQ model and compared with two other control scenarios. The results of the simulation of the neuro-fuzzy algorithm are very promising and an implementation of the neuro-fuzzy ramp metering system on a Munich middle ring road within the MOBINET project is planned.

GPS-Data Analysis of Munich's Free-Floating Bike Sharing System and Application of an Operator-based Relocation Strategy

Public Bike Sharing Systems provide a progressive option for urban mobility, not only for commuters but also for spontaneous users and tourists. Such systems are only reasonable, if the bikes are available where the users need them at a certain time though. In so-called free-floating systems as its implemented in Munich, the user is allowed to rent and return a bike within a clearly defined operating area. However, on one hand there are zones, where a shortage of returned bikes occurs. No bikes are available but needed there. On the other hand there are zones, where too many bikes were returned but the demand for renting a bike there is too low. Based on a detailed GPS-Data Analysis for the bike sharing system, mobility patterns of the usage were identified. Depending on different factors like weather conditions, time of the day and holidays/weekends, a demand model was created in order to obtain an optimal distribution of bikes within the operating area. At the end of this paper an application of an operater-based relocation strategy is given. By relocating at least some part of the fleet, its ensured that the demand for bikes is optimally satisfied in time and space.

A dynamic prizing scheme for a congestion charging zone based on a network fundamental diagram

The continuously rising amount of traffic is becoming more and more of a problem that cities have to deal with it, as it causes congestion, noise and air pollution, among other side effects. As a solution approach for these diverse problems, many cities have already decided to install a toll, which is often designed as a congestion-pricing area. With that, they aim to reduce, if not completely prohibit, traffic in the inner cities, and to provide a source of additional income for the city budget. In order to get the maximum traffic benefits out of such a tolling area and to avoid traffic jams within the tolled area, it is necessary to control the system with an efficient algorithm. However, at the moment there are no dynamic, traffic responsive city tolling systems. The major reason is that such controlling mechanisms, especially if they have to represent a whole network, would require a lot of data. This data is not only difficult to collect and manage, particularly if most of the roads inside the network have to be measured, it also makes it hard to design and calibrate the control algorithm. With the help of a network fundamental diagram (NFD), representing the traffic state of the whole network, this data collection and management problem can be solved. This motivates the idea of using an NFD as a basis for controlling the pricing scheme of a city tolling system. To examine the feasibility of this approach, a microscopically simulated test network was created and a NFD for this network was developed. Using this NFD, a desired occupancy value for the whole network is set, and the toll height is calculated from different control functions of the occupancy inside the tolled network compared to the desired occupancy value. This toll height is subsequently included into the route choice algorithm of the microsimulation, shifting the traffic onto the non-tolled roads. In order to assess the different control approaches, evaluation criteria including a comparison of the resulting network occupancy with the desired one, the stability of the price, and the reaction speed are set. Several approaches to determine the prizing based on the fundamental diagram are developed and tested in the simulated network. The development of the traffic flow and network occupation over time inside the tolled network is compared between the various tolling functions in order to identify the best performing one.

Microsimulation of an autonomous taxi-system in Munich

Studies about autonomous taxis (aTaxis) concluded that empty vehicle movements account for a share of about 10% of vehicle miles traveled. In many of these studies, constant (in time or space) travel times are used due to a lack of data and to simplify the computations. Furthermore, the influence of the empty vehicle movements on the street network has not yet been a focal point of research. To address these two issues, the operation of an aTaxi system is implemented into an existing traffic microsimulation model. On the one hand, a microsimulation depicts travel times more accurately than constant link-level values. On the other hand, the taxi movements influence the flows along the network links and thereby have the potential to change travel times in the street network. Based on a calibrated Aimsun model of the city of Munich, a small number of scenarios are simulated: Starting from the calibrated OD matrix, a share of 10% of trips originating and ending inside the highway belt of Munich are completely or partially served by aTaxis. In case of a 1-to-1 substitution of private trips with aTaxi requests, the network-wide delay of private vehicles only increases by 1% due to induced empty rides. Furthermore, the differences between a simulation using linklevel travel times and a traffic microsimulation are studied. Delays due to left turns and traffic lights are present in the microsimulation. Results show, that fleet operation algorithms need to address these issues, which occur in reality.

Fusing probe speed and flow data for robust short-term congestion front forecasts

In this paper a robust and flexible method is proposed that combines the strengths of detector as well as Floating Car (FC) data in order to provide short-term congestion front forecasts. Based on the high spatio-temporal resolution of FC data, congested regimes and according congestion fronts are identified accurately. Subsequently, the flow data provided by loop detectors are utilized in order to predict these congestion fronts for a time horizon of up to ten minutes. Three variations of the method are presented which focus the difficulty of estimating traffic density in congested traffic conditions with given data. The evaluation is based on real FC as well as loop detector data collected during a congestion on the German Autobahn A9. Comparisons of the variants of the proposed method and a naive predictor emphasize the advantage of combining both data sources and point out the strategy that results in the most accurate front forecasts.

Usability of escooters in urban environments — A pilot study

While scooters, often powered by 2-stroke engines, are quite popular in the southern parts of Europe they are rather scarce in the rest of Europe. Over the last years, electric-powered two-wheelers debuted on European markets. Since this type of vehicle can considerably improve traffic, reduce shortage of parking, and cut local emissions in cities, its low distribution and propagation in Europe seems rather inconvenient. This article presents the results of an escooter pilot study conducted in Munich, Germany, in order to broaden the understanding of the low distribution and of the field of application, usage, and constraints this kind of vehicle is facing in a European city. Therefore this article gives a summary about the subject of low-powered two-wheelers. In order to analyze the gathered data, a method to minimize irregularities in completion of a trip diary is presented. Final results of this pilot study show that escooters are particularly utilizable for commuting and leisure trips and can thereby substitute up to 64% of average daily distances. Additionally, weather conditions as constraints for escooter usage are examined. Even with weather conditions prevailing in Central Europe, escooters can be used at 58% of days per year without weather adjusted gear.