Road Network Simulation Using FLAME GPU

Demand for high performance road network simulation is increasing due to the need for improved traffic management to cope with the globally increasing number of road vehicles and the poor capacity utilisation of existing infrastructure. This paper demonstrates FLAME GPU as a suitable Agent Based Simulation environment for road network simulations, capable of coping with the increasing demands on road network simulation. Gipps’ car following model is implemented and used to demonstrate the performance of simulation as the problem size is scaled. The performance of message communication techniques has been evaluated to give insight into the impact of runtime generated data structures to improve agent communication performance. A custom visualisation is demonstrated for FLAME GPU simulations and the techniques used are described

Combination of simulation and model-checking for the analysis of autonomous vehicles’ behaviors: A case study

International audienceAutonomous vehicles’ behavioural analysis represents a major challenge in the automotive world. In order to ensure safety and fluidity of driving, various methods are available, in particular, simulation and formal verification. The analysis, however, has to cope with very complex environments depending on many parameters evolving in real time. In this context, none of the aforementioned approaches is fully satisfactory, which lead us to propose a combined methodology in order to point out suspicious behaviours more efficiently. We illustrate this approach by studying a non deterministic scenario involving a vehicle, which has to react to some perilous situation

Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c

Basic Driving Dynamics of Cyclists

In this work we introduce the Necessary-Deceleration-Model (NDM) which is a car-following-model developed to investigate driving behavior of bicycles. For this purpose the derivation of the mathematical description of the NDM is investigated. For the sake of calibration and validation of the model, several experiments are performed. The results of the experiments are presented and examined. Finally, the limits and possibilities of the NDM are discussed

Towards Eliminating Overreacted Vehicular Maneuvers: Part II Comparative Analyses

\ua9 2019, Springer Nature Singapore Pte Ltd. Microscopic car following models are of great importance to traffic flow studies and vehicular dynamics reproducing. The Full Velocity Difference (FVD) model is a well-known example with satisfactory simulation performances in most times. However, by analyzing the structure of the model formula, we find that it can sometimes generate overreacted vehicular maneuvers such as unrealistically strong (overshooting for short) accelerations or decelerations that conflict with normal driver habits or even beyond the actual vehicular acceleration/deceleration performance, especially when the target vehicle encounter a leader cut-in or move-out (leader lane change for short). As Part II of the entire research, this paper conducts performance comparative analyses between the existing FVD model and the capped Full Velocity Difference (capped-FVD) model introduced in Part I of the research (the other companion paper) to address the above deficiency, and the results indicate that both models are equivalent in most times but the capped-FVD model will outperform the existing FVD model in aforementioned traffic scenarios since overreacted vehicular maneuvers (overshooting accelerations or decelerations) are totally eliminated. In other words, the aforementioned deficiency of the existing FVD model is totally corrected by the capped-FVD model and the capped-FVD model is a better choice for simulating vehicle movements in multi-lane roadways

Towards Eliminating Overreacted Vehicular Maneuvers: Part I Model Development and Calibration

Microscopic car following models are of great importance to traffic flow studies and vehicular dynamics reproducing. The Full Velocity Difference (FVD) model is a well-known example with satisfactory simulation performances in most times. However, by analyzing the structure of the model formulas, we find that it can sometimes generate overreacted vehicular maneuvers such as unrealistically strong (overshooting for short) accelerations or decelerations that conflict with normal driver habits or even beyond the actual vehicular acceleration/deceleration performance, especially when the target vehicle encounter a leader cut-in or move out (leader lane change for short). As Part I of the entire research, this paper corrects the above deficiency of the FVD model by proposing a capped-Full Velocity Difference (capped-FVD) model in which we limit any potential overshooting accelerations or decelerations generated to a reasonable range. Then, all model parameters are also calibrated using field data. Performance comparative analyses to validate the performance improvement of the capped-FVD model are included in the other companion paper serving as Part II of this research

Bionics-Inspired Cellular Automaton Model for Pedestrian Dynamics

We present a 2-dimensional cellular automaton model for the simulation of pedestrian dynamics. Inspired by the principles of chemotaxis the interactions between the pedestrians are mediated by a so-called floor field. This field has a similar effect as the chemical trace created e.g. by ants to guide other individuals to food places. In our case the floor field modifies the transition rates to neighbouring cells. It has its own dynamics (diffusion and decay) and can be changed by the motion of the pedestrians. This means that in our model pedestrians follow a virtual rather than a chemical trace as in the case of chemotaxis. The approach is extremely efficient and makes faster-than-real-time simulations of large crowds possible. Already the inclusion of only nearest-neighbour interactions allows to reproduce many of the collective effects and self-organization phenomena (lane formation, ow oscillations at doors etc.) encountered in pedestrian dynamics