scholarly journals Reconfigurable SRTM System for Road Traffic in Kingdom of Bahrain

2016 ◽  
Vol 17 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Wael El-Medany ◽  
Alauddin Al-Omary ◽  
Riyadh Al-Hakim ◽  
Taher Homeed
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Traffic Signals ◽  
Google Maps ◽  
Traffic System ◽  
The Road ◽  
Field Programmable ◽  
Hardware Description ◽  
Traffic Management System ◽  
On The Road

Abstract This paper presents reconfigurable hardware architecture for smart road traffic system based on Field Programmable Gate Array (FPGA). The design can be reconfigured for different timing of the traffic signals according to the received and collected data read by the different sensors on the road; the design has been described using VHDL (VHSIC Hardware Description Language). The SRTM (Smart Road Traffic Management) System has some more features that help passenger to avoid traffic jamming by sending the collected information through web/mobile applications to find the best road between the start and destination points, which will be displayed on Google maps, at the same time it will also shows the points of traffic jamming on Google maps. SRTM system can also manage emergency vehicles such as ambulance and fire fighter and also can send snapshots and video streaming for different roads and junctions to show the points of traffic jamming. The design has been simulated and tested using ModelSim PE student edition 10.4. Spartan 3 FPGA starter kit from Xilinx has been used for implementing and testing the design in a hardware level.

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

Landscape Design of City Road

2014 ◽  
Vol 1065-1069 ◽  
pp. 2753-2756 ◽  
Author(s):  
Yong Zhang
Keyword(s):  
Main Part ◽  
Road Traffic ◽  
Landscape Design ◽  
Road Vehicles ◽  
Visual Effects ◽  
Traffic Demand ◽  
Traffic System ◽  
The Road ◽  
On The Road ◽  
The City

the road is the main part of city traffic system, connects the different functions of the city land. The actual function of road traffic and space includes two functions. As the bus approaches of road vehicles and personnel, with clear guidance, on both sides of the road environment landscape should be consistent with the requirements and guidance, achieve walking King visual effects shift. Planting and pavement texture color road side of the choice should have the sense of rhythm and ornamental. To meet the traffic demand at the same time, the road can form an important view corridor. Therefore, the design should pay attention to the landscape and vision on the road, in order to strengthen the focus of the landscape.

Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System

2020 ◽  
pp. 750-765
Author(s):  
Shamim Akhter ◽  
Rahatur Rahman ◽  
Ashfaqul Islam
Keyword(s):  
Neural Network ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Integrated Approach ◽  
Management Support ◽  
The Road ◽  
Multiple Data ◽  
Management Support Systems ◽  
Traffic Management System

Low-cost, flexible, easily maintainable and secure traffic management support systems are in demand. Internet-based real time bi-directional communication provides significant benefits to monitor road traffic conditions. Dynamic route computation is a vital requirement to make the traffic management system more realistic and reliable. Therefore, an integrated approach with multiple data feeds and Backpropagation (BP) Neural Network (NN) with Levenberg-Marquardt (LM) optimization is applied to predict the road weights. The results indicate that the proposed traffic system/tool with NN based dynamic weights computation is much more effective to find the optimal routes. The BP NN with LM optimization achieves 96.67% accuracy.

On the Road Traffic Signals

1980 ◽  
Vol 64 (6) ◽  
pp. 315-318
Author(s):  
Hiroyuki Koyama ◽  
Hikaru Masaki ◽  
Joji Inagaki
Keyword(s):  
Road Traffic ◽  
Traffic Signals ◽  
The Road ◽  
On The Road

Design and Implementation of an Intelligent Traffic Management System

2019 ◽  
pp. 58-79 ◽  
Author(s):  
Shamim Akhter ◽  
Sakhawat Hosain Sumit ◽  
Md. Rahatur Rahman
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Route Planning ◽  
Efficient Solutions ◽  
The Road ◽  
Decision Attributes ◽  
Software Modules ◽  
Traffic Management System

Intelligence traffic management system (ITMS) provides effective and efficient solutions toward the road traffic management and decision-making problems, and thus helps to reduce fuel consumption and emission of greenhouse gases. Software-based real-time bi-directional TMS with a neural network was proposed and implemented. The proposed TMS solves a decision problem, dynamic road weights calculation, using different environmental, road and vehicle related decision attributes. In addition, the development of the real-time operational models as well as their solving challenges has increased in a rapid manner. Therefore, the authors integrate the design and development of a neural-based complete real-time operational ITMS, with the combination of software modules including traffic monitoring, road weight updating, forecasting, and optimum route planning decision. Collecting, extracting the insights and inherit meaning, and modeling the tremendous amount of continuous data is a challenging task. A discussion is also included with the future improvements on ITMS.

scholarly journals Novel Road Traffic Management Strategy for Rapid Clarification of the Emergency Vehicle Route Based on V2V Communications

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5120
Author(s):  
Radwa Ahmed Osman ◽  
Amira I. Zaki ◽  
Ahmed Kadry Abdelsalam
Keyword(s):  
Traffic Management ◽  
Management Strategy ◽  
Road Traffic ◽  
Emergency Vehicle ◽  
The Road ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Proposed Model ◽  
V2v Communications ◽  
On The Road

Vehicle-to-vehicle communication is a promising paradigm that enables all vehicles in the traffic road to communicate with each other to enhance traffic performance and increase road safety. Through vehicle-to-vehicle (V2V) communication, vehicles can understand the traffic conditions based on the information sent among vehicles on the road. Due to the potential delay caused by traffic jams, emergency vehicles may not be able to reach their destination in the required time, leading to severe losses. The case is more severe especially in developing countries where no emergency-vehicle-dedicated lanes are allocated. In this study, a new emergency vehicle route-clarifying strategy is proposed. The new clarifying strategy is based on vehicular traffic management in different interference medium scenarios. The proposed model aims, through V2V communication, to find the nearest vehicle with which to communicate. This vehicle plays an important role in reducing the travel time: as the emergency message is received, this vehicle will immediately communicate with all the neighboring vehicles on the road. Based on V2V communications, all the vehicles in the road will clear from the lane in the road for the emergency vehicle can safely reach its destination with the minimum possible travel time. The maximum distance between the emergency vehicle and the nearest vehicle was determined under different channel conditions. The proposed strategy applied an optimization technique to find the varied road traffic parameters. The proposed traffic management strategy was evaluated and examined through different assumptions and several simulation scenarios. The obtained results validated the effectiveness and the accuracy of the proposed model, and also indicated significant improvement in the network’s performance in terms of packet delivery ratio (PDR) and average end-to-end delay (E2E).

Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System

2016 ◽  
Vol 7 (4) ◽  
pp. 45-59 ◽  
Author(s):  
Shamim Akhter ◽  
Rahatur Rahman ◽  
Ashfaqul Islam
Keyword(s):  
Neural Network ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Low Cost ◽  
Integrated Approach ◽  
Management Support ◽  
The Road ◽  
Multiple Data ◽  
Traffic Management System

Low-cost, flexible, easily maintainable and secure traffic management support systems are in demand. Internet-based real time bi-directional communication provides significant benefits to monitor road traffic conditions. Dynamic route computation is a vital requirement to make the traffic management system more realistic and reliable. Therefore, an integrated approach with multiple data feeds and Backpropagation (BP) Neural Network (NN) with Levenberg-Marquardt (LM) optimization is applied to predict the road weights. The results indicate that the proposed traffic system/tool with NN based dynamic weights computation is much more effective to find the optimal routes. The BP NN with LM optimization achieves 96.67% accuracy.

scholarly journals Analysis of ITMS System Impact Mechanism in Beijing Based on FD and Traffic Entropy

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ailing Huang ◽  
Wei Guan ◽  
Yimei Chang ◽  
Zhen Yang
Keyword(s):  
Positive Feedback ◽  
Intelligent Transportation Systems ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Fundamental Diagram ◽  
Impact Mechanism ◽  
Traffic System ◽  
The Road ◽  
On The Road

Although more attention has been attracted to benefit evaluation of Intelligent Transportation Systems (ITS) deployment, how ITS impact the traffic system and make great effects is little considered. As a subsystem of ITS, in this paper, Intelligent Transportation Management System (ITMS) is studied with its impact mechanism on the road traffic system. Firstly, the correlative factors between ITMS and the road traffic system are presented and 3 positive feedback chains are defined. Secondly, we introduce the theory of Fundamental Diagram (FD) and traffic system entropy to demonstrate the correlative relationship between ITMS and feedback chains. The analyzed results show that ITMS, as a negative feedback factor, has damping functions on the coupling relationship of all 3 positive feedback chains. It indicates that with its deployment in Beijing, ITMS has impacted the improvement of efficiency and safety for the road traffic system. Finally, related benefits brought by ITMS are presented corresponding to the correlative factors, and effect standards are identified for evaluating ITMS comprehensive benefits.

scholarly journals A Pick-Up Points Recommendation System for Ridesourcing Service

2019 ◽  
Vol 11 (4) ◽  
pp. 1097 ◽  
Author(s):  
Wanqiu Zhu ◽  
Jian Lu ◽  
Yi Yang
Keyword(s):  
Traffic Management ◽  
Recommendation System ◽  
Road Traffic ◽  
Second Step ◽  
Huge Amount ◽  
Analytic Hierarchy ◽  
The Road ◽  
Spatial Distribution Characteristics ◽  
On The Road

In the ridesourcing industry, drivers are often unable to quickly and accurately locate the waiting position of riders, but patrol or wait on the road, which will seriously affect the management of the road traffic order. It may be a good idea to provide an online virtual site for the taxi to facilitate convergence of the rider and driver. The concept of recommended pick-up point is presented in this paper. At present, ridesourcing service platforms on the market have similar functions, but they do not take into account whether the setting of the pick-up point is compatible with the actual traffic environment, resulting in some problems. We have invented a method to select the recommended pick-up point by integrating various traffic influencing factors, so as to ensure that the setting of the pick-up point is compatible with the actual traffic situation, which consists of three steps. Firstly, we studied the rider’s maximum tolerable waiting time and defined an attractive walking range for riders based on the huge amount of data. In the second step, we analyzed spatial distribution characteristics of the taxi demand hotspot and determined candidate pick-up locations. Lastly, the fuzzy analytic hierarchy method was used to select the recommended pick-up point that is most conducive to traffic management from multiple candidate points. A case study was conducted to validate the proposed approach and experimental evidence showed that recommended results based on the approach are in line with the actual situation of the road, and conducive to road traffic management. This recommendation method is based on real ridesourcing orders data.

Sign in / Sign up

Export Citation Format

Share Document