scholarly journals Network Effects, Congestion Externalities, and Air Traffic Delays: Or Why Not All Delays Are Evil

2003 ◽  
Vol 93 (4) ◽  
pp. 1194-1215 ◽  
Author(s):  
Christopher Mayer ◽  
Todd Sinai
Keyword(s):  
Travel Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Network Effects ◽  
Air Traffic ◽  
Small Impact ◽  
Traffic Delays ◽  
Two Factors ◽  
Short Time ◽  
Congestion Externalities

We examine two factors that explain air traffic congestion: network benefits due to hubbing and congestion externalities. While both factors impact congestion, we find that the hubbing effect dominates empirically. Hub carriers incur most of the additional travel time from hubbing, primarily because they cluster their flights in short time spans to provide passengers as many potential connections as possible with a minimum of waiting time. Non-hub flights at the same hub airports operate with minimal additional travel time. These results suggest that an optimal congestion tax might have a relatively small impact on flight patterns at hub airports.

scholarly journals Bus Travel Time Reliability Incorporating Stop Waiting Time and In-vehicle Travel Time with AVL Data

2022 ◽  
Author(s):  
Zixu Zhuang ◽  
Zhanhong Cheng ◽  
Jia Yao ◽  
Jian Wang ◽  
Shi An
Keyword(s):  
Travel Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Influence Factors ◽  
Future Research ◽  
Travel Time Reliability ◽  
Independent Events ◽  
Harbin City ◽  
Bus Travel Time ◽  
Vehicle Travel Time

Abstract Improving bus operation quality can attract more commuters to use bus transit, and therefore reduces the share of car and alleviates traffic congestion. One important index of bus operation quality is the bus travel time reliability, which in this paper is defined to be the probability when the sum of bus stop waiting time and in-vehicle travel time is less than a certain threshold. We formulate the bus travel time reliability by the convolution of independent events’ probabilities, and elaborate the calculation method using Automatic Vehicle Location (AVL) data. Next, the No.63 Bus Line in Harbin City is used to test the applicability of the proposed method, and analyze the influence factors of the bus travel time reliability. The numerical results show that factors such as weather, workday, departure time, travel distance, and the distance from the boarding stop to the bus departure station will significantly affect the travel time reliability. At last, some general conclusions and future research are summarized.

scholarly journals Speed Adaptation in Urban Road Network Management

2016 ◽  
Vol 17 (2) ◽  
pp. 111-121 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Moving Average ◽  
Road Networks ◽  
Satellite System ◽  
Global Navigation Satellite ◽  
Short Time ◽  
Gnss Data

Abstract Various forecasting schemes have been proposed to manage traffic data, which is collected by videos cameras, sensors, and mobile phone services. However, these are not sufficient for collecting data because of their limited coverage and high costs for installation and maintenance. To overcome the limitations of these tools, we introduce a hybrid scheme based on intelligent transportation system (ITS) and global navigation satellite system (GNSS). Applying the GNSS to calculate travel time has proven efficient in terms of accuracy. In this case, GNSS data is managed to reduce traffic congestion and road accidents. This paper introduces a short-time forecasting model based on real-time travel time for urban heterogeneous road networks. Travel time forecasting has been achieved by predicting travel speeds using an optimized exponential moving Average (EMA) model. Furthermore for speed adaptation in heterogeneous road networks, it is necessary to introduce asuitable control strategy for longitude, based on the GNSS. GNSS products provide worldwide and real-time services using precise timing information and, positioning technologies.

scholarly journals Values of Travel Time for Recreational Trips under Different Behavioural Rules

2021 ◽  
Vol 13 (12) ◽  
pp. 6831
Author(s):  
Rosa Marina González ◽  
Concepción Román ◽  
Ángel Simón Marrero
Keyword(s):  
Travel Time ◽  
National Parks ◽  
Traffic Congestion ◽  
National Park ◽  
Revealed Preference ◽  
Discrete Choice Models ◽  
Model Specification ◽  
Regret Minimization ◽  
Random Regret Minimization

In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.

scholarly journals Measuring Recurrent and Nonrecurrent Traffic Congestion

2003 ◽  
Vol 1856 (1) ◽  
pp. 118-124 ◽  
Author(s):  
Alexander Skabardonis ◽  
Pravin Varaiya ◽  
Karl F. Petty
Keyword(s):  
Los Angeles ◽  
Travel Time ◽  
San Francisco ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Variability ◽  
Loop Detectors ◽  
Bay Area ◽  
Freeway Corridors ◽  
Travel Time Variability

A methodology and its application to measure total, recurrent, and nonrecurrent (incident related) delay on urban freeways are described. The methodology used data from loop detectors and calculated the average and the probability distribution of delays. Application of the methodology to two real-life freeway corridors in Los Angeles, California, and one in the San Francisco, California, Bay Area, indicated that reliable measurement of congestion also should provide measures of uncertainty in congestion. In the three applications, incident-related delay was found to be 13% to 30% of the total congestion delay during peak periods. The methodology also quantified the congestion impacts on travel time and travel time variability.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals Minimizing Traffic Congestion Through Continuous-Time Route Reservations With Travel Time Predictions

2019 ◽  
Vol 4 (1) ◽  
pp. 141-153 ◽  
Author(s):  
Charalambos Menelaou ◽  
Stelios Timotheou ◽  
Panayiotis Kolios ◽  
Christos G. Panayiotou ◽  
Marios M. Polycarpou
Keyword(s):  
Travel Time ◽  
Continuous Time ◽  
Traffic Congestion

scholarly journals Estimates of Economic Cost of Congestion Travel Time Delay Between Onne-Seaport and Eleme-Junction Traffic Corridor

2020 ◽  
Vol 11 (2) ◽  
pp. 33-43
Author(s):  
Theophilus C. Nwokedi ◽  
Lazarus I. Okoroji ◽  
Ifiok Okonko ◽  
Obed C. Ndikom
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Oil And Gas ◽  
Economic Cost ◽  
Oil And Gas Industry ◽  
Research Approach ◽  
Traffic Corridor ◽  
Output Losses

AbstractTravelers along the Onne-seaport to Eleme-junction road corridor in the hub of the oil and gas industry in Port-Harcourt, Nigeria, have continued to experience very serious traffic congestion travel time delays, culminating into loss of man-hours and declining productivity. This study estimated the economic cost of traffic congestion travel time delay along the corridor, with a view to providing economic justification for developing traffic management policies and road infrastructure, to remedy it. A mixed research approach was adopted in which data was sourced through field survey and from secondary sources. The gross output model was used to estimate the output losses occasioned by productive time losses related to traffic congestion. The study established that the average daily traffic congestion travel time delay along the traffic corridor by travelers in trucks, car, bus and taxi modes are 104.17 minutes, 46.60 minutes, 58.5 minutes and 56.4 minutes respectively. The estimated daily aggregate economic cost of output losses associated with traffic congestion time delay on the corridor is 46049809.8 naira (210923.5USD) for all modes. This justifies any investment in traffic congestion remedial strategies along the route.

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