On this page we are collected our research on road traffic microsimulation
The ways of microsimulation
The microsimulation, this increasingly everyday technique, but we are really conscious of its potential? Today for any problem concerning road traffic, whether it is on a highway in the middle of the city, is increasingly being resolved through a microsimulation software traffic flow. These tools are able to provide detailed and more precise information on the likely evolution of traffic in different contexts. It is gradually passed from the use of these to simulate small traffic problems to their use to predict the evolution of the traffic in the latest generation ITS systems, able to constantly inform millions of drivers of any problems. This below the main fields of use of microsimulators, in order to help designers and not to understand their potential.
https://www.researchgate.net/publication/294676865_Le_vie_della_micro-simulazione
Tritone: study of various car-following models
A few years ago it has started a joint research between the University of Calabria (Italy) and Politechnika Poznańska (Poland) in order to carry out studies on the difference in response of various simulation models of road traffic. One such study involved the comparison of 12 different behavioral patterns car-following, available in TRITONE, a road traffic simulator specializing in the evaluation of problems related to road safety. The problem arises from the fact that a reliable reproduction of the vehicular traffic is not a trivial problem, because so far as many mathematical models for the resolution of these problems have been proposed, but none of them can actually be considered as better than another. The work involved the study of a part of the road network of the city of Poznan (Poland) where traffic is higher in the afternoon.
https://www.researchgate.net/publication/272640397_TRITONE_studio_di_vari_modelli_di_car-following
Tritone: a microsimulator for road safety
Since 2009, the University of Calabria has developed Tritone, a microsimulatore of road networks capable of providing not only the evolution of traffic, possible areas of a road network at greater risk of accidents. Tritone is able to represent in a timely, accurate and specific traffic, its instantaneous evolution and the situations of risk, taking into account the geometrical aspects of retail infrastructure and the actual behavior of drivers by examining in detail the ‘ coupling of the characteristics of the vehicle and the driver. Tritone was founded with the aim of becoming a leading tool in the area of road safety, because not only is efficient functionally and from a usability point of view, re-mirroring full new trends of a user-friendly user interface, but also it allows you to automatically evaluate and dynamically many road safety parameters such as DRAC indicators, TTC, etc., which allow you to pre-see situations of danger and aim to the prevention already in the planning stage or verification.
Real road network application of a new microsimulation tool TRITONE
The aim of the paper is to carry out a comparative study of 13 different traffic flow models available in TRITONE, a new road traffic simulator that specializes particularly in quantitative road safety assessment. After a short introduction on traffic flow modelling, a description of the TRITONE functionality is given and various types of behavioural models available in this tool are presented in brief. Then a part of Poznan (Poland) network that served as the study area was illustrated. The following section lists all the models used in the research and provides a comparison of the results obtained with these models. The article ends with conclusions on the results’ quality of individual models.
Calibration of a New Microsimulation Package for the Evaluation of Traffic Safety Performances
Recently, some studies have confirmed that the reproduction by simulation of user behaviour under different flow and geometric conditions, can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network (Cunto and Saccomanno, 2007; Cunto and Saccomanno, 2008; Saccomanno et al. 2008). In this paper a calibration and validation technique of a microsimulation model for short-term road safety analysis is presented. The microscopic model developed allows the estimation of road safety performance through a series of indicators (Crash Potential Index, Deceleration Rate to Avoid Crash, Maximum Available Deceleration Rate, Time to Collision, etc.), representing interactions in real time between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The calibration procedure was applied using an optimization algorithm to systematically modify the 5 parameters of the core behavior model (the General Motors car following model that is a module of the main traffic microsimulation model) in order to fit travel times obtained from simulations to the measured travel times. Experimental measures where obtained in one measurement site from a survey on a two lane undivided rural highway and were provided using a specifically developed video digital processing algorithm. In order to assess the capability of the microsimulation model to reflect reality and, consequently, to make further predictions, a validation technique was carried out. In the validation process the optimization algorithm shows the ability to increase the goodness of fit of estimated travel times to measured values. The estimated car following model parameters are used in estimating the goodness of fit with a set of observed data which have not previously been used in the calibration process. This procedure has brought very good results that show how the travel times estimation errors can be greatly reduced, even in different traffic conditions relatively to the calibration scenario, by using the set of parameters obtained in the optimization procedure.
A new microsimulation model for the evaluation of traffic safety performances
Some papers have been recently presented (Cunto and Saccomanno 2007, Cunto and Saccomanno 2008, Saccomanno et al. 2008) on the potential of traffic microsimulation for the analysis of road safety. In particular, studies have confirmed that the reproduction by simulation of user behaviour under different flow and geometry conditions, can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network. The objective of this paper is to assess the validity of this approach; for this reason a microsimulation model and an automatic video detection system have been developed. The microscopic model allows the estimation of road safety performance through a series of indicators (Deceleration Rate to Avoid Crash, Time to Collision, Proportion of Stopping Distance), representing interactions in real time, between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The microscopic simulation model is used combined with a new video image traffic detection algorithm to calculate vehicle trajectories. Microscopic traffic flow parameters obtained by video detection are used to calibrate the microsimulation model, and the safety performance indicators obtained by the real vehicles trajectories can be compared with simulated scenarios where safety performance indicators are obtained on the simulated trajectories. Results indicate that the methodology can be useful in the estimation of safety performance indicators and in evaluating traffic control measures.
Safety performance measures: A comparison between microsimulation and observational data
Safety performance measures can be obtained either through simulation (based on well specified or calibrated traffic models) or experimentally through observational vehicle tracking data. Accurate calibration of traffic models ensures that simulated measures of safety performance are reflective of “real world” traffic conditions. The microscopic model, for a case study, allows the estimation of road safety performance through a series of indicators, representing interactions in real time between different pairs of vehicles belonging to the traffic stream. When these indicators reach a certain critical value, a possible accident scenario is identified. For the same case study, safety performance indicators are obtained through a video image processing algorithm for vehicle detection and tracking. The accuracy of the algorithm is evaluated with respect to GPS tracking measurements. The algorithm adopts a background subtraction-based approach for vehicle detection in 0.1 second increments. Since this approach is sensitive to background changes (or noise), a median filter technique has been introduced. Individual vehicles are detected and tracked using a region-based approach, whereby a connected zone (or blob) is assigned to each image, which is then tracked over time. In case of overlapping, where the designated blob may correspond to several vehicles, a real time sub-routine is accessed that manually discriminates each constituent vehicle’s specific position within the blob. Output from the algorithm application is expressed in terms of several trajectory descriptors over time, such as position and speed. The focus of this paper is on the analysis of road safety from two different perspectives: microsimulation and observational data. In this way it is possible to determine how microsimulation reflects “real” driver behavior and traffic conditions for a given case study.
Investigating road safety issues through a microsimulation model
Some papers have been recently presented (Cunto and Saccomanno, 2007; Cunto and Saccomanno, 2008; Saccomanno et al., 2008) on the potential of traffic microsimulation for the analysis of road safety. In particular, studies have confirmed that the reproduction by simulation of user behaviour under different flow and geometric conditions, can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network. The objective of this paper is to assess the validity of this approach and present a new methodology for investigating road safety issues. A calibrated microsimulation model has been developed to analyze vehicle trajectories, and hence vehicle interactions, in some different scenarios and verify traffic safety levels. The microscopic model allows the estimation of road safety performance through a series of indicators (Crash Potential Index, Deceleration Rate to Avoid Crash, Maximum Available Deceleration Rate, Time to Collision, etc.), representing interactions in real time between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The validation of the proposed methodology can be done by comparing the value assumed by safety performance indicators in simulated and real scenarios. The microscopic simulation model is also combined with a new video image traffic detection algorithm to detect vehicle trajectories. Microscopic traffic flow parameters obtained by video detection are, in fact, used to calibrate the microsimulation model. The above described methodology has been applied in the analysis of overtaking maneuvers on single lane for direction fast rural roads. Results indicate that the methodology can be useful in the estimation of safety performance indicators and in evaluating traffic control measures.
A new microsimulation model for the evaluation of traffic safety performances
Some papers have been recently presented (Cunto and Saccomanno 2007,Cunto and Saccomanno 2008, Saccomanno et al.2008) on the potential of traffic microsimulation for the analysis of road safety. In particular, studies have con?rmed that the reproduction by simulation of user behaviour under different ?ow and geometry conditions can identify a potential incident hazard and allow to take appropriate countermeasures at specific points of the road network.. The objective of this paper is to asses the validity of this approach, for this reason a microsimulation model and an automatic video detection system have been developed. The microscopic model allows the estimation of road safety performance through a series of indicators (Crash Potential Index, Rate Deceleration to Avoid Crash, Available Maximum Deceleration Rate, Time to Collision,etc..), representing interactions in real time between different pairs of vehicles belonging to the traffic stream. When these indicators take a certain critical value, a possible accident scenario is identified. The validation of the proposed methodology is done by comparing the value assumed by the indicators of safety performance in simulated and real scenarios. The microscopic simulation model is used combined with a new video image traffic detection algorithm to calculate vehicle trajectories. Microscopic traffic ?ow parameters obtained by video detection are used to calibrate the microsimulation model and the safety performance indicators obtained by the real vehicles trajectories can be compared with simulated scenarios where safety performance indicators are obtained on the simulated trajectories. The above described procedure has been applied in the analysis of overtaking manoeuvres on single lane for direction fast rural roads. Results indicate that the methodology can be useful in the estimation of safety performance indicators and in evaluating traffic control measures.
Investigating safety issues in two-way rural highways
In the last years the growing need for a better mobility has coincided with an increase of congestion levels on transportation infrastructures and a consequent repercussion on safety aspects. For this reason researchers and technicians have focused on the study of safety performances on road networks identifying and applying all kinds of countermeasures useful to decrease accident risks. One of the most common methodologies to estimate safety makes use of inferential statistics applied to crash databases in what can be considered as a reactive approach to the problem. Although this method seems to intuitively link causes to effects, a good knowledge of the dynamics of the events preceding the crash may provide a more useful support to the implementation of appropriate countermeasures. Moreover, the problems of consistency and availability of crash data as well as the methodological challenges posed by the extremely random nature and the uniqueness of accidents have led to the development of complementary ap-proaches to improve road safety assessment, such as the observation of traffic conflicts and the use of microscopic traffic simulation. The potential of micro-scopic simulation in traffic safety has gained a growing interest due to recent de-velopment in human behavior modeling and real time vehicle data acquisition (Cunto and Saccomanno 2007, Cunto and Saccomanno 2008, Saccomanno et al. 2008, Yang et al. 2010, Cheol and Taejin 2010). A recent FHWA review of these models has concluded that: “when properly calibrated, traffic simulation models can provide useful and reliable information on individual driver responses to changing traffic and geometric road conditions” (FHWA, 2003). Since traffic con-ditions are inputs into safety performance, these models can also provide a solid causal platform for the study of safety.
Localization issues in the use of ITS
The problem to rectify and optimize distance measures from satellites in GNSS devices has been thoroughly explored in many researches. Instead there is not much information on available procedures to replicate the observed errors. The replication of GNSS errors can, in fact, be useful in many traffic simulation scenarios to test for ITS performances. The purpose of this article is to present cases where such a methodology can be useful and then introduce a methodology for the explicit simulation of errors in GNSS systems. The proposed methodology is based on the experimental analysis of some statistical distributions. Such distributions, arising from multiple observations in the field, are able to reproduce the behavior of the error in time as a function of the factors that influence it. The analyzed data were extracted by the GPS/GLONASS sensors of common smartphones and compared with a high-precision GPS equipment. These data were evaluated in different signal coverage conditions, in an open field where the signal quality is expected to be better, suburban and urban areas, where the signal is expected to be worse. The analysis considers many aspects such as the signal reflection problems and the sudden loss of the signal because of a change of the received satellite constellation. The research was conducted by following various steps: a field survey through smartphones and high-precision instrumentation in different conditions, the creation of reference distributions for each parameter that can have an influence on the error, the analysis of correlation functions between the variables, and a final implementation of the proposed algorithm coupled with microsimulation. The paper intends to shed some light on this problem allowing scientist and developers of new ITS system methodologies to reproduce in a simulated environment not only the movement of single vehicles (as usually carried on with microsimulation) but also the data that could be obtained from on-vechicle GNSS instrumentation. The reproduction of this GNSS tracks can be useful to assess the overall response of some new ITS systems before implementing them in the field. The proposed simulation methodology could become a standard tool to help in making better decisions in ITS implementation and to develop better ITS systems.
https://www.researchgate.net/publication/319052456_Localization_issues_in_the_use_of_ITS
New features of Tritone for the evaluation of traffic safety performances
Recent research papers have confirmed that traffic simulation can identify near crashes events and establish a good base for the estimation of real crashes risk. The objective of this paper is to present the new features of a microsimulation model originally developed to estimate road safety performance.
The presented microsimulator has many new features that can be useful to engineers and researchers such as:
- Dynamic calculation of traffic and road safety indicators.
- Simulation of satellite location data obtained by GPS and smartphones.
- Simulation of adaptive traffic lights activated by FCD data.
- 20 different acoustic emission models.
- Possibility of taking into account “instrumented” vehicles to assess new Intelligent Transportation System performances.
The paper describes the above listed new features of TRITONE that combined with the calculation of road safety indicators evaluations allow planners to benefit from the availability of a useful and innovative tool for traffic simulation.
TRITONE: Un microsimulatore per l’inquinamento acustico
Tritone e sistemi GIS: una coppia vincente
https://www.researchgate.net/publication/316166239_Tritone_e_sistemi_GIS_una_coppia_vincente