Development of Methods and Tools for Managing Traffic Congestion in Freeway Corridors

2006 ◽  
Author(s):  
W. Recker ◽  
H.M. Zhang ◽  
Lianyu Chu ◽  
A. Chen ◽  
M. McNally
Keyword(s):  
Traffic Congestion ◽  
Freeway Corridors

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.

Assessing the Impact of Automated and Connected Automated Vehicles on Virginia Freeways

2021 ◽  
pp. 036119812110049
Author(s):  
Bumsik Kim ◽  
Kevin P. Heaslip ◽  
Mirla Abi Aad ◽  
Antonio Fuentes ◽  
Noah Goodall
Keyword(s):  
Traffic Congestion ◽  
Poor Performance ◽  
Automated Vehicles ◽  
Traffic Demand ◽  
Average Speed ◽  
Road Capacity ◽  
Freeway Corridors ◽  
Behavior Models ◽  
The Impact ◽  
Connected Automated Vehicles

This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.

Impact of the urban construction solutions on the safety population

2020 ◽  
Vol 17 (2) ◽  
pp. 66-73
Author(s):  
R. D. Oktyabrskiy
Keyword(s):  
Traffic Congestion ◽  
Urban Population ◽  
Road Network ◽  
Residential Development ◽  
Emergency Situations ◽  
Urban Construction ◽  
Safety Population ◽  
Peace And War ◽  
The City

The article is devoted to the justification of the need to reduce the population density in the residential development of cities. The analysis of vulnerability of the urban population from threats of emergency situations of peace and war time, and also an assessment of provision of the city by a road network is given. Proposals have been formulated to reduce the vulnerability of the urban population in the long term and to eliminate traffic congestion and congestion — jams.

Analysis of Traffic Congestion by Considering Merging on Entry Lines in Transportation System

2011 ◽  
Vol 131 (8) ◽  
pp. 1059-1067
Author(s):  
Takahiro Hoshino ◽  
Kazuhiro Tsuboi ◽  
Yoshio Hamamatsu
Keyword(s):  
Traffic Congestion ◽  
Transportation System

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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.

Determination of Optimal Public Transportation Routes Using Firefly and Tabu Search Algorithms

2020 ◽  
Vol 4 (5) ◽  
pp. 884-891
Author(s):  
Salwa Salsabila Mansur ◽  
Sri Widowati ◽  
Mahmud Imrona
Keyword(s):  
Tabu Search ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Search Algorithm ◽  
Urban Transportation ◽  
The Public ◽  
Comparison Results ◽  
Congestion Problems ◽  
Transportation Routes

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

A Selection of Bandung City Travel Route Using The FLOYD-WARSHALL Algorithm

2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Rapid Development ◽  
Route Selection ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
A Value ◽  
Distance Data ◽  
Simple Additive Weighting ◽  
The City ◽  
Selection Of

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.

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