A Real-Time Wireless Route Guidance System for Urban Traffic Management and Its Performance Evaluation

2009 ◽  
Author(s):  
Kai Chen ◽  
Kia Makki ◽  
Niki Pissinou
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Traffic Management ◽  
Urban Traffic ◽  
Guidance System ◽  
Route Guidance

scholarly journals Assessments of Real-Time Communications over TSN Automotive Networks

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 556
Author(s):  
Lucia Lo Bello ◽  
Gaetano Patti ◽  
Giancarlo Vasta
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Communication System ◽  
Traffic Management ◽  
Mac Layer ◽  
Automated Driving ◽  
Real Time Traffic ◽  
Management Scheme ◽  
Event Driven ◽  
Automotive Networks

The IEEE 802.1Q-2018 standard embeds in Ethernet bridges novel features that are very important for automated driving, such as the support for time-driven communications. However, cars move in a world where unpredictable events may occur and determine unforeseen situations. To properly react to such situations, the in-car communication system has to support event-driven transmissions with very low and bounded delays. This work provides the performance evaluation of EDSched, a traffic management scheme for IEEE 802.1Q bridges and end nodes that introduces explicit support for event-driven real-time traffic. EDSched works at the MAC layer and builds upon the mechanisms defined in the IEEE 802.1Q-2018 standard.

MACHINE LEARNING ON CONGESTION ANALYSIS BASED REAL-TIME NAVIGATION SYSTEM

2011 ◽  
Vol 20 (04) ◽  
pp. 753-781
Author(s):  
KAI CHEN ◽  
KIA MAKKI ◽  
NIKI PISSINOU
Keyword(s):  
Machine Learning ◽  
Travel Time ◽  
Real Time ◽  
Navigation System ◽  
Prediction Models ◽  
Urban Traffic ◽  
Route Guidance ◽  
Highway Traffic ◽  
Data Set ◽  
Guidance Systems

In the metropolitan region, most congestion or traffic jams are caused by the uneven distribution of traffic flow that creates bottleneck points where the traffic volume exceeds the road capacity. Additionally, unexpected incidents are the next most probable cause of these bottleneck regions. Moreover, most drivers are driving based on their empirical experience without awareness of real-time traffic situations. This unintelligent traffic behavior can make the congestion problem worse. Prediction based route guidance systems show great improvements in solving the inefficient diversion strategy problem by estimating future travel time when calculating accurate travel time is difficult. However, performances of machine learning based prediction models that are based on the historical data set degrade sharply during a congestion situation. This paper develops a new navigation system for reducing travel time of an individual driver and distributing the flow of urban traffic efficiently in order to reduce the occurrence of congestion. Compared with previous route guidance systems, the results reveal that our system, applying the advanced multi-lane prediction based real-time fastest path (AMPRFP) algorithm, can significantly reduce the travel time especially when drivers travel in a complex route environment and face frequent congestion problems. Unlike the previous system,1 it can be applied either for single lane or multi-lane urban traffic networks where the reason for congestion is significantly complex. We also demonstrate the advantages of this system and verify the results using real highway traffic data and a synthetic experiment.

Parking Navigation System Based on the Double Signal Double Display Intersection Vehicle Terminal and Automobile Internal Information

2014 ◽  
Vol 536-537 ◽  
pp. 803-808
Author(s):  
Jian Zhong Xi ◽  
Cheng Chun Han
Keyword(s):  
Real Time ◽  
Effective Means ◽  
Time Instant ◽  
Urban Traffic ◽  
Guidance System ◽  
The Real ◽  
Cross Presentation ◽  
Intelligent Terminal ◽  
Internal Information ◽  
Vehicle Terminal

In view of more and more complicate driving and parking problems in urban traffic, the parking guidance system are proposed based on a double signal double display intersection vehicle terminal. The system is based on the information interaction between intelligent terminal, vehicle terminal and vehicle of internet, and to introduce the space maze module and automobile internal information, by simulation maze module planning the different target route and its navigation through the intelligent terminal screen, at the same time instant maze module choice and determine the real-time path navigation through the on-board navigator screen, and to improve the accuracy of target navigation. The system will be the target route and real-time route through their channel respectively on the intelligent terminal and vehicle navigation cross presentation, realize the whole process of target parking navigation, or real-time navigation guidance section step by step according to the real-time parking lots, and in order to improve the parking navigation accuracy to provide an effective means of technology.

Real-time travel time predictor for route guidance consistent with driver behavior

2012 ◽  
Vol 39 (10) ◽  
pp. 1113-1124 ◽  
Author(s):  
Tian-dong Xu ◽  
Yuan Hao ◽  
Zhong-ren Peng ◽  
Li-jun Sun
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Time Estimation ◽  
Field Testing ◽  
Pilot Project ◽  
Time Travel ◽  
Guidance System ◽  
Route Guidance ◽  
Travel Time Prediction ◽  
Traffic Conditions

Providing reliable real-time travel time information is a critical challenge to all existing traffic routing systems. This study develops a new model for estimating and predicting real-time traffic conditions and travel times for variable message signs-based route guidance system. The proposed model is based on real-time limited detected traffic data, stochastic nonlinear macroscopic traffic flow model, and adaptive Kalman filtering theory. The method has the following main features: (1) real-time estimation and prediction of traffic conditions on a network level using limited traffic detectors, (2) travel time prediction in free flow and congested flow, and (3) prediction of drivers’ en-route diversion behavior. Field testing is conducted based on the Route Guidance Pilot Project sponsored by the National Science and Technology Ministry of China. The achieved testing results are satisfactory and have potential use for future works and field applications.

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