ترغب بنشر مسار تعليمي؟ اضغط هنا

Simulating the interaction of road users: A glance to complexity of Venezuelan traffic

69   0   0.0 ( 0 )
 نشر من قبل Juan C. Correa
 تاريخ النشر 2016
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

Automotive traffic is a classical example of a complex system, being the simplest case the homogeneous traffic where all vehicles are of the same kind, and using different means of transportation increases complexity due to different driving rules and interactions between each vehicle type. In particular, when motorcyclists drive in between the lanes of stopped or slow-moving vehicles. This later driving mode is a Venezuelan pervasive practice of mobilization that clearly jeopardizes road safety. We developed a minimalist agent-based model to analyze the interaction of road users with and without motorcyclists on the way. The presence of motorcyclists dwindles significantly the frequency of lane changes of motorists while increasing their frequency of acceleration-deceleration maneuvers, without significantly affecting their average speed. That is, motorcyclist corralled motorists in their lanes limiting their ability to maneuver and increasing their acceleration noise. Comparison of the simulations with real traffic videos shows good agreement between model and observation. The implications of these results regarding road safety concerns about the interaction between motorists and motorcyclists are discussed.



قيم البحث

اقرأ أيضاً

222 - Jingyuan Wang , Yu Mao , Jing Li 2014
Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behav ior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any a priori knowledge of drivers origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion.
Traffic breakdown, as one of the most puzzling traffic flow phenomena, is characterized by sharply decreasing speed, abruptly increasing density and in particular suddenly plummeting capacity. In order to clarify its root mechanisms and model its obs erved properties, this paper proposes a car-following model based on the following assumptions: (i) There exists a preferred time-varied and speed-dependent space gap that cars hope to maintain; (ii) there exists a region R restricted by two critical space gaps and two critical speeds in the car following region on the speed-space gap diagram, in which cars movements are determined by the weighted mean of the space- gap-determined acceleration and the speed-difference-determined acceleration; and (iii) out of region R, cars either accelerate to the free flow speed or decelerate to keep safety. Simulation results show that this model is able to simultaneously reproduce traffic breakdown and the transition from the synchronized traffic flow to wide moving jams. To our knowledge, this is the first car-following model that is able to fully depict traffic breakdown, spontaneous formation of jams, and the concave growth of the oscillations.
New York City (NYC) is entering Phase 4 of the states reopening plan, starting July 20, 2020. This white paper updates travel trends observed during the first three reopening phases and highlights the spatial distributions in terms of bus speeds and Citi Bike trips, and further investigates the role of micro-mobility in the pandemic response.
This article analyzes the complex geometry of urban transportation networks as a gateway to understanding their encompassing urban systems. Using a proposed ring-buffer approach and applying it to 50 urban areas in the United States, we measure road lengths in concentric rings from carefully-selected urban centers and study how the trends evolve as we move away from these centers. Overall, we find that the complexity of urban transportation networks is naturally coupled, consisting of two distinct patterns: (1) a fractal component (i.e., power law) that represent a uniform grid, and (2) a second component that can be exponential, power law, or logarithmic that captures changes in road density. From this second component, we introduce two new indices, density index and decay index, which jointly capture essential characteristics of urban systems and therefore can help us gain new insights into how cities evolve.
Selecting an appropriate clustering method as well as an optimal number of clusters in road accident data is at times confusing and difficult. This paper analyzes shortcomings of different existing techniques applied to cluster accident-prone areas a nd recommends using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Ordering Points To Identify the Clustering Structure (OPTICS) to overcome them. Comparative performance analysis based on real-life data on the recorded cases of road accidents in North Carolina also show more effectiveness and efficiency achieved by these algorithms.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا