Stuck on the Road: Traffic Congestion and Stock Returns

2017 ◽  
Author(s):  
Serkan Imisiker
Keyword(s):  
Stock Returns ◽  
Traffic Congestion ◽  
Road Traffic ◽  
The Road ◽  
On The Road ◽  
Road Traffic Congestion

scholarly journals INTELLIGENT CAR PARKING SYSTEM

2014 ◽  
pp. 261-267
Author(s):  
S. AVINASH ◽  
SNEHA MITTRA ◽  
SUDIPTA NAYAN GOGOI ◽  
C. SURESH
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Empty Space ◽  
The West ◽  
The Road ◽  
Design And Implementation ◽  
Dc Motors ◽  
Parking System ◽  
Machine Interface ◽  
On The Road

Due to the proliferation in the number of vehicles on the road, traffic problems are bound to exist. This is due to the fact that the current transportation infrastructure and car parking facility developed are unable to cope with the influx of vehicles on the road. In India, the situation are made worse by the fact that the roads are significantly narrower compared to the west. Therefore problems such as traffic congestion and insufficient parking space inevitably crops up. In his paper we describe an Intelligent Car Parking System, which identifies the available spaces for parking using sensors, parks the cars in an identified empty space and gets the car back from its parked space without the help of any human personnel. A Human Machine Interface (HMI) helps in entering a unique identification number while entry of any car which helps in searching for the space where the car is parked while exit. An Indraconrol L10 PLC controls the actions of the parking system. The PLC is used to sequence the placing and fetching of the car via DC motors. We have implemented a prototype of the system. The system evaluation demonstrates the effectiveness of our design and implementation of car parking system.

scholarly journals Real-time predication and navigation on traffic congestion model with equilibrium Markov chain

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771876978 ◽  
Author(s):  
Yan Zheng ◽  
Yanran Li ◽  
Chung-Ming Own ◽  
Zhaopeng Meng ◽  
Mengya Gao
Keyword(s):  
Markov Chain ◽  
Real Time ◽  
Traffic Congestion ◽  
Field Experiments ◽  
Road Traffic ◽  
Markov Chain Model ◽  
Chain Model ◽  
The Road ◽  
Shortest Path Algorithms ◽  
On The Road

With the explosive growth of vehicles on the road, traffic congestion has become an inevitable problem when applying guidance algorithms to transportation networks in a busy and crowded city. In our study, the authors proposed an advanced prediction and navigation models on a dynamic traffic network. In contrast to the traditional shortest path algorithms, focused on the static network, the first part of our guiding method considered the potential traffic jams and was developed to provide the optimal driving advice for the distinct periods of a day. Accordingly, by dividing the real-time Global Positioning System data of taxis in Shenzhen city into 50 regions, the equilibrium Markov chain model was designed for dispatching vehicles and applied to ease the city congestion. With the reveals of our field experiments, the traffic congestion of city traffic networks can be alleviated effectively and efficiently, the system performance also can be retained.

scholarly journals A Framework to Reduce Road Congestion by means of Data Analytics

2021 ◽  
Vol 4 (1) ◽  
pp. 287-297
Author(s):  
Anosha Arooj Yousaf ◽  
Najia Saher ◽  
Faisal Shahzad ◽  
Sara Fareed
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Data Analytics ◽  
Road Traffic ◽  
Image Data ◽  
The Road ◽  
Road Planning ◽  
On The Road ◽  
Critical Traffic ◽  
Processing Techniques

The density of vehicles on the road especially in urban areas keeps on increasing to large amount day by day. Especially during the peak hours of the day, large amount of people wastes much of their time in traffic signals. Not only they waste energy by burning excess fuel and releasing CO2 emissions in the environment as well as their time and money. An idea has been proposed to monitor the traffic congestion by means of data analytics on image data and solve the critical traffic congestion issue. The CCTV or surveillance cameras installed at the top points on the roads acts as a medium to provide image data as an input to analyze road traffic congestion by counting the number of vehicles under specified interval of time. Monitoring of traffic congestion using image processing techniques is very useful for the future urban road planning such as: 1) if there is a need to make the road wider, 2) if there is a need to add more lanes on the road, 3) if there is need to make flyover or a bridge to control the traffic on the roads. It will help municipalities to structure and expansion of the roads.

Video Stream Mining for On-Road Traffic Density Analytics

2012 ◽  
pp. 182-194
Author(s):  
Rudra Narayan Hota ◽  
Kishore Jonna ◽  
P. Radha Krishna
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Video Stream ◽  
Traffic Density ◽  
Svm Classifier ◽  
Stream Mining ◽  
The Road ◽  
Video Frames ◽  
Traffic Congestion Control ◽  
On The Road

Traffic congestion problem is rising day-by-day due to increasing number of small to heavy weight vehicles on the road, poorly designed infrastructure, and ineffective control systems. This chapter addresses the problem of estimating computer vision based traffic density using video stream mining. We present an efficient approach for traffic density estimation using texture analysis along with Support Vector Machine (SVM) classifier, and describe analyzing traffic density for on-road traffic congestion control with better flow management. This approach facilitates integrated environment for users to derive traffic status by mining the available video streams from multiple cameras. It also facilitates processing video frames received from video cameras installed in traffic posts and classifies the frames according to traffic content at any particular instance. Time series information available from various input streams is combined with traffic video classification results to discover traffic trends.

scholarly journals The Study on In-City Capacity Affected by Pedestrian Crossing

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Chang-jiang Zheng ◽  
Rui He ◽  
Xia Wan ◽  
Chen Wang
Keyword(s):  
Traffic Congestion ◽  
Traffic Accident ◽  
Motor Vehicle ◽  
Road Traffic ◽  
The Road ◽  
Simulation Evaluation ◽  
Road Capacity ◽  
Pedestrian Crossing ◽  
Road Traffic Congestion

Currently, the urban road traffic congestion is serious and the traffic accident is happening at a high frequency; thus it has not satisfied the travel needs of security and affects the quality of urban trips. In order to effectively relieve the confliction of people and motor vehicle, to make sure of the safety of pedestrians crossing the road, and to improve the capacity of urban roads, this passage focuses on studying the influence of pedestrians crossing the roads on the capacity of urban roads in three pedestrian crossing approaches including freely crossing the street, uncontrolled crossing of the pedestrian crosswalk, and controlled crossing of the pedestrian crosswalk. Firstly, it confirms the general formula of the road capacity when pedestrians are crossing the road based on three preassumptions, combined with the survey data, and then constructs the empirical mathematical model of pedestrian crossing on the capacity impact. Lastly, it takes the step of case calculation and simulation evaluation and calculates errors between them, finding that the error between the model calculation and software simulation is small. The efficiency of the model is validated and improved.

scholarly journals Does Road Traffic Congestion Increase Fuel Consumption of Households in Kathmandu City?

2021 ◽  
Vol 3 (2) ◽  
pp. 67-79
Author(s):  
Raghu Bista ◽  
Surendra Paneru
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Economic Loss ◽  
Multiple Regression Model ◽  
Urban Life ◽  
Descriptive Statistics ◽  
Additional Time ◽  
The Road ◽  
Urban City ◽  
Road Traffic Congestion

The growth of vehicle and road traffic congestion is characteristics of urbanization and urban city and indicators of urban life in developing countries. In Nepal, non-economic factors and non-state factors have accelerated unexpectedly and haphazardly urbanization process, although the country was reengineered into seven provincial federal structure. In this backdrop, this paper empirically examines the growth of traffic congestion and its impact on urban households and livelihood based on 160 vehicle owners and users’ survey at six major traffic routes of two urban cities by applying mixed analytical methods (qualitative cum quantitative), descriptive statistics and multiple regression model. The descriptive statistics result of the study reveals nearly 94 percent acceptance level of vehicle owners and users about the growth of traffic congestion. Despite short distances of the road i.e. 2-4 kilometers and vehicle efficiency, the growth of traffic congestion increases 14036-liters fuel additional consumption. Per month, additional cost of fuel is estimated at 18,808 US dollars for a sum of distance i.e. 72,992 km between residence location and workplace each month. In the case of commuters, the estimation result of the study is 1188 hours of additional time loss with 6706 US dollars’ worth per month. The estimation of total economic loss is 25514 US dollars per month. Specifically, per month, economic loss of doctors and taxi drivers is 6556 US dollars but teachers and bankers have not economic loss.

scholarly journals Applications of Surveying and Geoinformatics for Planning New Routes to Solve Traffic Congestion in part of Minna Metropolis (Kpakungu, a case study)

2019 ◽  
Vol 3 (1) ◽  
pp. 149-160
Author(s):  
I. C. Onuigbo ◽  
T. Adewuyi ◽  
J. O. Odumosu ◽  
G. A. Oluibukun
Keyword(s):  
Land Use ◽  
Traffic Congestion ◽  
Road Network ◽  
Road Traffic ◽  
Urban Land Use ◽  
Land Use Pattern ◽  
The Road ◽  
National Examination ◽  
Traffic Volumes ◽  
On The Road

The volume of traffic generated by land-use pattern varies during different periods of the day but there is usually a predictable pattern of such traffic volumes. Most often, the structure of urban land-use fails to provide easy and convenient traffic movement, which in the case of the study area is usually that of vehicles and pedestrian traffic. The fact is that Minna is presently experiencing rapid urban growth. Both the authorities and citizens seem to simply ignore this and its impact on human existence. The research is based on Road Traffic Network Analysis in Minna, to develop a road network map and determine the causes of Traffic Congestion in Kpakungu specifically. Quickbird satellite imagery was used in analyzing and mapping out the existing road network within the study area. Field survey aspects involving measuring of roads, traffic count, coordinates captured were also undertaken. It was discovered that the causes of the traffic pressure in the study area was as a result of the relocation of Federal University of Technology, Minna to its permanent site in Gidan Kwanu and the relocation of National Examination Council(NECO) Headquarter. Majority of the traffic pressure in the area were as a result of vehicles coming from Maikunkele, Bosso, Maitumbi, Minna central, Dutsen Kura, Chanchaga, Tunga, Sahuka-kahuta and BarikinSale going to Bida, Gidan-Kwanu or NECO office. It was concluded that alternative roads should be provided for vehicle diversion to limit the congestion of traffic on the road.

Video Stream Mining for On-Road Traffic Density Analytics

2013 ◽  
pp. 1019-1030
Author(s):  
Rudra Narayan Hota ◽  
Kishore Jonna ◽  
P. Radha Krishna
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Video Stream ◽  
Traffic Density ◽  
Svm Classifier ◽  
Stream Mining ◽  
The Road ◽  
Video Frames ◽  
Traffic Congestion Control ◽  
On The Road

Traffic congestion problem is rising day-by-day due to increasing number of small to heavy weight vehicles on the road, poorly designed infrastructure, and ineffective control systems. This chapter addresses the problem of estimating computer vision based traffic density using video stream mining. We present an efficient approach for traffic density estimation using texture analysis along with Support Vector Machine (SVM) classifier, and describe analyzing traffic density for on-road traffic congestion control with better flow management. This approach facilitates integrated environment for users to derive traffic status by mining the available video streams from multiple cameras. It also facilitates processing video frames received from video cameras installed in traffic posts and classifies the frames according to traffic content at any particular instance. Time series information available from various input streams is combined with traffic video classification results to discover traffic trends.

scholarly journals A Route Reservation Approach for an Autonomous Vehicles Routing Problem

2018 ◽  
Vol 220 ◽  
pp. 02004 ◽  
Author(s):  
Anton Agafonov ◽  
Aleksandr Borodinov
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Routing Problem ◽  
Microscopic Traffic Simulation ◽  
The Road ◽  
On The Road ◽  
Road Segments

Autonomous vehicle development is one of many trends that will affect future transport demands and planning needs. Autonomous vehicles management in the context of an intelligent transportation system could significantly reduce the traffic congestion level and decrease the overall travel time in a network. In this work, we investigate a route reservation architecture to manage road traffic within an urban area. The routing architecture decomposes road segments into time and spatial slots and for every vehicle, it makes the reservation of the appropriate slots on the road segments in the selected route. This approach allows to predict the traffic in the network and to find the shortest path more precisely. We propose to use a rerouting procedure to improve the quality of the routing approach. Experimental study of the routing architecture is conducted using microscopic traffic simulation in SUMO package.

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