Reflective Nested Simulations Supporting Optimizations within Sequential Railway Traffic Simulators

This article describes and discusses railway-traffic simulators that use reflective nested simulations. Such simulations support optimizations (decision-making) with a focus on the selection of the most suitable solution where selected types of traffic problems are present. This approach allows suspension of the ongoing main simulation at a given moment and, by using supportive nested simulations (working with an appropriate lookahead), assessment of the different acceptable solution variants for the problem encountered—that is, a what-if analysis is carried out. The variant that provides the best predicted operational results (based on a specific criterion) is then selected for continuing the suspended main simulation. The proposed procedures are associated, in particular, with the use of sequential simulators specifically developed for railway traffic simulations. Special attention is paid to parallel computations of replications both of the main simulation and of supportive nested simulations. The concept proposed, applicable to railway traffic modelling, has the following advantages. First, the solution variants for the existing traffic situation are analyzed with respect to the feasibility of direct monitoring and evaluation of the natural traffic indicators or the appropriate (multi-criterial) function. The indicator values compare the results obtained from the variants being tested. Second, the supporting nested simulations, which potentially use additional hierarchic nesting, can also include future occurrences of random effects (such as train delay), thereby enabling us to realistically assess future traffic in stochastic conditions. The guidelines presented (for exploiting nested simulations within application projects with time constraints) are illustrated on a simulation case study focusing on traffic assessment related to the track infrastructure of a passenger railway station. Nested simulations support decisions linked with dynamic assignments of platform tracks to delayed trains. The use of reflective nested simulations is appropriate particularly in situations in which a reasonable number of admissible variants are to be analyzed within decision-making problem solution. This method is applicable especially to the support of medium-term (tactical) and long-term (strategic) planning. Because of rather high computational and time demands, nested simulations are not recommended for solving short-term (operative) planning/control problems.

Integration of Different Mobility Behaviors and Intermodal Trips in MATSim

MATSim is an open-source simulation framework for mesoscopic traffic simulations that has gained popularity in recent years. In this paper, we present a MATSim model for the city of Vienna, with a particular emphasis on the intermodal routing framework used to create agent trips, and the development of a utility function to specify different agents’ mode preferences. To create agent activity chains, we use mobility diaries from the national transportation survey in Austria and disaggregate the available geospatial information to best fit the reported travel times. The novelty of the intermodal framework is the ability to create trips that do not consist of only one mode of transportation, but to also include bicycle, car, and demand-responsive transport (e.g., cab, car sharing) trips in combination with public transportation. To represent the different mobility behaviors of agents, we divide the population into groups and assign them different utility functions for transportation modes according to their socio-demographic characteristics. After presenting the validation of the model, we discuss ways to improve the model.

Car-Access Attractiveness of Urban Districts Regarding Shopping and Working Trips for Usage in E-Mobility Traffic Simulations

With the continuous proliferation of private battery electric vehicles, the demand for electrical energy and power is constantly increasing. As a result, the electrical grid may need to be expanded. To plan for such expansion, information about the spatial distribution of the energy demand is necessary. This can be determined from e-mobility traffic simulations, where travel schedules of individuals are combined with an attractiveness rating of locations to estimate traffic flows. Typically, attractiveness is determined from the “size” of locations (e.g., number of employees or sales area), which is applicable when all modes of transportation are considered. This approach leads to inaccuracies for the estimation of car traffic flows, since the parking situation is neglected. To overcome these inaccuracies and fill this research gap, we have developed a method to determine the car-access attractiveness of districts for shopping and working trips. Our method consists of two steps. First, we determine the car-access attractiveness of buildings within a district based on the parking situation of each individual building and then aggregate the results at the district level. The approach is demonstrated for the city of Berlin. The results confirm that conventional models cannot be used to determine the car-access attractiveness of districts. According to these models, attractive districts are predominantly located in the city centre due to the large amount of sales areas or the large number of employees. However, due to the high density of buildings, only limited space is available for parking. Attractive districts rated according to our new approach are mainly located in the outer areas of the city and thus match the parking situation.

Analysis of Pollutant Emissions on City Arteries—Aspects of Transport Management

The aim of the study is to present a methodology for analyzing pollution emissions in a medium-sized city using modern traffic simulations in the aspect of minimizing exhaust emissions. The scope of the research and the methods of analysis used differ from those applied in big cities projects that can be found in the literature, Therefore the progressive elaboration model has been applied methodically to formulate and carry out the feasibility study. To perform microscopic traffic simulations, the software Simulation of Urban Mobility (SUMO—German Aerospace Center (DLR), Berlin, Germany) was applied. Thanks to the simulations, changes in traffic organization were accurately identified in the context of pollution emissions before they were implemented. The proposed approach allows a smooth flow of vehicles and a reduction of exhaust emissions. The experiments, supported by visual modelling of traffic with respect to pollution emissions, were performed on one of the main arteries of the city of Czestochowa (Poland). The results were used to explain the benefits of planned roadworks and convince the city government of the necessity to modernize the communication network.

Calibrating the Wiedemann 99 Car-Following Model for Bicycle Traffic

Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.

A cellular automaton-based model of ship traffic flow in busy waterways

In busy waterways, spatial-temporal discretisation, safe distance and collision avoidance timing are three of the core components of ship traffic flow modelling based on cellular automata. However, these components are difficult to determine in ship traffic simulations because the size, operation and manoeuvrability vary between ships. To solve these problems, a novel traffic flow model is proposed. Firstly, a spatial-temporal discretisation method based on the concept of a standard ship is presented. Secondly, the update rules for ships’ motion are built by considering safe distance and collision avoidance timing, in which ship operation and manoeuvrability are thoroughly considered. We demonstrate the effectiveness of our model, which is implemented through simulating ship traffic flow in a waterway of the Yangtze River, China. By comparing the results with actual observed ship traffic data, our model shows that the behaviours and the characteristics of ships’ motions can be represented very well, which also can be further used to reveal the mechanism that affects the efficiency and safety of ship traffic.

Cooperative messages to enhance the performance of L3 vehicles approaching roadworks

Introduction In the near future, automated vehicles will drive on public roads together with traditional vehicles. Even though almost the whole academia agrees on that statement, the possible interferences between the two different kinds of driver are still to be analyzed and the real impacts on the traffic flow to be under-stood. Objectives Aim of this paper is to study one of the most likely L3 automated system to be deployed on public roads in the short term: Highway Chauffeur. The analysis of this system is carried out on a roadwork scenario to assess the positive impacts arising from a joint implementation of the automated system and the C-ITS Use Case signaling the closure of a lane. In fact, the main contribution of this paper is the assessment of the possible benefits in travel times and driving regime arising from the joint implementation of the Highway Chauffeur system and of C-ITS messages, both for the vehicles equipped with both technologies and for the surrounding traffic. Methods The assessment is achieved through traffic simulations carried out with the VISSIM software and a Python script developed by the authors. The overall process is described and the obtained results are provided, commented and compared to define the implementation of the C-ITS Use Case that could maximize the benefits of L3 driving. Results These results showed how triggering the take-over maneuver in ad-vance fosters the bottleneck efficiency (the same speed values reached between 80 and 100% Market Penetration for around 700 m range of the C-ITS message are reached at 50% Market Penetration with a 1500 m range). Besides, an in-creased speed up to 30 km/h at the bottleneck is recorded, depending on the mar-ket penetration and the message range. Finally, the delay upstream the roadworks entrance is reduced by 6% and arises at around 700 m, without the need to deploy the message up to 1500 m. Conclusions The paper investigates the impacts of take-over maneuvers and of automated driving while considering different operational parameters such as the message range. The results suggest all the potentialities of the Use Case while providing interesting figures that frame the trends related to the different imple-mentations. Finally, the tool developed to carry out the presented analysis is re-ported and made available so that hopefully the Use Case may be explored further and a precise impact assessment may be carried out with different prototypes of AVs and on different infrastructures.

Report on design of modules for the stochastic traffic simulation

As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).