scholarly journals Temporal Aggregation Effects in Spatiotemporal Traffic Modelling

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6931
Author(s):  
Dmitry Pavlyuk
Keyword(s):  
Travel Time ◽  
Urban Traffic ◽  
Sensor Data ◽  
Model Specification ◽  
Data Series ◽  
Temporal Aggregation ◽  
Traffic Forecasting ◽  
Spatiotemporal Models ◽  
Aggregation Level ◽  
Selection Of

Spatiotemporal models are a popular tool for urban traffic forecasting, and their correct specification is a challenging task. Temporal aggregation of traffic sensor data series is a critical component of model specification, which determines the spatial structure and affects models’ forecasting accuracy. Through extensive experiments with real-world data, we investigated the effects of the selected temporal aggregation level for forecasting performance of different spatiotemporal model specifications. A set of analysed models include travel-time-based and correlation-based spatially restricted vector autoregressive models, compared to classical univariate and multivariate time series models. Research experiments are executed in several dimensions: temporal aggregation levels, forecasting horizons (one-step and multi-step forecasts), spatial complexity (sequential and complex spatial structures), the spatial restriction approach (unrestricted, travel-time-based and correlation-based), and series transformation (original and detrended traffic volumes). The obtained results demonstrate the crucial role of the temporal aggregation level for identification of the spatiotemporal traffic flow structure and selection of the best model specification. We conclude that the common research practice of an arbitrary selection of the temporal aggregation level could lead to incorrect conclusions on optimal model specification. Thus, we recommend extending the traffic forecasting methodology by validation of existing and newly developed model specifications for different temporal aggregation levels. Additionally, we provide empirical results on the selection of the optimal temporal aggregation level for the discussed spatiotemporal models for different forecasting horizons.

Continuous ACO in a SVR Traffic Forecasting Model

2011 ◽  
pp. 410-417
Author(s):  
Wei-Chiang Samuelson Hong
Keyword(s):  
Time Series ◽  
Travel Time ◽  
Traffic Flow ◽  
Urban Traffic ◽  
Forecasting Model ◽  
Risk Minimization ◽  
Minimization Principle ◽  
Traffic Forecasting ◽  
Proposed Model ◽  
Fuel Costs

The effective capacity of inter-urban motorway networks is an essential component of traffic control and information systems, particularly during periods of daily peak flow. However, slightly inaccurate capacity predictions can lead to congestion that has huge social costs in terms of travel time, fuel costs and environment pollution. Therefore, accurate forecasting of the traffic flow during peak periods could possibly avoid or at least reduce congestion. Additionally, accurate traffic forecasting can prevent the traffic congestion as well as reduce travel time, fuel costs and pollution. However, the information of inter-urban traffic presents a challenging situation; thus, the traffic flow forecasting involves a rather complex nonlinear data pattern and unforeseen physical factors associated with road traffic situations. Artificial neural networks (ANNs) are attracting attention to forecast traffic flow due to their general nonlinear mapping capabilities of forecasting. Unlike most conventional neural network models, which are based on the empirical risk minimization principle, support vector regression (SVR) applies the structural risk minimization principle to minimize an upper bound of the generalization error, rather than minimizing the training errors. SVR has been used to deal with nonlinear regression and time series problems. This investigation presents a short-term traffic forecasting model which combines SVR model with continuous ant colony optimization (SVRCACO), to forecast inter-urban traffic flow. A numerical example of traffic flow values from northern Taiwan is employed to elucidate the forecasting performance of the proposed model. The simulation results indicate that the proposed model yields more accurate forecasting results than the seasonal autoregressive integrated moving average (SARIMA) time-series model.

scholarly journals Study on the Selection Model of Staying Adjustment Bus Lines along Rail Transit

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Jie Cui ◽  
Yueer Gao ◽  
Jing Cheng ◽  
Lei Shi
Keyword(s):  
Decision Making ◽  
Travel Time ◽  
Public Transport ◽  
Traffic Congestion ◽  
Urban Traffic ◽  
Gps Data ◽  
Rail Transit ◽  
Travel Time Savings ◽  
Time Savings ◽  
Selection Of

To fully achieve effective rail transit, prevent the waste of conventional bus capacity along a rail transit line, and relieve the urban traffic congestion problem, it is necessary to screen for the adjustment of conventional bus lines prior to the operation of rail transit to provide a basis for further optimization of bus lines. Based on the analysis of spatial relationships between a rail transit line and conventional collinear bus lines and considering the time advantage characteristics of rail transit in rush hours, a model of the generalized travel time costs and travel time savings proportion in the collinear section of rail transit and bus was proposed. To evaluate the utility of rail transit relative to conventional bus collinear lines, the conventional bus lines to be adjusted were determined. Taking Xiamen as an example, the bus lines of Hubin East Road Station as the endpoint of metro line 1 were employed to calculate the model using GPS data of the buses, and the bus lines to be adjusted in the Hubin East Road were determined. The results show that the model is effective in the elastic selection of conventional bus lines that need to be adjusted and provides decision-making support for urban comprehensive public transport planning.

scholarly journals Values of Travel Time for Recreational Trips under Different Behavioural Rules

2021 ◽  
Vol 13 (12) ◽  
pp. 6831
Author(s):  
Rosa Marina González ◽  
Concepción Román ◽  
Ángel Simón Marrero
Keyword(s):  
Travel Time ◽  
National Parks ◽  
Traffic Congestion ◽  
National Park ◽  
Revealed Preference ◽  
Discrete Choice Models ◽  
Model Specification ◽  
Regret Minimization ◽  
Random Regret Minimization

In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.

Analyzing Travel Time Reliability from Sparse Probe Vehicle Data: A Case Study on the Effects of Spatial and Temporal Aggregation

2021 ◽  
pp. 036119812110315
Author(s):  
Markus Steinmaßl ◽  
Stefan Kranzinger ◽  
Karl Rehrl
Keyword(s):  
Travel Time ◽  
Time Of Day ◽  
Temporal Aggregation ◽  
Travel Time Reliability ◽  
Probe Vehicle ◽  
Vehicle Data ◽  
Depth Analysis ◽  
Data Source ◽  
Travel Time Index

Travel time reliability (TTR) indices have gained considerable attention for evaluating the quality of traffic infrastructure. Whereas TTR measures have been widely explored using data from stationary sensors with high penetration rates, there is a lack of research on calculating TTR from mobile sensors such as probe vehicle data (PVD) which is characterized by low penetration rates. PVD is a relevant data source for analyzing non-highway routes, as they are often not sufficiently covered by stationary sensors. The paper presents a methodology for analyzing TTR on (sub-)urban and rural routes with sparse PVD as the only data source that could be used by road authorities or traffic planners. Especially in the case of sparse data, spatial and temporal aggregations could have great impact, which are investigated on two levels: first, the width of time of day (TOD) intervals and second, the length of road segments. The spatial and temporal aggregation effects on travel time index (TTI) as prominent TTR measure are analyzed within an exemplary case study including three different routes. TTI patterns are calculated from data of one year grouped by different days-of-week (DOW) groups and the TOD. The case study shows that using well-chosen temporal and spatial aggregations, even with sparse PVD, an in-depth analysis of traffic patterns is possible.

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.

Stock assessment and risk analysis for the school shark (Galeorhinus galeus) off southern Australia

1998 ◽  
Vol 49 (7) ◽  
pp. 719 ◽  
Author(s):  
André E. Punt ◽  
Terence I. Walker
Keyword(s):  
Stock Assessment ◽  
Catch Rate ◽  
Data Series ◽  
Structured Population ◽  
Population Dynamics Model ◽  
Equilibrium Size ◽  
Structured Population Dynamics ◽  
Pup Survival ◽  
Galeorhinus Galeus ◽  
Selection Of

A spatially aggregated age- and sex-structured population dynamics model was fitted to standardized catch-rate data from the school shark resource off southern Australia. The model incorporates the peculiarities of shark populations and fisheries, including the pupping process and the selectivity characteristics of gill-nets. Estimates are determined by a Bayesian approach that incorporates prior distributions for virgin biomass, the parameter that determines productivity, and the variation in pup survival. Tests of sensitivity include changing the data series used, varying the value of adult natural mortality, and changing the prior distribution for the productivity parameter. The point estimates of the mature biomass at the start of 1995 range from 13% to 45% of the pre-exploitation equilibrium size, depending on the specifications of the assessment. The results are notably sensitive to the selection of a catch-rate series. Results suggest that the current fishing intensity will lead to further declines in abundance, that a reduction of ~20% in fishing mortality would achieve a 0.5 probability of not declining further, and that a reduction of 42% would achieve with a probability of 0.8 the management goal of not being below the 1996 mature biomass at the start of 2011. Extra keyword: CPUE.

scholarly journals Research on Electronic Image Stabilization Technology of Vehicle-Mounted Remote-Controlled Weapon Station

2021 ◽  
Vol 2083 (3) ◽  
pp. 032061
Author(s):  
Shumin Qin ◽  
Lizhen Zhao ◽  
Xingke Tian ◽  
Lidan Li ◽  
Shuyun Liu
Keyword(s):  
System Design ◽  
Robust Stability ◽  
Sensor Data ◽  
Two Stage ◽  
Image Stabilization ◽  
Image Information ◽  
Gyro Sensor ◽  
Image Compensation ◽  
Stable Scheme ◽  
Selection Of

Abstract The image information of the vehicle-mounted remote-controlled weapon station is jittered and blurred when the stance changes or vibrates, which increases the aiming difficulty and observation fatigue of the shooter, in order to realize the stable marching fire of the vehicle-mounted remote-controlled weapon station, the two-stage stable scheme with the shared gyro sensor is adopted in the system design, namely, the aiming device is rigidly fixed on the initially stable weapon platform, and then the electronic image stabilization is carried out. This paper proposes an approach combining two image stabilization schemes: gyro sensor data and image projection registration, optimizes the selection of image compensation data by registering and comparing the results of the two stable data, and uses the special features of the two schemes to improve the robust stability of electronic image stabilization, which ensure the observation effect of video image stabilization of the vehicle-mounted remote-controlled weapon station.

scholarly journals Real-time urban regional route planning model for connected vehicles based on V2X communication

2020 ◽  
Vol 13 (1) ◽  
pp. 517-538 ◽  
Author(s):  
Pangwei Wang ◽  
Hui Deng ◽  
Juan Zhang ◽  
Mingfang Zhang
Keyword(s):  
Land Use ◽  
Travel Time ◽  
Real Time ◽  
Land Use Planning ◽  
Route Planning ◽  
Urban Traffic ◽  
Urban Transport ◽  
Connected Vehicles ◽  
Planning Model ◽  
Optimal Route

Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.

Sign in / Sign up

Export Citation Format

Share Document