Integrating the End User into Infrastructure Systems

2011 ◽  
pp. 63-77 ◽  
Author(s):  
Thomas A. Horan
Keyword(s):  
Intelligent Transportation Systems ◽  
Preliminary Evidence ◽  
Systems Development ◽  
Transportation Systems ◽  
End User ◽  
Market Segments ◽  
Alternative Mode ◽  
Traffic Conditions ◽  
Systems Planning

This chapter analyzes the role of users in enacting Intelligent Transportation Systems (ITS) functions and services. Preliminary evidence from recent demonstrations and market research studies is reviewed with a focus on the role of travelers in producing and using information about traffic conditions and traveler options. The potential for systems development is then considered with specific regard to alternative mode travel, flexible travel, emergency, and commercial services. Based on these findings, several directions and recommendations are made for creating the next generation of ITS systems that enhance user-based elements. Several areas for research and development are recommended, including integrating a wider range of market segments into ITS systems planning, developing a better understanding of how users drive complex systems, and creating new institutional partnerships for delivering innovative services.

scholarly journals An application of Bayesian multilevel model to evaluate variations in stochastic and dynamic transition of traffic conditions

2019 ◽  
Vol 27 (4) ◽  
pp. 235-249 ◽  
Author(s):  
Emmanuel Kidando ◽  
Ren Moses ◽  
Thobias Sando ◽  
Eren Erman Ozguven
Keyword(s):  
Intelligent Transportation Systems ◽  
Regression Models ◽  
Transition Probabilities ◽  
Management Strategies ◽  
Gaussian Mixture ◽  
Transportation Systems ◽  
Hierarchical Regression ◽  
Dynamic Transition ◽  
Traffic Conditions ◽  
Traffic Speed

Abstract This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes (DTTR). In the proposed analysis, hierarchical regression models fitted using Bayesian frameworks were used to calibrate the transition probabilities that describe the DTTR. Datasets of two sites on a freeway facility located in Jacksonville, Florida, were selected for the analysis. The traffic speed thresholds to define traffic regimes were estimated using the Gaussian mixture model (GMM). The GMM revealed that two and three regimes were adequate mixture components for estimating the traffic speed distributions for Site 1 and 2 datasets, respectively. The results of hierarchical regression models show that there is considerable evidence that there are heterogeneity characteristics in the DTTR associated with lateral lane locations. In particular, the hierarchical regressions reveal that the breakdown process is more affected by the variations compared to other evaluated transition processes with the estimated intra-class correlation (ICC) of about 73%. The transition from congestion on-set/dissolution (COD) to the congested regime is estimated with the highest ICC of 49.4% in the three-regime model, and the lowest ICC of 1% was observed on the transition from the congested to COD regime. On the other hand, different days of the week are not found to contribute to the variations (the highest ICC was 1.44%) on the DTTR. These findings can be used in developing effective congestion countermeasures, particularly in the application of intelligent transportation systems, such as dynamic lane-management strategies.

scholarly journals IoT based Real Time Traffic Monitoring System Using M/G/1 Queuing Research

2019 ◽  
Vol 8 (6) ◽  
pp. 3818-3822
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Queuing Theory ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Theory Approach ◽  
The Road ◽  
Traffic Conditions ◽  
Performance Framework ◽  
Real Time Traffic

Vehicular Traffic crowding is paramount worry in urban cities. The use of technologies like Intelligent Transportation systems and Internet of Things can solve the problem of traffic congestion to some extent. The paper analyses the traffic conditions on a particular urban highway using queuing theory approach. It researches on performance framework such as time for waiting and queue length. The results can provide significant analysis to predict traffic congestion during peak hours. A congestion controlling action can be generated to utilize the road capacity fully during peak hours by using these results

KNOWLEDGE BASED TRAFFIC SIGNAL CONTROL MODEL FOR SIGNALIZED INTERSECTION

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 263-267 ◽  
Author(s):  
Henrikas Pranevičius ◽  
Tadas Kraujalis
Keyword(s):  
Intelligent Transportation Systems ◽  
Control Method ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Signalized Intersection ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Traffic Conditions

Intelligent transportation systems have received increasing attention in academy and industry. Being able to handle uncertainties and complexity, expert systems are applied in vast areas of real life including intelligent transportation systems. This paper presents a traffic signal control method based on expert knowledge for an isolated signalized intersection. The proposed method has the adaptive signal timing ability to adjust its signal timing in response to changing traffic conditions. Based on the traffic conditions, the system determines to extend or terminate the current green signal group. Using the information from its traffic detectors of isolated intersection, the proposed controller gives optimal signals to adapt the phase lengths to the traffic conditions. A comparative analysis between proposed control algorithm, fuzzy logic (FLC) and fixed-timed (pre-timed) controllers has been made in traffic flows control, with varying traffic volume levels, by using simulation software ‘Arena’. Simulation results show that the proposed traffic signal control method (EKC) has better performance over fuzzy logic and conventional pre-time controllers under light and heavy traffic conditions.

scholarly journals The Role of ICT in the Smart City Concept

2019 ◽  
Vol 14 (1) ◽  
pp. 63-74 ◽  
Author(s):  
Mariusz Czupich
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Public Services ◽  
Transportation Systems ◽  
City Management ◽  
Negative Consequences ◽  
Large Cities ◽  
Wide Range ◽  
The Face

The concept of a smart city enables the effective implementation of public services despite the negative consequences related to population growth in large cities. City authorities, in the face of growing demand for public services, often use a wide range of smart city instruments in various areas of operation. Despite the fact that a large part of innovative solutions is widespread and used, such as intelligent transportation systems or e-office, new opportunities are still emerging which are aimed at improving the quality of life for city dwellers. The aim of the article is to define the role of ICT in smart city management. The subjects of analysis are innovative instruments used in technologically advanced cities as well as contemporary challenges facing city management. The functioning of the city depends to a large extent on access to the communication network, mobile devices as well as on infrastructure connected with them. Therefore, it is necessary, on the one hand, to ensure the capacity of connections and network communication, and, on the other hand, to involve citizens in the process of creating new solutions.

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