scholarly journals Proactive Traffic Information Control in Emergency Evacuation Network

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Zhengfeng Huang
Keyword(s):  
Real Time ◽  
Road Network ◽  
Emergency Evacuation ◽  
Traffic Information ◽  
Information Control ◽  
Traffic Condition ◽  
The Road ◽  
Real Time Information ◽  
Near Future ◽  
Time Information

Traffic demand in emergency evacuation is usually too large to be effectively managed with reactive traffic information control methods. These methods adapt to the road traffic passively by publishing real-time information without consideration of the routing behavior feedback produced by evacuees. Other remedy measures have to be prepared in case of nonrecurring congestion under these methods. To use the network capacity fully to mitigate near-future evacuation traffic congestion, we propose proactive traffic information control (PTIC) model. Based on the mechanism between information and routing behavior feedback, this model can change the route choice of evacuees in advance by dissipating strategic traffic information. Generally, the near-future traffic condition is difficult to accurately predict because it is uncertain in evacuation. Assume that the value of traffic information obeys certain distribution within a range, and then real-time traffic information may reflect the most-likely near-future traffic condition. Unlike the real-time information, the proactive traffic information is a selection within the range to achieve a desired level of the road network performance index (total system travel time). In the aspect of the solution algorithm, differential equilibrium decomposed optimization (D-EDO) is proposed to compare with other heuristic methods. A field study on a road network around a large stadium is used to validate the PTIC.

scholarly journals Ergonomic Evaluation of Smart Navigation System for Riding on Motorcycle

2018 ◽  
Vol 201 ◽  
pp. 01009
Author(s):  
Po-Hsiang Liu ◽  
Yong-Cheng Li ◽  
Yu-Jung Tsai
Keyword(s):  
Factor Analysis ◽  
Real Time ◽  
Navigation System ◽  
Response Rate ◽  
Smart Device ◽  
The Road ◽  
On The Road ◽  
Real Time Information ◽  
Design Factors ◽  
Time Information

A smart navigation device could be provided to keep riders’ eyes safely on the road while riding on motorcycle. Present study surveyed the riding behaviors and examined the fifteen design factors about navigation device and determined the priority of each factor. Further, navigation device have been evaluated on road. A total of 550 questionnaires were dispatched, with a response rate of 89 % (n = 491). Results of factor analysis showed the six dimensions of prediction information, real-time information, brand and appearance, cost, functionality, efficacy and utility. Further, the highest priority design factors of smart navigation device are reminder for speeding camera, intersection name of next turn, distance of next turn, lane guide and map guide line. After navigation device have been evaluated on road, the smart device that effortlessly guides rider through the safest and most enjoyable riding routes with intuitive light patterns. Results of this study could provide the information for the design of the smart navigation device for riding on motorcycle.

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.

scholarly journals Real Time Traffic Information from Ferries to Optimise Intermodal Transport Chains

2019 ◽  
pp. 16-19
Author(s):  
Nina Vojdani
Keyword(s):  
Real Time ◽  
Customer Service ◽  
Traffic Information ◽  
Fleet Management ◽  
The Baltic Sea ◽  
Real Time Traffic ◽  
Multimodal Transport ◽  
The Baltic ◽  
Real Time Information ◽  
Time Information

The baltic sea traffics are in particular characterized by ferry and RoRo traffic. Numerous ferry connections link the neighboring countries and thus allow for an exchange of goods. The use of real time information still has untapped potential so that the respective initial and terminal hauls as well as port‐related transshipment processes can be matched to the ferry traffic as a major part of journey in multimodal transport chains. In this way, to provide dispatchers with decision‐relevant real time information enables timely decision‐making, not only with regard to efficient fleet management, but also with a view to a better customer service.

scholarly journals Dynamic Path Optimization with Real-Time Information for Emergency Evacuation

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Huajun Zhang ◽  
Qin Zhao ◽  
Zihui Cheng ◽  
Linfan Liu ◽  
Yixin Su
Keyword(s):  
Real Time ◽  
Optimal Path ◽  
Emergency Evacuation ◽  
Path Optimization ◽  
Breadth First Search ◽  
Exit Port ◽  
Dynamic Path ◽  
Short Time ◽  
Real Time Information ◽  
Time Information

In order to find the optimal path for emergency evacuation, this paper proposes a dynamic path optimization algorithm based on real-time information to search the optimal path and it takes fire accident as an example to introduce the algorithm principle. Before the accidents, it uses the Dijkstra algorithm to get the prior evacuation network which includes evacuation paths from each node to the exit port. When the accidents occur, the evacuees are unable to pass through the passage where the accident point and the blocking point are located, then the proposed method uses the breadth-first search strategy to solve the path optimization problem based on the prior evacuation network, and it dynamically updates the evacuation path according to the real-time information. Because the prior evacuation network includes global optimal evacuation paths from each node to the exit port, the breadth-first search algorithm only searches local optimal paths to avoid the blockage node or dangerous area. Because the online optimization solves a local pathfinding problem and the entire topology optimization is an offline calculation, the proposed method can find the optimal path in a short time when the accident situation changes. The simulation tests the performances of the proposed algorithm with different situations based on the topology of a building, and the results show that the proposed algorithm is effective to get the optimal path in a short time when it faces changes caused by the factors such as evacuee size, people distribution, blockage location, and accident points.

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