Study on Cooperation between Traffic Control and Route Guidance Based on Real-time Speed

Author(s):  
Cao Jie ◽  
Wang Chuan
2020 ◽  
Vol 12 (2) ◽  
pp. 726 ◽  
Author(s):  
Stefano de Luca ◽  
Roberta Di Pace ◽  
Silvio Memoli ◽  
Luigi Pariota

This paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis.


2012 ◽  
Vol 22 (2) ◽  
pp. 125-131 ◽  
Author(s):  
Niko Jelušić ◽  
Mario Anžek ◽  
Božidar Ivanković

Advanced automatic traffic control systems and various other ITS (Intelligent Transport Systems) applications and services rely on real-time information from the traffic system. This paper presents the overview and general functions of different information sources which provide real-time information that are used or could be used in ITS. The objective is to formally define the quality of information sources suitable for ITS based on formal models of the traffic system and information sources. The definition of quality encompasses these essential factors: traffic system information that exists or may be requested, user requirements and attributes that describe the information sources. This provides the framework and guidelines for the evaluation of information sources that accounts for relevant factors that influence their selection for specific ITS applications. KEY WORDS: information source, information source quality, Intelligent Transport Systems (ITS), automatic traffic control


2016 ◽  
Vol 2554 (1) ◽  
pp. 101-110 ◽  
Author(s):  
Anastasia Spiliopoulou ◽  
Markos Papageorgiou ◽  
Juan Carlos Herrera ◽  
Juan Carlos Muñoz
Keyword(s):  

Author(s):  
Robert Rice ◽  
Rand Decker ◽  
Newel Jensen ◽  
Ralph Patterson ◽  
Stanford Singer

The growth of winter travel on alpine roads in the western United States, a result of the demand for reliable winter access, has increased the hazard to motorists and highway maintenance personnel from snow avalanches. Configurations are presented for systems that can detect and provide, in real time, warnings to motorists and highway maintainers of roadway avalanches. These warnings include on-site traffic control signing, in-vehicle audio alarms for winter maintenance vehicles, and notifying maintenance facilities or centralized agency dispatchers. These avalanche detection and warning systems can detect an existing avalanche and use the avalanche’s remaining time of descent to initiate on-site alarms. Alternatively, real-time knowledge and notification of the onset of avalanching may be used to proactively manage the evolving hazard over an affected length or corridor of highway. These corridors can be several tens of kilometers in length and may be very remote, low-volume rural highways. As a consequence, these detection and warning systems must be cost-effective alternatives to existing avalanche hazard reduction technology. Results and experiences from the winters of 1997–1998 and 1998–1999 are presented, along with recommendations and criteria for future deployment of these automated natural hazard reduction systems for rural transportation corridors.


2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.


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