Crowding effects in vehicular traffic

While the impact of crowding on the diffusive transport of molecules within a cell is widely studied in biology, it has thus far been neglected in traffic systems where bulk behavior is the main concern. Here, we study the effects of crowding due to car density and driving fluctuations on the transport of vehicles. Using a microscopic model for traffic, we found that crowding can push car movement from a superballistic down to a subdiffusive state. The transition is also associated with a change in the shape of the probability distribution of positions from negatively-skewed normal to an exponential distribution. Moreover, crowding broadens the distribution of cars' trap times and cluster sizes. At steady state, the subdiffusive state persists only when there is a large variability in car speeds. We further relate our work to prior findings from random walk models of transport in cellular systems.Comment: 23 pages, 11 figures, accepted for publication in PLoS ON

Comparison between Floating Car Data and Infrastructure Sensors for Traffic Speed Estimation

The development of new generation Intelligent Vehicle Technologies will enable a better level of road safety and CO2 emission reductions. However, the bottleneck of all of these systems is the need of a comprehensive and reliable data. For traffic data acquisition, two sources are available today: infrastructure sensors and floating vehicles. The first ones consist on a set of static underground sensors installed in the roads; the second ones consist of the use of intelligent vehicles as mobile sensors. Both of them make use of different communication systems, V2V, V2I and I2I. In this paper we present a comparison of the performance of both kinds of traffic data source for road traffic speed estimation. A set of real experiments has been performed in several traffic conditions, using infrastructure sensors and the information retrieved by one instrumented intelligent vehicle. After processing these data, the results show the better accuracy of the floating cat data as well as its low cost in the case of a massive implantation

Prototype system development for wireless vehicle speed monitoring

Vehicle speed monitoring and management of the associated data in an intelligent and efficient way is an important issue in modern transportation system in order to reduce road accidents. The aim of this work is to develop an automatic wireless system for monitoring vehicle speed on the road, identify a speeding vehicle and imposing penalty for the speeding offenders. In this work, a prototype system has been developed in a laboratory environment to generate random speed data using a mechanical wheel, measure the speed data with a Shimmer wireless sensor and transfer the data wirelessly to a client computer for further analysis. Software has been developed using a Java based socket programming technique to monitor the vehicle speed in a server computer and to send the data associated with a speeding vehicle to a remotely placed client computer. The graphical user interface (GUI) can visually display the speed of a vehicle at any particular time. The functionality of the software has been tested by simulating different traffic scenarios with low and high speed limits (40 and 60 km/hr respectively). To do that a high or low speed limit can be set in the GUI. The mechanical wheel is run at different speeds and the GUI continuously displays the speed. If the vehicle speed is higher than the set speed limit for the road, the system automatically detects it and generates a report with the time of speeding, vehicle number, vehicle speed etc. to be saved in the client computer in order to take further necessary actions for the speeding offender

Vision-Based Traffic Data Collection Sensor for Automotive Applications

This paper presents a complete vision sensor onboard a moving vehicle which collects the traffic data in its local area in daytime conditions. The sensor comprises a rear looking and a forward looking camera. Thus, a representative description of the traffic conditions in the local area of the host vehicle can be computed. The proposed sensor detects the number of vehicles (traffic load), their relative positions and their relative velocities in a four-stage process: lane detection, candidates selection, vehicles classification and tracking. Absolute velocities (average road speed) and global positioning are obtained after combining the outputs provided by the vision sensor with the data supplied by the CAN Bus and a GPS sensor. The presented experiments are promising in terms of detection performance and accuracy in order to be validated for applications in the context of the automotive industry

A Study on Vehicle Trajectory Analysis

Successful developments of effective real-time traffic management and information systems demand high quality real time traffic information. In the era of intelligent transportation convergence, traffic monitoring requires traffic sensory technologies. The present analysis extracted data from Mobile Century experiment. The data obtained in the experiment was pre-processed. Based on the pre processed data experimental road map has generated. Individual vehicle tracking has done using trajectory analysis. Finally an attempt has been made for extracting association rules from mobile century dataset using Apriori algorithm

Addressing the new normal and the future of transport: the future of transport data collection using floating car data

The COVID-19 pandemic has impacted many sectors in countries, and transport is one of them. Due to the new normal of staggered working systems, traffic congestion still proves a problem. Nonetheless, transport institutions should work tirelessly to improve the transport network by reducing travel time, reducing GHG emissions, and ensuring safety. However, traffic data is an essential entity to enhance the transport system. The essay aims to present the future of transport data collection using Floating Car Data (FCD). The data is highly available and quite affordable. Using such data helps prevail over the lack of other data collection systems, which prove expensive. The essay further illustrates the relevance of such data stipulating its advantages and disadvantages. Also, a discussion on the application of FCD follows, citing some research studies conducted in transport management. The essay concludes by asserting the use of FCD in developing countries to aid traffic management systems. It also recommends further studies in traffic management using FCD and transport institutions in respective countries to possess their FCD collection system to analyse the traffic independently.Papers presented at the 40th International Southern African Transport Conference on 04 -08 July 202

Traffic Routing in Urban Environments: the Impact of Partial Information

There are many studies concerning the problem of traffic congestion in cities. One of the best accepted solutions to relieving congestion involves optimization of resources already available, by means of balancing traffic flows to minimize travel delays. To achieve this optimization, it is necessary to collect and process Floating Car Data (FCD) from vehicles. In this paper we evaluate the repercussions of partial information on the overall traffic view, and consequently on the outcome of the optimization. Our study focuses on the role of the user participation rate and the availability of Road Side Units to collect the FCD. By means of simulation we quantify the impact of partially-available information on the computation of route optimization, and how it impedes traffic flows. Our results show that even minor uncertainties can significantly impact routing strategies and lead to deterioration in the overall traffic situation

Floating Car Data Technology

The limiting conditions of traffic in cities, together with the complex and dynamic traffic flows, require an efficient and systematic management and information provision for the traffic participants, with the goal to achieve better utilisation of traffic resources and preserve sustainable mobility. In that context, it is important to identify the traffic flow location features, which requires data and information. This paper presents the application of mobile vehicles for the collection of real time traffic flow data. Such data have become an important source of traffic data, since they can be collected in a simple and cost-efficient way, enabling higher coverage than the conventional approaches, despite the reliability issues. The term referring to that type of data collection, commonly used in scientific and professional literature is FCD (Floating Car Data) and “Probe vehicle”. The efficiency presentation of applying this extensive data source for retrieving necessary parameters and information related to the achievement of sustainable mobility is the final objective of this paper. A description of modern technologies that serve as a basis for probe vehicle data collection has been provided: a geographical information system (GIS), global navigation satellite system (GNSS) and related wireless communication. Within the key technologies review, the development possibilities of data collection by mobile sensors have also been presented