ARCHISIM: a behavioral multi-actors traffic simulation model for the study of a traffic system including ITS aspects (original) (raw)
Related papers
2007
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.
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.
SOME ISSUES CONCERNING THE USE OF SIMULATION IN ADVANCED TRAFFIC MANAGEMENT SYSTEMS
Advanced Traffic Management Systems constitute one of the major envisaged applications of Intelligent Transport Systems. Various architectures and approaches have been proposed and tested in projects of R&D programmes of the European Commission in recent years, as for example ARTIS, KITS and ENTERPRICE, just to mention a few. An approach shared by all of them has been the conception of the system as an intelligent decision support system able of identifying the actual traffic conditions on the network from real time traffic measurements, make a diagnosis of the network state, identify potential or actual conflicts and propose strategies to prevent or alleviate the conflicts. In some cases the decision support functions have been based on evaluating by simulation the scenarios for the proposed management strategies. The simulation provides the human operator with a quantitative basis for the decision making process. A key question on using simulation in this context deals with the model building process in the changing conditions of the real-time decision making framework. This paper discusses some traffic management architectures that use the microscopic simulator AIMSUN2 for these purposes, and describes the structure of a translator that automatically builds the AIMSUN2 simulation model of the selected scenario from GEODYN, an ad hoc Geographic Information System purposely designed for these traffic management applications. Examples from ENTERPRICE project are presented and the quality of the results is discussed.
Periodica Polytechnica Civil Engineering, 2021
It is believed that autonomous vehicles will replace conventional human drive vehicles in the next decades due to the emerging autonomous driving technology, which will definitely bring a massive transformation in the road transport sector. Due to the high complexity of traffic systems, efficient traffic simulation models for the assessment of this disruptive change are critical. The objective of this paper is to justify that the common practice of microscopic traffic simulation needs thorough revision and modification when it is applied with the presence of autonomous vehicles in order to get realistic results. Two high-fidelity traffic simulators (SUMO and VISSIM) were applied to show the sensitivity of microscopic simulation to automated vehicle’s behavior. Two traffic evaluation indicators (average travel time and average speed) were selected to quantitatively evaluate the macro-traffic performance of changes in driving behavior parameters (gap acceptance) caused by emerging aut...
Enhanced Micro-simulation models for accurate safety assessment of traffic management ITS Solutions
2008
Much research has been conducted in the development, implementation, and evaluation of innovative ITS technologies aiming to improve traffic operations and driving safety. Existing micro-simulation modeling only describes normative car-following behaviors devoid of weakness and risks associated with real-life everyday driving. This research aims to develop a new behavioral car-following model that is pertinent to the true nature of everyday human driving. Unlike traditional car-following models that deliberately prohibit vehicle collisions, this new model builds upon multi-disciplinary findings explicitly taking into account perceptual thresholds, judgment errors, anisotropy of reaction times and driver inattention, in order to replicate "less-than-perfect" driving behavior with all its weakness and risks. Most importantly, all parameters of this model have direct physical meaning; this ensures vehicle collisions are replicated as a result of behavioral patterns rather than simply being numerical artifacts of the model. Meanwhile, vehicle trajectories were extracted from real-life crashes collected from a freeway section of I-94WB This is by far the first data collection efforts that aim to collect vehicle trajectories from real-life crashes to aid car-following modeling. These data were employed in this study to test, calibrate and validate the model. This new model is successful in replicating these vehicle trajectories as well as crashes.
Development of a Microscopic Artificially Intelligent Traffic Model for Simulation
2014
Roadway safety continues to be a major public health concern. Recent statistics show that more than 30,000 fatalities occur due to motor vehicle accidents, and in the year 2012, motor vehicle crashes resulted in more than 2 million injuries. As a result of these ongoing trends, simulators continue to become more abundant in applications ranging from Intelligent Transportation Systems (ITS) research, autonomous driving, human factors studies, rehabilitation, and driver training and workload applications. However, many current simulators lack realism with regards to accompanying traffic, which often does not satisfactorily respond to the real-time actions of the human subject who is operating the simulation. Artificial traffic simulation models found within many modern-day driving simulators are often “macroscopic” in nature – they aggregate the description of overall traffic flow, which is based on “idealistic” driver behavior. This lack of network realism (particularly in the vicini...
Simulation and Evaluation of Freeway Traffic Using Interchangeable Behavioral Models
Computing in Civil Engineering (2005), 2005
Microscopic simulation of traffic flow has spawned many different behavioral models, some of them commercially distributed, some developed at academic institutions for scientific purposes. These models are either kept secret (for commercial products) or substantially lacking in terms of usability and visualization. In this paper, we introduce the simulation environment BABSIM that allows for different driving behaviors to be integrated into one common simulation package. An overview of microscopic simulation is given, and several existing models and their implementations are being discussed. The fundamental structure of the BABSIM package, its user interface and the calibration of the model parameters are presented.
Modelling and simulation of urban traffic systems: present and future
Int. J. Cybernetics and Cyber-Physical Systems, 2021
The conflict of supply and demand in urban traffic system causes serious problems nowadays owing to rapid urbanisation worldwide, including traffic congestion, air pollution, etc. In this paper, the recent development of modelling and simulation of urban traffic systems is briefly overviewed, where the macro-, micro-and meso-scopic simulation models, especially the microscopic models are discussed. Three widely used microscopic traffic simulation models are analysed and the new generation traffic simulation technologies for Intelligent Transportation Systems (ITS) are discussed from the perspectives of software technology, hardware technology, and methodologies. The existing problems and challenges in modelling and simulation of urban traffic systems are evaluated and the latest trends and the potential solutions are suggested.
A microsimulation-based analysis for driving behaviour modelling on a congested expressway
Journal of Ambient Intelligence and Humanized Computing
Recently, simulation models have been widely used around the world to evaluate the performance of different traffic facilities and management strategies for efficient and sustainable transportation systems. One of the keys factors for ensuring the reliability of the models in reflecting local conditions is the calibration and validation of microsimulation models. The majority of the existing calibration efforts focus is on the experimental designs of driver behaviour and lane-changing parameters. Towards this end, this paper describes the necessary procedure for the calibration and validation of a microscopic model using the VISSIM software, during peak hours. The procedure is applied on Muscat Expressway in the Sultanate of Oman. The calibration parameters and the measure-of-effectiveness are identified by using multi-parameter sensitivity analysis. The optimum values for these parameters are obtained by minimising errors between simulated data and field data. In our proposed model, we used traffic volume and travel speed for model calibration, as well as average travel time for validation of the calibrated model. The achieved results showed that driving characteristics significantly impacted the merging/ diverging traffic flow ratio in the merging area, the link length and the distance between on-ramps and off-ramps, as well as the percentage of heavy vehicles. The results also showed that having both the advanced merging and cooperative lanechange settings active, along with safety distance reduction factor, necessary lane change, minimum headway (front/rear), and emergency stop, had a significant influence on simulation precision, especially at on-ramps and off-ramps. Finally, our proposed model can be utilized as a base for future traffic strategy analysis and intelligent transportation systems evaluation to help decision makers with long-term and sustainable development decisions.