The Impact of Traffic Information Acquisition on the Traffic Conditions of the Athens Greater Area

2015 ◽  
pp. 174-191
Author(s):  
Athena Tsirimpa ◽  
Amalia Polydoropoulou
Keyword(s):  
Information Acquisition ◽  
Latent Variable ◽  
Traffic Information ◽  
Activity Scheduling ◽  
Variable Model ◽  
Travel Information ◽  
Traffic Conditions ◽  
Real Time Information ◽  
The Impact ◽  
Time Information

The main objective of this article is to gain fundamental understanding on the effect of real time information acquisition, on the traffic conditions of the Athens greater area. Activity scheduling is a dynamic process, where individuals often need to modify their schedule, as a result of new insights. Research so far hasn't analyzed the effect of traffic information acquisition, in activity scheduling, although several studies have been conducted to capture the factors that influence the rescheduling of activities. An integrated latent variable model has been estimated, that predicts the probability of rescheduling activities as a function of flexibility, mode choice constraints and travel information. The analysis of the results indicates that one of the biggest impacts of traffic information acquisition is reflected in the rescheduling of activities. Therefore, traffic information not only can significantly improve the travel experience of individuals but may directly affect the performance of the transportation system.

The Impact of Traffic Information Acquisition on the Traffic Conditions of the Athens Greater Area

2014 ◽  
Vol 5 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Athena Tsirimpa ◽  
Amalia Polydoropoulou
Keyword(s):  
Information Acquisition ◽  
Latent Variable ◽  
Traffic Information ◽  
Activity Scheduling ◽  
Variable Model ◽  
Travel Information ◽  
Traffic Conditions ◽  
Real Time Information ◽  
The Impact ◽  
Time Information

The main objective of this article is to gain fundamental understanding on the effect of real time information acquisition, on the traffic conditions of the Athens greater area. Activity scheduling is a dynamic process, where individuals often need to modify their schedule, as a result of new insights. Research so far hasn't analyzed the effect of traffic information acquisition, in activity scheduling, although several studies have been conducted to capture the factors that influence the rescheduling of activities. An integrated latent variable model has been estimated, that predicts the probability of rescheduling activities as a function of flexibility, mode choice constraints and travel information. The analysis of the results indicates that one of the biggest impacts of traffic information acquisition is reflected in the rescheduling of activities. Therefore, traffic information not only can significantly improve the travel experience of individuals but may directly affect the performance of the transportation system.

Driver Acceptance of Unreliable Route Guidance Information

1994 ◽  
Vol 38 (16) ◽  
pp. 1062-1066 ◽  
Author(s):  
Richard J. Hanowski ◽  
Susan C. Kantowitz ◽  
Barry H. Kantowitz
Keyword(s):  
Real Time ◽  
Heavy Traffic ◽  
Traffic Information ◽  
Route Guidance ◽  
Experimental Conditions ◽  
Traveler Information ◽  
Traveler Information Systems ◽  
Traffic Conditions ◽  
Driver Acceptance ◽  
Real Time Information

Human factors research can be used to design safe and efficient Advanced Traveler Information Systems (ATIS) that are easy to use (Kantowitz, Becker, & Barlow, 1993). This research used the Battelle Route Guidance Simulator (RGS) to examine two important issues related to driver behavior and acceptance of ATIS technology: (1) the effect of route familiarity on ATIS use and acceptance and (2) the level of information accuracy needed for an ATIS to be accepted and considered useful. The RGS included two 486 computers that provided drivers with real-time information and traffic reports. Drivers used a touch screen to select routes on one computer monitor and watched the results of their selection (i.e., real-time video of the traffic) on a second computer monitor. Drivers could use the system to obtain information about the traffic conditions on any link before traversing a route. In this experiment, subjects were exposed to four experimental conditions involving manipulation of the driver's familiarity with the route and the reliability of the traffic information obtained from the RGS (i.e., 100%, 71%, and 43% accuracy). The driver's goal was to reach the destination as quickly as possible by avoiding heavy traffic. The results indicated that drivers were able to benefit from system information when it was reliable, but not when it was unreliable. Trust ratings for the 43% accuracy group were significantly higher at the beginning of the four trials than at the end. Also, drivers were more apt to rely on the ATIS and accept information given in an unfamiliar traffic network versus a familiar one.

Models for Predicting Bus Delays

1998 ◽  
Vol 1623 (1) ◽  
pp. 8-15 ◽  
Author(s):  
Ali M. Abdelfattah ◽  
Ata M. Khan
Keyword(s):  
Arrival Time ◽  
Field Studies ◽  
Traffic Operations ◽  
Control Center ◽  
Transit Service ◽  
Traffic Conditions ◽  
Bus Travel Time ◽  
Real Time Information ◽  
Time Information ◽  
Tracking Technology

The provision of accurate bus arrival time information to users is essential for improving the attractiveness of public transit service. Although bus-tracking technology provides real-time information to the control center about the location of a bus, there is a need to improve the prediction of bus travel time downstream from location of last observation in mixed traffic operations. Methods are required for making predictions in normal traffic conditions, as well as in conditions in which a temporary lane closure is experienced due to a variety of reasons, such as incidents and road improvement activities. The development of models for the estimation of the effect of changes in traffic and lane closures on bus performance is described. A microsimulation approach was used, supplemented by field studies. The models developed meet calibration tests and were verified by field data.

scholarly journals The Performance of Challenges Faced by SME in Managing Real-Time Information in the Inventory Management Process

2019 ◽  
Vol 8 (12) ◽  
pp. 5614-5618
Keyword(s):  
Real Time ◽  
Inventory Management ◽  
Business Performance ◽  
Qualitative Method ◽  
Skilled Worker ◽  
Depth Interview ◽  
Real Time Information ◽  
The Impact ◽  
Time Information ◽  
Food Manufacturer

Managing real-time information is an important task for any organization regardless of the size. This is because real-time information is used as the basis for an organization to make decisions that will affect the business if the information obtained is inaccurate, slow and outdated. For SMEs, this is a great challenge as it faces capital constraints and outdated technological applications. Thus, the purpose of this study to examine the challenges faced by SMEs in managing the real-time information to their inventory management and the impact on the overall business performance. A qualitative method was adopted where the in-depth interview was using to extract the information. Based on the saturation principle, the respondent was selected specifically from the SMEs in food manufacturer based in Malacca Halal Hub area. The finding of this study has supported the previous study on the challenges and issue of real-time information facing by the SMEs. A notable finding in this research is that SMEs is employing a skilled worker to manage the absence of an information system to manage real-time information and still capable to generate a profit from the business. This study extended the previous finding and offer an opportunity for further exploration in this area.

Breathe Easy, There's an App for That: Using Information and Communication Technology to Avoid Air Pollution in Bogotá

2021 ◽  
Author(s):  
Allen Blackman ◽  
Bridget Hoffmann
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Avoidance Behavior ◽  
Ambient Air ◽  
Text Messages ◽  
Information And Communication ◽  
Real Time Information ◽  
The Impact ◽  
Time Information

Ambient air pollution is a leading cause of death in developing countries. In theory, using smartphone apps, text messages, and other personal information and communication technologies to disseminate real-time information about such pollution can boost avoidance behavior like wearing face masks and closing windows. Yet evidence on their effectiveness is limited. We conduct a randomized controlled trial to evaluate the impact of training university students in Bogotá, Colombia to use a newly available municipal government smartphone app that displays real-time information on air quality. The training increased participants acquisition of information about air quality, their knowledge about avoidance behavior, and their actual avoidance behavior. It also enhanced their concern about other environmental issues. These effects were moderated by participants characteristics. For example, the training was generally less effective among job holders.

Dynamic Aspects of Commuter Decisions Under Advanced Traveler Information Systems: Modeling Framework and Experimental Results

1998 ◽  
Vol 1645 (1) ◽  
pp. 111-119 ◽  
Author(s):  
Yu-Hsin Liu ◽  
Hani S. Mahmassani
Keyword(s):  
Real Time ◽  
Switching Behavior ◽  
Traffic Information ◽  
Advanced Traveler Information Systems ◽  
Traveler Information ◽  
Traveler Information Systems ◽  
Real Time Traffic ◽  
Departure Time ◽  
Real Time Information ◽  
Time Information

Previous work on the effect of advanced traveler information systems was concerned primarily with immediate route choice decisions in response to real-time traffic information. Real-time traffic information also influences day-to-day decisions of trip makers, including departure time and route choices. Joint departure time decision and pretrip route selection are addressed, as well as en route path switching behavior by commuters under real-time information availability. Data were used from laboratory experiments using a dynamic interactive traveler simulator that allows actual commuters to simultaneously interact with each other within a simulated traffic corridor. Given real-time information provided by the system, commuters determine their departure time and route at the origin and select paths en route at various decision nodes along the trip. Day-to-day dynamic models of commuters’ joint departure time and route switching decisions are developed and calibrated by using a multinomial probit model framework that takes into account commuters’ learning from experience. The analysis provides insight into day-to-day effects of real-time traffic information on user decisions. Results indicate that the reliability of real-time information and supplied schedule delay (relative to the commuters’ preferred arrival time) are significant variables that influence users’ indifference band governing route switching behavior both pretrip and en route. These models are intended for use within evaluation frameworks (e.g., simulation-assignment models). In addition, the substantive insights provide guidelines for the design of real-time information content and systems.

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