Study on Road Traffic Condition Identification Based on Floating Taxi

2011 ◽  
Vol 105-107 ◽  
pp. 2250-2254
Author(s):  
Xin Sheng Yao ◽  
Jian Hua Qu ◽  
Ji Lai Ying
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Sampling Interval ◽  
Urban Traffic ◽  
Traffic Information ◽  
Prototype System ◽  
Data Sampling ◽  
Traffic Condition ◽  
Wireless Communication Protocol ◽  
Information Update

This paper describes a prototype system based on floating taxi for traffic condition identification. The system consists of in-vehicle hardware units placed in floating taxi and backstage database that process all data send from the report units. The communication between the taxi and the database center is based on a very compact wireless communication protocol. The taxi sample size is decided by the variables: section traffic information update cycle, data sampling interval, section covering ratio. The test in a road section showed that the system is operational which could offer useful reference for urban traffic management and resident trips decision.

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

scholarly journals EFFECTS OF THE RAINSTORM ON URBAN ROAD TRAFFIC SPEED &mdash; A CASE STUDY OF SHENZHEN, CHINA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 71-75 ◽  
Author(s):  
Q. Li ◽  
X. Hao ◽  
W. Wang ◽  
A. Wu ◽  
Z. Xie
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Urban Traffic ◽  
Gps Tracking ◽  
Shenzhen City ◽  
Adverse Weather ◽  
Stormy Weather ◽  
Wide Scale ◽  
Traffic Speed ◽  
The Impact

The adverse weather may significantly impact urban traffic speed and travel time. Understanding the influence of the rainstorm to urban traffic speed is of great importance for traffic management under stormy weather. This study aims to investigate the impact of rainfall intensity on traffic speed in the Shenzhen (China) during the period 1 July 2015&amp;ndash;31 August 2016. The analysis was carried out for five 1-h periods on weekdays during the morning periods (6:00 AM&amp;ndash;11:00 AM). Taxi-enabled GPS tracking data obtained from Shenzhen city are used in the analysis. There are several findings in this study. Firstly, nearly half of the roads are significantly affected by the rainstorm. Secondly, the proportion of positive correlated roads is about 35&amp;thinsp;%, but there still are some roads with uncorrelated traffic speed variation rates (SVR) and rainfall intensities. Thirdly, the impact of the rainstorm on traffic speed is not homogeneous but with obvious spatial difference. This research provides useful information that can be used in traffic management on a city-wide scale under stormy weather.

scholarly journals Dynamic RFID Identification in Urban Traffic Management Systems

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4225
Author(s):  
Bartosz Pawłowicz ◽  
Bartosz Trybus ◽  
Mateusz Salach ◽  
Piotr Jankowski-Mihułowicz
Keyword(s):  
Radio Frequency Identification ◽  
Traffic Management ◽  
Road Traffic ◽  
Object Identification ◽  
Urban Traffic ◽  
Mobile Object ◽  
Identification System ◽  
Dynamic Identification ◽  
Vehicle Identification ◽  
Simplified Algorithm

The paper covers the application of Radio Frequency IDentification (RFID) technology in road traffic management with regard to vehicle identification. Various infrastructure configurations for Automated Vehicle Identification (AVI) have been presented, including configurations that can be used in urban traffic as part of the Smart City concept. In order to describe the behavior of multiple identifications of moving vehicles, an operation model of the dynamic identification using RFID is described. While it extends the definition of the correct work zone, this paper introduces the concept of dividing the zone into sections corresponding to so-called inventory rounds. The system state is described using a set of matrices in which unread, read, and lost transponders are recorded in subsequent rounds and sections. A simplified algorithm of the dynamic object identification system was also proposed. The results of the simulations and lab experiments show that the efficiency of mobile object identification is conditioned by the parameters of the communication protocol, the speed of movement, and the number of objects.

Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)

2021 ◽  
Vol 17 (2) ◽  
pp. 46-71
Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Transportation Systems ◽  
Traffic Information ◽  
Traffic Characteristics ◽  
Traffic Video ◽  
Virtual Loop

Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.

scholarly journals Authors: Yunhui Zeng ; Wenjuan Hu ; Hongfei Guo ; Shiyue Shen ; Li Huang ; Yiying Lou

2019 ◽  
pp. 57-66
Author(s):  
Yunhui Zeng ◽  
Wenjuan Hu ◽  
Hongfei Guo ◽  
Shiyue Shen ◽  
Li Huang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Spline Interpolation ◽  
Road Construction ◽  
Traffic Condition ◽  
The Road ◽  
Traffic Capacity ◽  
Significant Difference ◽  
The Difference

Focused on the lane occupancy phenomenon, this paper analyzes the roads during two different accidents to the evacuation period. Firstly, according to the statistical data, this paper calculated the correction coefficients under the road traffic condition, and then obtained the actual traffic capacity result at each moment of the road when combining the function model of the actual traffic capacity corrected by the running speed and the road traffic condition. Next the actual traffic capacity results are fitted to the Smooth spline interpolation, and then the actual traffic capacity is further verified by the traffic congestion situation. The actual traffic capacity of the road during the accident to evacuation is summarized as follows: the actual traffic capacity shows a nonlinear trend, that is, ascending-attenuating-recovering and gradually stabilizing. Finally, using Mann-Whitney U test to carry out the difference test on the actual traffic capacity, it is found that there is significant difference between the two groups of data, and the actual traffic capacity of the second case is stronger than that of the first one, and the reasons for the difference are analyzed as follows: the ratio of the steering traffic volume at the downstream intersection is different; this road section includes the community intersection and there are vehicles entering and leaving; meanwhile the speed of each lane is different and there are buildings near the lane. The above conclusions will provide theoretical basis for the traffic management department to correctly guide the vehicle driving, approve the road construction, design the road channelization plan, set the roadside parking space and the non-port-type bus stations.

DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

2021 ◽  
Author(s):  
Matheus Bernardino de Araújo ◽  
Matheus Monteiro Silveira ◽  
Rafael Lopes Gomes
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Network Flows ◽  
Urban Traffic ◽  
Traffic Information ◽  
Transport Systems ◽  
Packet Delivery ◽  
Vehicle Accidents ◽  
Average Travel Time ◽  
Definition Of

Intelligent Transport Systems (ITS) arose as a modern solution to traffic jams and vehicle accidents in the urban environment. A key part of the ITS is Traffic Management (TM), which concerns the planning and route definition of the vehicle. Existing TM solution focuses specifically on urban traffic information, ignoring the issues related to the network infrastructure and the applications at the top of it. Within this context, this paper presents a vehicle routing and re-routing strategy, called DINO, that considers both travel time of vehicles on the roads and the active network flows in the network, aiming to dynamically bring a suitable balance between travel time and packet delivery through a heuristic. The experiments performed suggest that DINO improves the packet delivery of the applications while reduces the average travel time of vehicles.

Going with the Flow - Computer Visualization of Road Traffic Information

1993 ◽  
Vol 37 (4) ◽  
pp. 353-357
Author(s):  
John Murray ◽  
Yili Liu
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Road Traffic ◽  
Human Subjects ◽  
Traffic Information ◽  
Color Coding ◽  
Control Center ◽  
Computer Visualization ◽  
Vehicular Speed ◽  
Real State

Advanced road traffic management systems provide numerous opportunities for the application of sophisticated computer visualization concepts. The operating staff in a traffic control center are required to assimilate large quantities of incoming data in order to determine the real state of traffic flow and congestion. Part of the incoming data relates to vehicular speed and density, and is often not subjected to sufficient pre-processing before presentation in tabular form on a video display terminal (VDT). Improvements in the format of the tabular information are therefore worthy of investigation. A traffic control simulation experiment was conducted to examine how human subjects extract information from VDT data presented in several different formats. Subjects were asked to respond to exceptional values which occurred randomly in tabular columns of frequently changing data. Their accuracy and reaction time were measured for data columns which were sorted or unsorted, and for data which was presented either numerically or color-coded. Analysis of the results suggests that both sorting and color-coding are significant in reducing response time, and that color-coding is appreciably more effective in this regard.

Sign in / Sign up

Export Citation Format

Share Document