Adaptive Travel Time Path Selection in Hierarchical Index Road Network

2006 ◽  
Author(s):  
Adisak Sukul ◽  
Pattarasinee Bhattarakosol
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Path Selection ◽  
Time Path ◽  
Hierarchical Index

scholarly journals Analyzing travel time belief reliability in road network under uncertain random environment

2021 ◽  
Author(s):  
Yi Yang ◽  
Siyu Huang ◽  
Meilin Wen ◽  
Xiao Chen ◽  
Qingyuan Zhang ◽  
...  
Keyword(s):  
Travel Time ◽  
Random Environment ◽  
Road Network ◽  
Path Selection ◽  
Travel Time Reliability ◽  
Time Data ◽  
Urban Road Network ◽  
Urban Road ◽  
Starting Point ◽  
The Impact

Abstract It is necessary to understand the operation status of the urban road network, especially when the network is complicated and uncertain. Taking travel time data as the starting point, we have studied the shortcomings of existing travel time reliability indicators. Most of them simplify or even ignore the information of traffic performance thresholds. According to the characteristics of the real urban road network, by extracting the information of the subject and object of the traffic service, we proposed measurement of the reliability of travel time in an uncertain random environment, that is, the travel time belief reliability, which takes the impact of the epistemic and random uncertainty on reliability into account. Next, we established the belief reliability model of travel task under the uncertain random road environment. The model considers path selection, departure status and road conditions, and gives a path selection algorithm under time-varying road network. Besides, using the uncertainty regression analysis method, we explored the impact of road objective factors and driving state factors on the travel time threshold. Finally, we took the actual travel task in Beijing as an example to verify the feasibility and practicability of the model and algorithm.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

scholarly journals RealTE: Real-time Trajectory Estimation Over Large-Scale Road Networks

2022 ◽  
Author(s):  
Qibin Zhou ◽  
Qingang Su ◽  
Dingyu Yang
Keyword(s):  
Travel Time ◽  
Real Time ◽  
High Speed ◽  
Road Network ◽  
Large Scale ◽  
Road Networks ◽  
Trajectory Data ◽  
Real Time Traffic ◽  
Histogram Estimation ◽  
Traffic Estimation

Real-time traffic estimation focuses on predicting the travel time of one travel path, which is capable of helping drivers selecting an appropriate or favor path. Statistical analysis or neural network approaches have been explored to predict the travel time on a massive volume of traffic data. These methods need to be updated when the traffic varies frequently, which incurs tremendous overhead. We build a system RealTER⁢e⁢a⁢l⁢T⁢E, implemented on a popular and open source streaming system StormS⁢t⁢o⁢r⁢m to quickly deal with high speed trajectory data. In RealTER⁢e⁢a⁢l⁢T⁢E, we propose a locality-sensitive partition and deployment algorithm for a large road network. A histogram estimation approach is adopted to predict the traffic. This approach is general and able to be incremental updated in parallel. Extensive experiments are conducted on six real road networks and the results illustrate RealTE achieves higher throughput and lower prediction error than existing methods. The runtime of a traffic estimation is less than 11 seconds over a large road network and it takes only 619619 microseconds for model updates.

scholarly journals Research on path selection system based on green transportation

2021 ◽  
Vol 275 ◽  
pp. 02043
Author(s):  
Linyi Qian
Keyword(s):  
Travel Time ◽  
Energy Efficient ◽  
Time Estimation ◽  
Clean Energy ◽  
Path Selection ◽  
Travel Time Estimation ◽  
Optimal Route ◽  
Actual Problem ◽  
Transportation Sector ◽  
Energy Transportation

The transportation sector already accounts for 14% of global greenhouse gas emissions. Therefore, controlling carbon emissions in the transportation sector has become a top priority for China and other countries around the world. In addition to the technological development of clean energy transportation, the most critical aspect of the globalization of new energy transportation industry and market is the optimization of access routes. This paper will be based on road travel time estimation and optimal path selection of energy efficient transportation research hotspots. Firstly, the accuracy of road travel time estimation is improved according to the basic law of traffic flow. At the same time, this paper defines the optimal route into two cases of shortest path and shortest time for solving. Finally, the actual solution process is given according to the actual problem, as well as the optimal route, aiming to promote the strong development in the field of intelligent navigation system and energy-efficient transportation.

scholarly journals Vehicle Routing for Dynamic Road Network Based on Travel Time Reliability

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 190596-190604
Author(s):  
Luping Zhi ◽  
Xizhao Zhou ◽  
Jing Zhao
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Road Network ◽  
Travel Time Reliability
Sign in / Sign up

Export Citation Format

Share Document