Using the Road Traffic Simulation “SUMO” for Educational Purposes

JOURNAL OF TRAFFIC AND TRANSPORTATION ENGINEERING, 2019

h i g h l i g h t s A methodology for calibrating VISSIM simulation model is presented. The calibration procedure is based on queue lengths at the roundabout's entries. The best estimates of parameters have been determined using a genetic algorithm. This calibration procedure impacts positively on the safety performance measures. Safety performance Unmanned aerial vehicle Roundabouts Traffic conflicts a b s t r a c t A methodology for calibrating and validating VISSIM simulation model is presented that allows to replicate the observed vehicles conflicts. A roundabout case study has been selected to test the usefulness of a combined approach of VISSIM simulation package and the surrogate safety assessment model (SSAM) for providing reliable estimates of traffic conflicts. Safety performance has been assessed from the field by video-recording vehicle interactions at the roundabout, and then expressed in terms of time to collision (TTC) values. The proposed calibration procedure has been performed by a multistage methodology involving microscopic drivers' car following behavior parameters to enhance the correlation between observed and simulated queue lengths at the roundabout's entries. The calibration procedure is based on a statistical screening of inputs leading to a linear expression relating significant parameters to the queue length. The best estimates of the model's parameters have been determined using a genetic algorithm technique. The spatial distribution of the rear-end conflicts and the TTC values determined by SSAM have been finally compared with the observed ones to analyze the capability of the model of replicating rear-end conflicts. The results suggest to this calibration procedure impacts positively on the estimate of the safety performance measures obtained through the simulation processes. Notwithstanding the good results in the evaluation of the model's accuracy, the simulation seems to fail in reproducing the traffic phenomena linked to unusual driving behavior, and therefore it is not able to replicate forced drivers' maneuvers that can lead to a conflict situation. j o u r n a l o f t r a f fi c a n d t r a n s p o r t a t i o n e n g i n e e r i n g (e n g l i s h e d i t i o n) 2 0 1 9 ; 6 (2) : 1 7 5 e1 8 4

ggod one

2011

Software equipment of interactive vehicle simulators consists of two main parts; a generator of virtual reality (generating 3D graphics and surrounding sound) and a mathematical model of vehicle dynamics. The basic elements of mathematical dynamics model of the vehicle consists first of a physics of an engine and a set of parameterization files that define the current values of the parameters of the vehicle, second of the world which with each particular vehicle can interact. The paper describes the development, implementation and testing of such a mathematical software model, which was subsequently used in the latest driving simulator in the laboratories at the Faculty of Transportation Sciences of the Czech Technical University in Prague.

Transportation Research Record: Journal of the Transportation Research Board, 1998

A linear acceleration car-following model has been developed for realistic simulation of traffic flow in intelligent transportation systems (ITS) applications. The new model provides continuous acceleration profiles instead of the stepwise profiles that are currently used. The brake reaction times of the drivers are simulated effectively and are independent of the simulation time steps. Chain-reaction times of the drivers are also simulated and perception thresholds are incorporated in the model. The preferred time headways are utilized to determine the simulated drivers’ separation during car-following. The features of the model and the realistic vehicle simulation in car-following and in stop-and-go conditions make this model suitable to ITS, especially to autonomous intelligent cruise-control systems. The car-following algorithm is validated at microscopic and macroscopic levels by using field data. Simulated versus field trajectories and statistical tests show very strong agreem...

International Series in Operations Research & Management Science, 2010

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Traffic phenomena come on the one hand from supply / demand mechanisms and on the other hand from the interactions between the various actors involved. Simulation models have been developed for several decades by traffic engineers to reproduce the phenomena. Based on the identification of observed traffic, they are unfortunately limited when the study is related to future situations (i.e. non existing, thus non observable, ones). Driver models have also been developed for decades by psychologists, but these models are also often very limited (i.e. they deal with very few and very specific driving tasks) and not operational (i.e. they are conceptual models). The simulation of the impact of a change in the traffic system is nevertheless a key issue, both from the safety and the capacity standpoints. The behaviour of drivers facing a new situation is extremely difficult to forecast, since human beings easily adapt their behaviour in response to infrastructure and equipments. They will not always use them according to designers' expectations (a rational use for collective optimisation) but, on the contrary, they very often follow individual issues, such as minimisation of constraints or economy of manoeuvres. These different standpoints often lead to incoherences between design and uses, which have a negative impact on safety as well as on capacity. Designing tools allowing a systemic approach of changes in the traffic system is the main objective of the INRETS MSIS department. Based on the joint use of a driving simulator and behavioural traffic simulation, the proposed approach (called "integrated approach") consists of a four stage iterative process which jointly uses a driving simulator and a behavioural microscopic traffic simulation model. To carry on studies according to this approach, MSIS team has designed a behavioural traffic simulation model and a driving simulator architecture, both novel. In our presentation we will first explain the « integrated » approach. We will then introduce both the traffic simulation model and the driving simulator architecture. We will discuss the validation process of these tools and give an example of use for the assessment of a driver support system. We will conclude with our prospects.

Journal of Safety Research, 2014

This conference serves as an interdisciplinary forum for the exchange of ideas, methodologies, research, and applications aimed at improving road safety globally.

Transportation Research Record: Journal of the Transportation Research Board, 2008

ity to describe driver behavior under extreme and incident conditions is limited.

IEEE Transactions on Intelligent Transportation Systems, 2018

Microscopic traffic simulation models are widely used to assess the impact of measures and technologies on the road transportation system. The assessment usually involves several measures of performance, such as overall traffic conditions, travel time, energy demand/fuel consumption, emissions, and safety. In doing so, it is usually assumed that traffic models are able to capture not only traffic dynamics but also vehicle dynamics (especially to compute energy/fuel consumption, emissions, and safety). However, this is not necessarily the case with the possibility of achieving unreliable outcomes when extrapolating from traffic to measures of performance related to the vehicle dynamics. The objective of the present paper is to assess the capability of existing car-following models to reproduce observed vehicle acceleration dynamics. A set of experiments was carried out in the Vehicle Emissions Laboratories of the European Commission Joint Research Centre in order to generate relevant data sets. These experiments are used to test the performance of three well-known car-following models. Although all models have been largely tested against their capability to correctly reproduce traffic dynamics, the findings raise concerns about their capability (and thus of the traffic models using them) to predict the effect on the microscopic vehicle dynamics and thus on emissions and energy/fuel consumption. The results of the present work can be considered valid beyond the analyzed car-following models, as simple acceleration rules are usually assumed in the vast majority of the traffic simulation frameworks. Consequently, it can be concluded that there is a number.

2016

The traffic flow microscopic modeling is basically important for the development of specific tools for understanding, simulating and controlling urban transportation systems. Car-following models have been developed to describe the dynamical characteristics of the moving vehicles. In this paper, we present a microscopic car following model based on the consideration of the driving behavior on a single-lane road. With this model, we propose an approach which permits to take into account the phenomenon of anticipation in driver behavior. A comparative study with the optimal velocity model is done. The proposed modeling approach is validated by simulation. The numerical simulation shows that the model can improve the representation of traffic flow.

The accuracy of the micro-simulation modelʼs generated vehicle activity data used in the emissions modelling depends on how the dynamic behaviours of vehicles are being represented in the model. The dynamic behaviour of every single vehicle is constantly modelled during the simulation phase in accordance with different vehicle internal behaviour models. It is therefore imperative that the model reproduces the same variability of these behaviours in the real-world. This research paper investigated two main approaches in studying how car dynamics are represented in AIMSUN traffic micro-simulation model. The first approach was to use field trajectories data in the calibration of car dynamics parameters of the car-following internal behavioural model in AIMSUN, the second approach was to compare the simulated vehicles activity modelsʼ outputs with field vehicles activity data obtained from an Instrumented Vehicle (IV) driving along the study route. The field-obtained vehicle trajectories contained second-by-second speeds and acceleration data, which have been utilised in the evaluation of the AIMSUN model performance at both macro and micro levels. The findings showed that the calibration of vehicle dynamics in car-following models has reduced the values of accelerations and decelerations in the simulations. However, this did not influence the vehicle trajectories behaviour that continued to show sharp accelerations and decelerations, which are not representative of the real-world behaviours. The research showed that the use of IV real-world data to evaluate the car-following internal behaviour model provided an effective and computationally efficient validation methodology, which offered a further level of accuracy to the available standard validation procedures.

Applied Ergonomics, 2010

This paper presents the simulation tool called SDDRIVE (Simple Simulation of Driver performance), which is the numerical computerised implementation of the theoretical architecture describing Driver-Vehicle-Environment (DVE) interactions, contained in Cacciabue and Carsten [Cacciabue, P.C., Carsten, O. A simple model of driver behaviour to sustain design and safety assessment of automated systems in automotive environments, 2010]. Following a brief description of the basic algorithms that simulate the performance of drivers, the paper presents and discusses a set of experiments carried out in a Virtual Reality full scale simulator for validating the simulation. Then the predictive potentiality of the tool is shown by discussing two case studies of DVE interactions, performed in the presence of different driver attitudes in similar traffic conditions.

Mobility and Vehicle Mechanics

Transportation and traffic affect all the aspects of everyday life. To better understand traffic dynamics traffic models are developed. On microscopic level, carfollowing models are developed and improved during long period of time. They are used in traffic simulation tools or are the basis for operation in some advanced vehicle systems. Carfollowing models describe traffic dynamics through movement of individual vehicle-driver units. This paper compares Gipps model and Intelligent Driver Model (IDM) as carfollowing models based on driving strategies. These models are derived based on assumptions such as keeping safe distance from the leading vehicle, driving at a desired speed and producing accelerations within a comfortable range. The models are implemented and simulated in MATLAB environment and the results are discussed in terms of the ability to reproduce real driving behaviour in car following scenarios.

International Journal of Advanced Research (IJAR), 2019

Microscopic simulation models have been widely used in both transportation operations and management analysis because simulation is safer, less expensive and faster than field implementation and testing. The usefulness of these models in making design and traffic control decisions will mainly depend on their accuracy and reliability. This paper describes the detail procedure for the calibration and validation of a microscopic model of highly congested intersection Mirpur-10 in Dhaka. Legs of this intersection is composed of both motorized vehicles (Bus, Passenger car etc.) and non-motorized vehicles (Rickshaws, Bicycles). Most cases, drivers are rarely concern about the lane based traffic operation. Addressing this phenomena, a micro-simulation VISSIM model with modified driving behavior parameters helps to create a virtual environment representing the traffic scenario, optimize the problems and visualize the outputs that is important to face the challenges of transportation system at present and future.

2012

In order to make good decisions in transportation, decision-makers need some references to support the decision. One source for such reference is to perform a micro-simulation; a model for representing real-world conditions including the behavior of travelers, vehicles and the infrastructure. This study will examine and present a comparison between AIMSUN (a commercial micro-simulation software) and SUMO (a non-commercial micro-simulation software), identifying advantages and disadvantages of these applications in relation to the study object Södra länken, that is E266 and E75, in south part of Stockholm, Sweden. A calibration process is conducted in order to find the best value of a set of parameters in each software. The best set of parameters will be selected based on the lowest value of a Root Mean Square Error (RMSE) computed based on observed speed data and the model output. The parameters is then validated using evening peak-hour data. This research gave result that from the given experiments with the SUMO software, the best set of parameters was when the value of Driver Imperfection at 0,3 and Driver’s Reaction Time at 1,7. For AIMSUN , the best set of parameters was when the value of Maximum Desired Speed at 100 km/h and Speed Acceptance at 1,1. In comparison, AIMSUN has advantages in terms of the simplicity for the user in creating network, setting the parameters and creating animation over SUMO. The complexity of the SUMO software stimulate the user to carefully build the model.