All-Links-Based E-Hailing Pricing and Surcharge Mechanism for Transportation System Performance Improvement

2019 ◽  
Vol 2673 (12) ◽  
pp. 103-114 ◽  
Author(s):  
Qixing Wang ◽  
Nicholas E. Lownes
Keyword(s):  
System Performance ◽  
Large Scale ◽  
Travel Demand ◽  
Inverse Function ◽  
Optimal Level ◽  
Transportation System ◽  
Difficult Problem ◽  
Service Demand ◽  
Demand Changes ◽  
Demand Patterns

E-hailing services, in which riders request rides from their mobile devices, have rapidly developed into a viable transportation alternative for many travelers. This technology has changed the set of choices for travelers and has shifted travel patterns, most significantly away from traditional taxi services. However, several issues have arisen during this expansion. In this paper, an economical approach is proposed which considers both the effects of the travelers’ route choices and travel demand patterns. In this approach, we assume that all links can be surcharged for those using e-hailing services, and a heuristic process is applied to address this computationally difficult problem. A cost inverse function is introduced to update the demand changes along paths with different rates of e-hailing surcharges. The method is demonstrated on the mid-size network of Sioux Falls, South Dakota, and on the large-scale city network of Anaheim, California. Results indicate that an optimal price could efficiently reduce e-hailing service demand during congestion hours and improve the transportation system performance to system optimal level.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

Demographic Characterization of Anonymous Trace Travel Data

2015 ◽  
Vol 2526 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Joshua Auld ◽  
Abolfazl (Kouros) Mohammadian ◽  
Marcelo Simas Oliveira ◽  
Jean Wolf ◽  
William Bachman
Keyword(s):  
Test Data ◽  
Large Scale ◽  
Travel Demand ◽  
Null Model ◽  
Demographic Characteristics ◽  
Travel Pattern ◽  
Data Set ◽  
Trace Data ◽  
Demographic Models ◽  
Pattern Information

Research was undertaken to determine whether demographic characteristics of individual travelers could be derived from travel pattern information when no information about the individual was available. This question is relevant in the context of anonymously collected travel information, such as cell phone traces, when used for travel demand modeling. Determining the demographics of a traveler from such data could partially obviate the need for large-scale collection of travel survey data, depending on the purpose for which the data were to be used. This research complements methodologies used to identify activity stops, purposes, and mode types from raw trace data and presumes that such methods exist and are available. The paper documents the development of procedures for taking raw activity streams estimated from GPS trace data and converting these into activity travel pattern characteristics that are then combined with basic land use information and used to estimate various models of demographic characteristics. The work status, education level, age, and license possession of individuals and the presence of children in their households were all estimated successfully with substantial increases in performance versus null model expectations for both training and test data sets. The gender, household size, and number of vehicles proved more difficult to estimate, and performance was lower on the test data set; these aspects indicate overfitting in these models. Overall, the demographic models appear to have potential for characterizing anonymous data streams, which could extend the usability and applicability of such data sources to the travel demand context.

Disaster impacts in a port-city; learning from Beirut's  Port explosion

2021 ◽  
Author(s):  
Steluta topalov
Keyword(s):  
Large Scale ◽  
Focal Point ◽  
Transportation System ◽  
The Philippines ◽  
Lessons Learned ◽  
Social Dimension ◽  
Global Network ◽  
Port Cities ◽  
Residential Units ◽  
The Impact

<p>On 4 august 2020, one of the biggest non-nuclear explosions the world has seen in recent times took place in the Port of Beirut. Caused by the detonation of 2,750 tons of ammonium nitrate, inadequate stored in a warehouse in the port, the blast destroyed much of the city’s port and the surrounding infrastructure and severly  damaged the dense residential and commercial areas within 5 km of the explosion site. The impact of the explosion, which registered as a 3.3 magnitude earthquake according to the U.S. Geological Survey, was felt as far away as the island of Cyprus.</p><p>Athough the event was an technological hazard, the impact of the explosion is similar to a standardised natural disaster.</p><p>According to UNDP, a total of 200 000 residential units were affected with an estimated of 40 000 buildings damaged; 200 people lost their lives, around 6 000 individuals were injuried and around 300 000 people were displaced.</p><p>Such figure are comparable to other large-scale disasters such as Cyclone Vayu in India, which occured in June 2019 or the displacement caused by the Typhoon Vongfong, in the Philippines.</p><p>The frequent increase of the natural disasters  puts pressure on the critical infrastructure of the cities. The disruption of the transportation system,  which is vital for the sustainable daily operations, are having a big impact on the economical, enviromental and social dimension of a city system. Among the various types of transportation system, ports are a focal point because of its strategic role for the economic growth of cities,regions and  global network. In addition, they are nodal points for the social and economical activity of the inhabitants.</p><p>Although the ports have played a key role in the development of their host cities, they are also vulnerable to a broad range of risks and threats because of a particular spatial character: the location at the intersection of land and sea.  </p><p>The study of the Beirut’s Port explosion examines the impact of port failures on the host urban enviroment and the relationship between hazards, vulnerability and the impact. The vulnerability of the port to disasters results  to the vulnerability of its host city. A context –based understanding  of the impact of the disaster and the elements at risk is essential to identify appropriate risk management strategies. The location of the port within the urban environment, in densely populated area, as in case of Beirut are some of the characteristics of the port cities that can magnify the impact of disasters to which they are prone.  The study will focus on a collection of data that records the impact and allows visualisation of the complex patterns of the disaster risk reduction.</p><p>The impact caused by the Beirut’s port explosion reminds us about the important role of the ports in their host cities and how fundamental is to identify the port’s infrastructure  exposure to hazards and risks.  Lessons learned from such event may be useful to reduce disaster risks in the port cities.</p>

scholarly journals THE CONSTRUCTION OF A COMPREHENSIVE EVALUATION SYSTEM OF REGIONAL PUBLIC SPORTS SERVICE SUPPLY IN CHINA BASED ON RECIPIENT SATISFACTION INDEX MODEL

2021 ◽  
Vol 27 (spe) ◽  
pp. 56-58
Author(s):  
Pei Jiang
Keyword(s):  
Evaluation System ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Service Level ◽  
Difficult Problem ◽  
Performance Evaluation System ◽  
Satisfaction Index ◽  
Index Model ◽  
Comprehensive Evaluation System ◽  
Scale Design

ABSTRACT The comprehensive performance evaluation system of public sports service is an important part of public sports service system in China. How to objectively and comprehensively evaluate the present situation of public sports service performance in our country has always been a difficult problem in the development of public sports service. Based on the five principles of constructing the recipient satisfaction index, the PCSSI model of the comprehensive evaluation system of public sports service supply was constructed using scale design. Large-scale stadiums in seven districts of Shenyang were selected for investigation. The recipient satisfaction index model was established to compare the satisfaction index of the 7 regions, and analyze the influencing factors of the satisfaction index of public sports service supply, and put forward some suggestions for improving the service level of large stadiums and gymnasiums in Shenyang. Practice has proved that the application of the PCSSI model has a positive effect on improving the performance level of public sports service supply in China.

scholarly journals Applying Machine Learning for Improving Performance Classification on Driving Behavior

2021 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
Ahmad Iwan Fadli ◽  
Selo Sulistyo ◽  
Sigit Wibowo
Keyword(s):  
Machine Learning ◽  
Traffic Accident ◽  
Large Scale ◽  
Detection System ◽  
Difficult Problem ◽  
Sensor Data ◽  
Driving Safety ◽  
Support Vector ◽  
Classification Methods ◽  
Machine Learning Classification

Traffic accident is a very difficult problem to handle on a large scale in a country. Indonesia is one of the most populated, developing countries that use vehicles for daily activities as its main transportation.  It is also the country with the largest number of car users in Southeast Asia, so driving safety needs to be considered. Using machine learning classification method to determine whether a driver is driving safely or not can help reduce the risk of driving accidents. We created a detection system to classify whether the driver is driving safely or unsafely using trip sensor data, which include Gyroscope, Acceleration, and GPS. The classification methods used in this study are Random Forest (RF) classification algorithm, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) by improving data preprocessing using feature extraction and oversampling methods. This study shows that RF has the best performance with 98% accuracy, 98% precision, and 97% sensitivity using the proposed preprocessing stages compared to SVM or MLP.

scholarly journals Adaptive Integral Second-Order Sliding Mode Control Design for Load Frequency Control of Large-Scale Power System with Communication Delays

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Anh-Tuan Tran ◽  
Bui Le Ngoc Minh ◽  
Phong Thanh Tran ◽  
Van Van Huynh ◽  
Van-Duc Phan ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Power Systems ◽  
Power System ◽  
System Performance ◽  
Large Scale ◽  
Sliding Mode ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Communication Delays ◽  
Second Order Sliding Mode

Nowadays, the power systems are getting more and more complicated because of the delays introduced by the communication networks. The existence of the delays usually leads to the degradation and/or instability of power system performance. On account of this point, the traditional load frequency control (LFC) approach for power system sketches a destabilizing impact and an unacceptable system performance. Therefore, this paper proposes a new LFC based on adaptive integral second-order sliding mode control (AISOSMC) approach for the large-scale power system with communication delays (LSPSwCD). First, a new linear matrix inequality is derived to ensure the stability of whole power systems using Lyapunov stability theory. Second, an AISOSMC law is designed to ensure the finite time reachability of the system states. To the best of our knowledge, this is the first time the AISOSMC is designed for LFC of the LSPSwCD. In addition, the report of testing results presents that the suggested LFC based on AISOSMC can not only decrease effectively the frequency variation but also make successfully less in mount of power oscillation/fluctuation in tie-line exchange.

scholarly journals Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhi-guang Jiang ◽  
Xiao-tian Shi
Keyword(s):  
Video Analysis ◽  
Management System ◽  
Large Scale ◽  
Data Communication ◽  
Transportation System ◽  
Extraction Technology ◽  
Transportation Management ◽  
Key Frame Extraction ◽  
Original Algorithm ◽  
Key Frame

The intelligent transportation system under the big data environment is the development direction of the future transportation system. It effectively integrates advanced information technology, data communication transmission technology, electronic sensing technology, control technology, and computer technology and applies them to the entire ground transportation management system to establish a real-time, accurate, and efficient comprehensive transportation management system that works on a large scale and in all directions. Intelligent video analysis is an important part of smart transportation. In order to improve the accuracy and time efficiency of video retrieval schemes and recognition schemes, this article firstly proposes a segmentation and key frame extraction method for video behavior recognition, using a multi-time scale dual-stream network to extract video features, improving the efficiency and efficiency of video behavior detection. On this basis, an improved algorithm for vehicle detection based on Faster R-CNN is proposed, and the Faster R-CNN network feature extraction layer is improved by using the principle of residual network, and a hole convolution is added to the network to filter out the redundant features of high-resolution video images to improve the problem of vehicle missed detection in the original algorithm. The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. The detection rate is satisfactory.

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