scholarly journals Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements

2020 ◽  
Vol 12 (19) ◽  
pp. 8145
Author(s):  
Maximilian Braun ◽  
Jan Kunkler ◽  
Florian Kellner
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Network Performance ◽  
Service Providers ◽  
Traffic Information ◽  
Performance Measurements ◽  
Real World Data ◽  
Network Characteristics ◽  
Navigation Service ◽  
German Cities

Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.

scholarly journals ROUTE PLANNING METHODOLOGY OF AN ADVANCED TRAVELLER INFORMATION SYSTEM IN VILNIUS CITY

Transport ◽  
2010 ◽  
Vol 25 (2) ◽  
pp. 171-177 ◽  
Author(s):  
Marius Jakimavičius ◽  
Marija Burinskienė
Keyword(s):  
Information System ◽  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Service Providers ◽  
Information Service ◽  
Route Planning ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Driving Time ◽  
Planning Methodology

As a subsystem of an Intelligent Transportation System (ITS), an Advanced Traveller Information System (ATIS) disseminates real‐time traffic information to travellers. To help them with making better decisions on choosing their routes, a strong need to predict traffic congestion and to disseminate the predicted congestion information relating to travellers can be seen. This paper describes a methodology used by drivers for calculating an optimal driven route in Vilnius. The paper discusses how ATIS systems will likely evolve the experience of Information Service Providers (ISP) and optimal route planning calculations. A few methods of route planning have been taken into account. The paper presents the following types of route calculation: 1) the shortest route; 2) the quickest route; 3) the quickest forecasted route according to historical traffic information. Also, the paper deals with the architecture of the WEB based information system for drivers in Vilnius and analyzes data on traffic workflow. Furthermore, a comprehensive route planning procedure that forecasts data on driving time considering historical traffic is followed.

scholarly journals Impact on Network Performance of Probe Vehicle Data Usage: An Experimental Design for Simulation Assessment

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Lídia Montero ◽  
Maria Paz Linares ◽  
Josep Casanovas ◽  
Esteve Codina ◽  
Gonzalo Recio ◽  
...  
Keyword(s):  
Network Performance ◽  
Point Of View ◽  
Traffic Information ◽  
Route Guidance ◽  
Microscopic Simulation ◽  
Model Driven ◽  
Probe Vehicles ◽  
Real Time Traffic ◽  
Vehicle Data ◽  
Navigation Service

Probe-based technologies are proliferating as a means of inferring traffic states. Technological companies are interested in traffic data for computing the best routes in a traffic-aware manner and they also provide real-time traffic information with certain temporal accuracy. This paper analyses and evaluates how data provided by a fleet of probe cars can be used to develop a navigation service and how the penetration rate of this service affects a set of city-scale KPIs (Key Performance Indicators) and driver KPIs. The case study adopts a model-driven approach in which microscopic simulation emulates real-size fleets of probe vehicles that provide positions and speed data. What is noteworthy about the modelling behaviour is that drivers are segmented according to their knowledge of network conditions for selected trips: experts, regular drivers, and tourists. The paper presents and discusses the modelling approach and the results obtained from an experimental Barcelona CBD model designed to evaluate the penetration rates of probe vehicles and route guidance. An analysis of the simulation experiments reveals remarkable links among city-scale KPIs, which—from a multivariate point of view—is a novelty. A simulation-based framework for results analysis and visualization is also introduced in order to simplify the simulation results analysis and easily visualize OD paths for driver segments.

Traffic Parameters Prediction Method Based on Rolling Time Series

2013 ◽  
Vol 671-674 ◽  
pp. 2946-2950
Author(s):  
Gui Yan Jiang ◽  
Cui Liu Kong
Keyword(s):  
Time Series ◽  
Traffic Congestion ◽  
Road Network ◽  
Prediction Method ◽  
Traffic Information ◽  
Series Method ◽  
Management Measures ◽  
Time Series Method ◽  
Traditional Approaches ◽  
Better Than

The technologies of traffic parameters prediction provide future traffic information so that management measures for traffic congestion can be made timely and accurately based on the retrieved information. According to the shortcomings of traditional methods for predicting traffic parameters, a rolling time series method is proposed through improving the traditional time series methods. To test the performance of our proposed approach, the rolling time series method is compared with the traditional time series methods using measured traffic flow based on a part road network of a large urban area in China. The results show that the prediction effects by the rolling time series method developed in this study are better than traditional approaches.

scholarly journals A Data-Driven Control Strategy for Urban Express Ramp

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Liyan Zhang ◽  
Min Zhang ◽  
Jian Ma ◽  
Jing Ge
Keyword(s):  
Control Strategy ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Cooperative Control ◽  
Road Network ◽  
Urban Traffic ◽  
Data Driven ◽  
Traffic Information ◽  
Network Environment ◽  
Intelligent Network

Expressway, as the main artery of urban traffic, realizes the smooth operation of the whole urban road network through reasonably balancing the traffic flow. However, due to the lack of reasonable and effective traffic control, the safety and congestion of expressways are becoming more and more serious. The development of intelligent network technology provides a new idea to solve the control problem of expressways. In this paper, a data-driven ramp control model of urban expressway is constructed. The interaction of traffic information is realized through intelligent network connection technology. The cooperative control strategy of VSL and RM is adopted. The mutual feedback of VSL and RM is realized based on the improved METANET model. The simulation experiment based on VISSIM secondary development shows that the collaborative control strategy under the intelligent network environment could make the vehicle travel time reduced by 20.59% and the speed difference between adjacent sections of the expressway mainline by 34.07%, which realized the coordinated control of the mainline and the on-ramp under the intelligent network environment, alleviate the expressway traffic congestion, reduce the traffic pressure, and improve the efficiency of the road network.

Got the Results, Now What Do You Do?

2012 ◽  
Vol 2 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Michaela Heese
Keyword(s):  
Safety Culture ◽  
Success Factors ◽  
Service Providers ◽  
Transformation Process ◽  
Driving Safety ◽  
Critical Success ◽  
Culture Transformation ◽  
Survey Results ◽  
Air Navigation Services ◽  
Navigation Service

Members of the Civil Air Navigation Services Organisation have committed themselves to measure and improve safety culture within their organizations by 2013 ( CANSO, 2010 ). This paper attempts to offer support to air navigation service providers that have already implemented a standardized safety culture survey approach, in the process of transforming their safety culture based on existing survey results. First, an overview of the state of the art with respect to safety culture is presented. Then the application of the CANSO safety culture model from theory into practice is demonstrated based on four selected case studies. Finally, a summary of practical examples for driving safety culture change is provided, and critical success factors supporting the safety culture transformation process are discussed.

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.

scholarly journals Large-Scale Road Network Congestion Pattern Analysis and Prediction Using Deep Convolutional Autoencoder

2021 ◽  
Vol 13 (9) ◽  
pp. 5108
Author(s):  
Navin Ranjan ◽  
Sovit Bhandari ◽  
Pervez Khan ◽  
Youn-Sik Hong ◽  
Hoon Kim
Keyword(s):  
Traffic Congestion ◽  
Network Architecture ◽  
Road Network ◽  
Large Scale ◽  
Pattern Analysis ◽  
Image Data ◽  
Urban Life ◽  
Prediction Algorithm ◽  
Rapid Urbanization ◽  
Convolutional Autoencoder

The transportation system, especially the road network, is the backbone of any modern economy. However, with rapid urbanization, the congestion level has surged drastically, causing a direct effect on the quality of urban life, the environment, and the economy. In this paper, we propose (i) an inexpensive and efficient Traffic Congestion Pattern Analysis algorithm based on Image Processing, which identifies the group of roads in a network that suffers from reoccurring congestion; (ii) deep neural network architecture, formed from Convolutional Autoencoder, which learns both spatial and temporal relationships from the sequence of image data to predict the city-wide grid congestion index. Our experiment shows that both algorithms are efficient because the pattern analysis is based on the basic operations of arithmetic, whereas the prediction algorithm outperforms two other deep neural networks (Convolutional Recurrent Autoencoder and ConvLSTM) in terms of large-scale traffic network prediction performance. A case study was conducted on the dataset from Seoul city.

Empirical Assessment and Modeling of Traffic-induced Air Pollution

2021 ◽  
pp. 036119812110237
Author(s):  
Zhongyang Lu ◽  
Andy H. F. Chow ◽  
Jacky Leung ◽  
Haydn Kwok ◽  
Sammy Cheung
Keyword(s):  
Air Pollution ◽  
Hong Kong ◽  
Road Network ◽  
Historical Data ◽  
Flow Speed ◽  
Traffic Flows ◽  
Real World Data ◽  
Empirical Assessment ◽  
Air Quality Monitoring Stations ◽  
Transport Management

Congestion and traffic-induced air pollution are associated with population growth and economic development. Compared with congestion, there are relatively few studies on modeling and assessment of traffic-induced pollution. This paper presents an empirical assessment and analysis of traffic-induced air pollution with real-world data collected from the Hong Kong Strategic Road Network. The study employed historical data of traffic flows, speeds, and emission of air pollutants collated by the Hong Kong Transport Department and Environmental Protection Department. This paper first reveals the correlation between traffic flows, speeds, and corresponding induced pollutants including nitrogen oxides (NO2, NOX) and carbon monoxide (CO). To gain further statistical insight, a regression analysis was conducted on the flow–speed–emission relationship at three air quality monitoring stations, which revealed the significance of various factors on this relationship. This study contributes to green transport management and urban sustainability.

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