scholarly journals A Balanced Algorithm for In-City Parking Allocation: A Case Study of Al Madinah City

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3148
Author(s):  
Mohammad A. R. Abdeen ◽  
Ibrahim A. Nemer ◽  
Tarek R. Sheltami
Keyword(s):  
Traffic Congestion ◽  
Arrival Rate ◽  
Transportation Systems ◽  
Limiting Factors ◽  
Parking Lots ◽  
Driving Time ◽  
Parking Spot ◽  
Parking Lot ◽  
Street Traffic

Parking in heavily populated areas has been considered one of the main challenges in the transportation systems for the past two decades given the limited parking resources, especially in city centres. Drivers often waste long periods of time hunting for an empty parking spot, which causes congestion and consumes energy during the process. Thus, finding an optimal parking spot depends on several factors such as street traffic congestion, trip distance/time, the availability of a parking spot, the waiting time on the lot gate, and the parking fees. Designing a parking spot allocation algorithm that takes those factors into account is crucial for an efficient and high-availability parking service. We propose a smart routing and parking algorithm to allocate an optimal parking space given the aforementioned limiting factors. This algorithm supports choosing the appropriate travel route and parking lot while considering the real-time street traffic and candidate parking lots. A multi-objective function is introduced, with varying weights of the five factors to produce the optimal parking spot with the least congested route while achieving a balanced utilization for candidate parking lots and a balanced traffic distribution. A queueing model is also developed to investigate the availability rate in candidate parking lots while considering the arrival rate, departure rate, and the lot capacity. To evaluate the performance of the proposed algorithm, simulation scenarios have been performed for different cases of high and low traffic intensity rates. We have tested the algorithm on in-city parking facility in the city of Al Madinah as a case study. The results show that the proposed algorithm is effective in achieving a balanced utilization of the parking lots, reducing traffic congestion rates on all routes to candidate parking lots, and minimizing the driving time to the assigned parking spot. Additionally, the proposed algorithm outperforms the MADM algorithm in terms of the selected three metrics for the five periods.

Study Behaviour of Passengers on Transit Operation

2011 ◽  
Vol 97-98 ◽  
pp. 1154-1157 ◽  
Author(s):  
Mohammad Hesam Hafezi ◽  
Amiruddin Ismail
Keyword(s):  
Waiting Time ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Operation Time ◽  
Arrival Rate ◽  
Fleet Size ◽  
Transit Operation ◽  
Demand Patterns ◽  
Study Behaviour

Nowadays, delays problem are important issue in preparing schedule for public transportation. It is related to behaviour of passengers, behaviour of transportation means and interaction with traffic. Behaviour of passengers are including: demand patterns of passengers, fare payment and waiting time in station and in-vehicle. Behaviour of transportation means included fleet size and frequency of operation. The most interaction between public transportation and others traffic is in traffic congestion. In this paper, we studies different behaviour of passengers duration operation time in two points: in-station and in-vehicle. They are including: arrival rate of passengers, kinds of fare payment and waiting time. For illustrate behaviour of passengers on delays problem we survey they affects in bus operation. Hence, a case study based on an actual public bus operation in Tehran, Iran is used to demonstrate it.

scholarly journals Parking Functions on Directed Graphs and Some Directed Trees

10.37236/9051 ◽  
2020 ◽  
Vol 27 (2) ◽  
Author(s):  
Westin King ◽  
Catherine H. Yan
Keyword(s):  
Directed Graphs ◽  
Similar Relationship ◽  
Parking Functions ◽  
Directed Path ◽  
Parking Lots ◽  
Parking Spot ◽  
Parking Lot

Classical parking functions can be defined in terms of drivers with preferred parking spaces searching a linear parking lot for an open parking spot. We may consider this linear parking lot as a collection of n vertices (parking spots) arranged in a directed path. We generalize this notion to allow for more complicated “parking lots” and define parking functions on arbitrary directed graphs. We then consider a relationship proved by Lackner and Panholzer between parking functions on trees and “mapping digraphs” and we show that a similar relationship holds when edge orientations are reversed.

scholarly journals A Hybrid Method for Predicting Traffic Congestion during Peak Hours in the Subway System of Shenzhen

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 150 ◽  
Author(s):  
Zhenwei Luo ◽  
Yu Zhang ◽  
Lin Li ◽  
Biao He ◽  
Chengming Li ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Transportation Systems ◽  
Negative Effects ◽  
Agent Based ◽  
Traffic Demand ◽  
Assignment Model ◽  
Subway System

Traffic congestion, especially during peak hours, has become a challenge for transportation systems in many metropolitan areas, and such congestion causes delays and negative effects for passengers. Many studies have examined the prediction of congestion; however, these studies focus mainly on road traffic, and subway transit, which is the main form of transportation in densely populated cities, such as Tokyo, Paris, and Beijing and Shenzhen in China, has seldom been examined. This study takes Shenzhen as a case study for predicting congestion in a subway system during peak hours and proposes a hybrid method that combines a static traffic assignment model with an agent-based dynamic traffic simulation model to estimate recurrent congestion in this subway system. The homes and work places of the residents in this city are collected and taken to represent the traffic demand for the subway system of Shenzhen. An origin-destination (OD) matrix derived from the data is used as an input in this method of predicting traffic, and the traffic congestion is presented in simulations. To evaluate the predictions, data on the congestion condition of subway segments that are released daily by the Shenzhen metro operation microblog are used as a reference, and a comparative analysis indicates the appropriateness of the proposed method. This study could be taken as an example for similar studies that model subway traffic in other cities.

scholarly journals A Peak Traffic Congestion Prediction Method Based on Bus Driving Time

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 709 ◽  
Author(s):  
Zhao Huang ◽  
Jizhe Xia ◽  
Fan Li ◽  
Zhen Li ◽  
Qingquan Li
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Short Term Memory ◽  
Road Traffic ◽  
Prediction Method ◽  
Transportation Systems ◽  
Percentage Error ◽  
Driving Time ◽  
Congestion Prediction ◽  
Congestion Index

Road traffic congestion has a large impact on travel. The accurate prediction of traffic congestion has become a hot topic in intelligent transportation systems (ITS). Recently, a variety of traffic congestion prediction methods have been proposed. However, most approaches focus on floating car data, and the prediction accuracy is often unstable due to large fluctuations in floating speed. Targeting these challenges, we propose a method of traffic congestion prediction based on bus driving time (TCP-DT) using long short-term memory (LSTM) technology. Firstly, we collected a total of 66,228 bus driving records from 50 buses for 66 working days in Guangzhou, China. Secondly, the actual and standard bus driving times were calculated by processing the buses’ GPS trajectories and bus station data. Congestion time is defined as the interval between actual and standard driving time. Thirdly, congestion time prediction based on LSTM (T-LSTM) was adopted to predict future bus congestion times. Finally, the congestion index and classification (CI-C) model was used to calculate the congestion indices and classify the level of congestion into five categories according to three classification methods. Our experimental results show that the T-LSTM model can effectively predict the congestion time of six road sections at different time periods, and the average mean absolute percentage error ( M A P E ¯ ) and root mean square error ( R M S E ¯ ) of prediction are 11.25% and 14.91 in the morning peak, and 12.3% and 14.57 in the evening peak, respectively. The TCP-DT method can effectively predict traffic congestion status and provide a driving route with the least congestion time for vehicles.

How Much Can a Smart Parking System Save You?

2014 ◽  
Vol 22 (4) ◽  
pp. 15-20 ◽  
Author(s):  
Glenn Surpris ◽  
Dahai Liu ◽  
Dennis Vincenzi
Keyword(s):  
Real Time ◽  
Discrete Event Simulation ◽  
Vehicle Emissions ◽  
Discrete Event ◽  
Parking Lots ◽  
Event Simulation ◽  
Parking Spot ◽  
Parking System ◽  
Parking Lot ◽  
Smart Parking

We conducted this study to investigate the effect of smart parking systems on parking search times in large parking lots. Smart parking systems are systems that provide real-time parking spot availability information to drivers. We used discrete event simulation to model a university parking lot and estimate how much time could be saved without physically implementing a system for experimentation. We found that smart parking systems can reduce search times by an average of 11 s. This shows potential for a multi-lot smart parking system that might save a larger amount of time and reduce harmful vehicle emissions.

Parking lot allocation model considering conversion between dynamic and static traffic

2021 ◽  
pp. 1-11
Author(s):  
Zhouhu Xie ◽  
Xianyu Wu ◽  
Jingxue Guo ◽  
Zhenxi Zhan
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Sustainable Transportation ◽  
Distribution Model ◽  
Utilization Rate ◽  
Dynamic Traffic ◽  
Allocation Model ◽  
Parking Lots ◽  
The Road ◽  
Parking Lot

Nowadays, parking spaces are scarce resources in urban cities. Travelers often spend too much time looking for available parking spaces, which increases travel time of travelers and results in additional traffic congestion. With the innovation and application of intelligent parking technology, parking spaces can be booked in the system in advance through mobile phone, which will greatly reduce the time for drivers to cruise and search for parking spaces. Targeted at the serious waste of parking resources, traffic congestion caused by too intensive parking demand in time and space, a parking allocation model considering the ability of dynamic and static traffic conversion is established with the goal of minimizing the total travel time of the travelers. Based on the dynamic traffic distribution model, considering the constraints of capacity of the road link, parking lot entrance and the number of the parking spaces in parking lot, the dynamic and static traffic is combined by considering the parking lot connection section as a conversion link to be added into the traffic network. And the solution method based on particle swarm optimization is proposed. Experimental results on a case (Beijing Chaoyang Joy City and surrounding parking lots) show that our parking allocation model works satisfactorily by effectively reducing the travel time of travelers and increase customer arrivals in shopping centers. From the point of view of traffic managers, the model can make the parking occupancy of all parking lots more balanced, which indicates that the model can help to better coordinate the available parking resources. In summary, the model proposed in this paper can not only divert the flow beyond the capacity of the road facilities at the connection of the parking lot, but also balance the utilization rate of the surrounding parking resources and reduce the dynamic traffic pressure, it is a proper way to develop the sustainable transportation.

A Comprehensive Study on Intelligent Transportation Systems

2018 ◽  
Vol 4 (10) ◽  
pp. 10
Author(s):  
Ankur Mishra ◽  
Aayushi Priya
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Transportation Systems ◽  
Environmental Conservation ◽  
Integrated System ◽  
Transport Systems ◽  
Transport Sector ◽  
Intelligent Transport System ◽  
Intelligent Transport ◽  
Transportation Sector

Transportation or transport sector is a legal source to take or carry things from one place to another. With the passage of time, transportation faces many issues like high accidents rate, traffic congestion, traffic & carbon emissions air pollution, etc. In some cases, transportation sector faced alleviating the brutality of crash related injuries in accident. Due to such complexity, researchers integrate virtual technologies with transportation which known as Intelligent Transport System. Intelligent Transport Systems (ITS) provide transport solutions by utilizing state-of-the-art information and telecommunications technologies. It is an integrated system of people, roads and vehicles, designed to significantly contribute to improve road safety, efficiency and comfort, as well as environmental conservation through realization of smoother traffic by relieving traffic congestion. This paper aims to elucidate various aspects of ITS - it's need, the various user applications, technologies utilized and concludes by emphasizing the case study of IBM ITS.

Recent advances on urban taxi sharing systems with the path arrival probability

2020 ◽  
Vol 13 ◽  
Author(s):  
Dui Hongyan ◽  
Zhang Chi
Keyword(s):  
Failure Probability ◽  
Traffic Congestion ◽  
Optimal Strategy ◽  
Time Windows ◽  
Optimal Path ◽  
Route Planning ◽  
Driving Time ◽  
Load Rate ◽  
Travel Efficiency ◽  
Arrival Probability

Background : Taxi sharing is an emerging transportation arrangement that helps improve the passengers’ travel efficiency and reduce costs. This study proposes an urban taxi sharing system. Methods: Considering each side congestion of the transport network, their corresponding reliability and failure probability are analyzed. Under the constraints of the number of passengers and their own time windows, the analysis is performed on passengers whose optimal path is inclusive. Results: According to the optimal strategy, the different passengers can be arranged into the same taxi to realize the taxi sharing. Then the shared taxi route can be optimized. Conclusion: Due to the reasonable vehicle route planning and passenger combination, these can effectively alleviate the traffic congestion, save the driving time, reduce the taxi no-load rate, and save the driving distance. At last, a numerical example is used to demonstrate the proposed method.

Proposal and implementation of parking guidance method

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 12-14
Author(s):  
Akira Kawai ◽  
Masahiro Kenmotsu
Keyword(s):  
Traffic Congestion ◽  
Positional Information ◽  
Associate Professor ◽  
Parking Lots ◽  
Gps Technology ◽  
The World ◽  
Car Park ◽  
Free Spaces ◽  
Interest In Research ◽  
Gain Access

Traffic congestion in parking lots is a common phenomenon across the world and larger commercial facilities with multiple parking areas may be particularly affected as many users struggle to gain access to sought-after parking spots close to their destinations. These popular zones often see traffic jams forming as many vehicles arrive within these regions, while less popular areas may remain free from congestion. This creates a very uneven distribution of traffic, with motorists in popular areas becoming trapped and unable to leave bottleneck regions. As a result, the car park management industry has taken an interest in research into parking guidance. Parking guidance has been developed to help improve efficiencies in car parks, guiding drivers to specific spaces using GPS technology to highlight free spaces near their location detailing the most efficient way to get to that spot. Associate Professor Akira Kawai, who is based at Shiga University in Japan, has been working on a KAKEN project that seeks to leverage real-time positional information to help guide drivers to free spaces within parking lots.

scholarly journals A Case Study of a Large Unstable Mass Stabilization: “El Portalet” Pass at the Central Spanish Pyrenees

2021 ◽  
Vol 11 (16) ◽  
pp. 7176
Author(s):  
Guillermo Cobos ◽  
Miguel Ángel Eguibar ◽  
Francisco Javier Torrijo ◽  
Julio Garzón-Roca
Keyword(s):  
Water Table ◽  
Critical Factor ◽  
Slope Stabilization ◽  
Survey Techniques ◽  
Geotechnical Investigations ◽  
Spanish Pyrenees ◽  
Parking Lot ◽  
Unstable Slope ◽  
Total Stability

This case study presents the engineering approach conducted for stabilizing a landslide that occurred at “El Portalet” Pass in the Central Spanish Pyrenees activated due to the construction of a parking lot. Unlike common slope stabilization cases, measures projected here were aimed at slowing and controlling the landslide, and not completely stopping the movement. This decision was taken due to the slow movement of the landslide and the large unstable mass involved. The degree of success of the stabilization measures was assessed by stability analyses and data obtained from different geotechnical investigations and satellite survey techniques such as GB-SAR and DinSAR conducted by different authors in the area under study. The water table was found to be a critical factor in the landslide’s stability, and the tendency of the unstable slope for null movement (total stability) was related to the water table lowering process, which needs more than 10 years to occur due to regional and climatic issues. Results showed a good performance of the stabilization measures to control the landslide, demonstrating the effectiveness of the approach followed, and which became an example of a good response to the classical engineering duality cost–safety.

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