Traffic congestion

About: Traffic congestion is a research topic. Over the lifetime, 16826 publications have been published within this topic receiving 235654 citations. The topic is also known as: traffic jam & traffic snarl-up.

Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis

Abstract: Recently, many efforts have been made to develop more efficient Inter-Vehicle Communication (IVC) protocols for on-demand route planning according to observed traffic congestion or incidents, as well as for safety applications. Because practical experiments are often not feasible, simulation of network protocol behavior in Vehicular Ad Hoc Network (VANET) scenarios is strongly demanded for evaluating the applicability of developed network protocols. In this work, we discuss the need for bidirectional coupling of network simulation and road traffic microsimulation for evaluating IVC protocols. As the selection of a mobility model influences the outcome of simulations to a great extent, the use of a representative model is necessary for producing meaningful evaluation results. Based on these observations, we developed the hybrid simulation framework Veins (Vehicles in Network Simulation), composed of the network simulator OMNeT++ and the road traffic simulator SUMO. In a proof-of-concept study, we demonstrate its advantages and the need for bidirectionally coupled simulation based on the evaluation of two protocols for incident warning over VANETs. With our developed methodology, we can advance the state-of-the-art in performance evaluation of IVC and provide means to evaluate developed protocols more accurately.

Urban Computing: Concepts, Methodologies, and Applications

Abstract: Urbanization's rapid progress has modernized many people's lives but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated in cities (e.g., traffic flow, human mobility, and geographical data). Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems, and the environment. Urban computing is an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology in the context of urban spaces. This article first introduces the concept of urban computing, discussing its general framework and key challenges from the perspective of computer sciences. Second, we classify the applications of urban computing into seven categories, consisting of urban planning, transportation, the environment, energy, social, economy, and public safety and security, presenting representative scenarios in each category. Third, we summarize the typical technologies that are needed in urban computing into four folds, which are about urban sensing, urban data management, knowledge fusion across heterogeneous data, and urban data visualization. Finally, we give an outlook on the future of urban computing, suggesting a few research topics that are somehow missing in the community.

A study of traffic capacity

Abstract: The results of a traffic capacity study started in june 1934 by the traffic bureau of the ohio state highway department are presented. The data were collected by the photographic method described in volume 13 of the PROCEEDINGS OF THE HIGHWAY RESEARCH BOARD. After a brief description of the method of collecting and tabulating the information, certain selected data are analyzed to secure a measure of the working capacity of a two-lane roadway and the amount of vehicle time lost under varying degrees of congestion. The study of 1180 groups of 100 vehicles each, including not over 10 percent trucks, reveals the average free moving speed to be about 43 miles per hour on either a two or three lane road. When the number of vehicles exceeds 400 to 600 per hour, the average speed decreases and the effect of a few slow-moving vehicles is more pronounced. The mean speed of 859 light trucks was 41.0 miles per hour, and of 225 heavy trucks, 32.4 miles per hour. for 18 buses, the average was 41.6 miles per hour. In the discussion, Mr. Bibbins discusses the method of obtaining over-all speeds over a stretch of highway by recording the tag number of the vehicle entering the stretch and checking the same tag number on leaving. Mr. Canning describes a method of obtaining average running speed. Mr. Miller discusses measurement of traffic delay by traffic counts and the progress of an automobile in traffic. The record of progress is obtained by means of an instrument attached to the automobile which marks a graduated ribbon indicating the speed of the vehicle and the time loss due to cross traffic, stop lights, slow moving traffic, congestion, road conditions, etc. In Pennsylvania, a number of touring cars were equipped with Recordographs that indicate the speed of a car graphically on a ribbon. The Recordograph traffic analysis was found to be an accurate method of determining the traffic capacity of highways and valuable aid in determining traffic conditions.

Review of road traffic control strategies

Abstract: Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. After illustrating the main reasons for infrastructure deterioration due to traffic congestion, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance. Selected application results, obtained from either simulation studies or field implementations, are briefly outlined to illustrate the impact of various control actions and strategies. The paper concludes with a brief discussion of future needs in this important technical area.