scholarly journals Using GPS Trajectories to Adaptively Plan Bus Lanes

2021 ◽  
Vol 11 (3) ◽  
pp. 1035
Author(s):  
Yanjie Sun ◽  
Mingguang Wu ◽  
Huien Li
Keyword(s):  
Optimization Problem ◽  
Construction Cost ◽  
Urban Traffic ◽  
Planning Problem ◽  
Multiobjective Optimization Problem ◽  
The Road ◽  
Shenzhen City ◽  
Road Condition ◽  
Gps Trajectories ◽  
Bus Lane

Since bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly specified. Many bus GPS trajectories have been accumulated and can be contiguously gathered if needed. This paper proposes a trajectory-based bus lane planning method. First, we formulize the bus lane planning problem as a multiobjective optimization problem in which the road conditions, traffic flow, connectivity of bus lanes, and construction cost are organized as four constraints, and road utilization and bus punctuality are modeled as two objectives. Then, an evolutionary algorithm-based method is presented to solve the problem. We tested the model in the Nanshan District, Shenzhen City, China. Through a comparison with existing survey-based methods, the parameters associated with road conditions in this method are directly extracted from GPS trajectories, and this method is more effectively deployed than other methods. Since GPS trajectories can cover a wide area if needed, and because the proposed method can be effectively executed, this method can be adapted to large urban scales.

scholarly journals Fuzzy polychromatic sets constraint model for route planning problem

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142095924
Author(s):  
Cai Chao ◽  
Gong Zhi Xing ◽  
Qin Xiao Wei ◽  
Zhou Qiu Shi ◽  
Sun Xi Xia
Keyword(s):  
Mutual Coupling ◽  
Optimization Problem ◽  
Route Planning ◽  
Planning System ◽  
Planning Problem ◽  
Multiobjective Optimization Problem ◽  
Constraint Condition ◽  
Operation Rules ◽  
Aerial Vehicle ◽  
Constraint Model

Unmanned aerial vehicle route planning is a complex multiconstrained multiobjective optimization problem. Due to the complexity of various constraints and the mutual coupling between them, the expression of constraint conditions is not universal and normative. The development, maintenance, and upgrading of an existing route planning system are very difficult. In this article, by establishing the polychromatic sets of aircraft, aircraft equipment, and flight actions, creating the fuzzy relational matrix between equipment and actions and between actions and actions, this article realizes the standardized and generalized expression of the constraint condition of the route planning problem. Then the analysis and inspection of the constraint conditions are realized by the polychromatic sets operation rules.

scholarly journals Environmental and Social Problems and Countermeasures in Transportation System under Resource Constraints

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Qianyuan Li ◽  
Shaoying Tian
Keyword(s):  
Optimization Problem ◽  
Social Problems ◽  
Resource Constraints ◽  
Rapid Development ◽  
Transportation System ◽  
Urban Traffic ◽  
Route Optimization ◽  
Planning Problem ◽  
Selection Scheme ◽  
The Impact

With the rapid development of urban economy and the acceleration of urbanization, the demand for urban traffic is increasing rapidly. The single traffic-oriented planning does not take into account the requirements of traffic development on resources and the impact on the environment. The traffic construction of most cities can not fully meet the standard of ecotype. In this paper, the vehicle distribution route optimization problem under multiresource constraints such as vehicle energy capacity and vehicle loading capacity is studied, and the static and dynamic models of distribution route optimization under multiresource constraints are established. In the static distribution route optimization model, the distribution route optimization problem with subloops is solved by modifying the network structure and adding virtual resource points. In the dynamic model, the spatiotemporal network model is used to avoid the generation of subloops, and the description of the vehicle distribution route planning problem is more intuitive and accurate. The model enriches the vehicle distribution route selection scheme at the cost of expanding the model scale. And it can solve the time when the vehicle arrives and leaves the customer point. This paper provides a good countermeasure for solving the environmental and social problems in the transportation system under the condition of resource constraints.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

scholarly journals Measurements of urban traffic parameters before and after road reconstruction

2021 ◽  
Vol 11 (1) ◽  
pp. 365-376
Author(s):  
Andrzej Bąkowski ◽  
Leszek Radziszewski
Keyword(s):  
Urban Traffic ◽  
Noise Model ◽  
Vehicle Traffic ◽  
The Road ◽  
Passenger Vehicles ◽  
Before And After ◽  
Traffic Volumes ◽  
National Road ◽  
The City ◽  
Good Agreement

Abstract The study analyzed the parameters of vehicle traffic and noise on the national road in the section in the city from 2011 to 2016. In 2013–2014 this road was reconstructed. It was found that in most cases, the distribution of the tested variable was not normal. The median and selected percentiles of vehicle traffic parameters and noise were examined. The variability and type A uncertainty of the results were described and evaluated. The results obtained for the data recorded on working and non-working days were compared. The vehicle cumulative speed distributions, for two-way four-lane road segments in both directions were analyzed. A mathematical model of normalized traffic flow has been proposed. Fit factor R2 of the proposed equations to the experimental data for passenger vehicles ranges from 0.93 to 0.99. It has been shown that two years after the road reconstruction, the median noise level did not increase even though traffic volumes and vehicle speeds increased. The Cnossos noise model was validated for data recorded over a period of 6 years. A very good agreement of the medians determined according to the Cnossos-EU model and the measured ones was obtained. It should be noted, however, that for the other analyzed percentiles, e.g. 95%, the discrepancies are larger.

Engine Mount Optimization for Vibration Isolation in Motorcycles

2006 ◽  
Author(s):  
Sudhir Kaul ◽  
Anoop K. Dhingra ◽  
Timothy G. Hunter
Keyword(s):  
Optimization Problem ◽  
Vibration Isolation ◽  
Total Force ◽  
Engine Mounts ◽  
The Road ◽  
Design Variables ◽  
Swing Arm ◽  
Engine Mount ◽  
Six Degree Of Freedom

This paper presents a comprehensive model to capture the dynamics of a motorcycle system in order to evaluate the quality of vibration isolation. The two main structural components in the motorcycle assembly - the frame and the swing-arm - are modeled using reduced order finite element models; the power-train assembly is modeled as a six degree-of-freedom (DOF) rigid body connected to the frame through the engine mounts and to the swing-arm through a shaft assembly. The engine mounts are modeled as tri-axial spring-damper systems. Models of the front-end assembly as well as front and rear tires are also included in the overall model. The complete vehicle model is used to solve the engine mount optimization problem so as to minimize the total force transmitted to the frame while meeting packaging and other side constraints. The mount system parameters - stiffness, position and orientation vectors - are used as design variables for the optimization problem. The imposed loads include forces and moments due to engine imbalance as well as loads transmitted due to irregularities in the road surface through the tire patch.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

Schedule-Constrained Demand Management in Two-Region Urban Networks

2021 ◽  
Author(s):  
Sakitha Kumarage ◽  
Mehmet Yildirimoglu ◽  
Mohsen Ramezani ◽  
Zuduo Zheng
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Time Window ◽  
Demand Management ◽  
Urban Traffic ◽  
Fundamental Diagram ◽  
Constrained System ◽  
Nonlinear Optimization Problem ◽  
Management Platform ◽  
User Compliance

Demand management aiming to optimize system cost while ensuring user compliance in an urban traffic network is a challenging task. This paper introduces a cooperative demand redistribution strategy to optimize network performance through the retiming of departure times within a limited time window. The proposed model minimizes the total time spent in a two-region urban network by incurring minimal disruption to travelers’ departure schedules. Two traffic models based on the macroscopic fundamental diagram (MFD) are jointly implemented to redistribute demand and analyze travelers’ reaction. First, we establish equilibrium conditions via a day-to-day assignment process, which allows travelers to find their preferred departure times. The trip-based MFD model that incorporates individual traveler attributes is implemented in the day-to-day assignment, and it is conjugated with a network-level detour ratio model to incorporate the effect of congestion in individual traveler route choice. This allows us to consider travelers with individual preferences on departure times influenced by desired arrival times, trip lengths, and earliness and lateness costs. Second, we develop a nonlinear optimization problem to minimize the total time spent considering both observed and unobserved demand—that is, travelers opting in and out of the demand management platform. The accumulation-based MFD model that builds on aggregated system representation is implemented as part of the constraints in the nonlinear optimization problem. The results confirm the resourcefulness of the model to address complex two-region traffic dynamics and to increase overall performance by reaching a constrained system optimum scenario while ensuring the applicability at both full and partial user compliance conditions.

scholarly journals Traffic Analysis and Pavement Technology as a Tool for Urban Noise Control

2015 ◽  
Vol 61 (4) ◽  
pp. 107-126 ◽  
Author(s):  
K. J. Kowalski ◽  
A. J. Brzeziński ◽  
J. B. Król ◽  
P. Radziszewski ◽  
Ł. Szymański
Keyword(s):  
Urban Space ◽  
Urban Traffic ◽  
Vehicle Speed ◽  
Noise Emission ◽  
Noise Barriers ◽  
Technical Improvement ◽  
Protection Measures ◽  
The Road ◽  
Road Pavement ◽  
Acoustic Conditions

Traffic related noise is currently considered as an environmental pollution. Paper presents results of multidirectional study attempting to serve urban traffic without the need to erect noise barriers interfering urban space. Initial concept of the road expansion included construction of 1000 m of noise barriers dividing city space. Improvement in the acoustic conditions after construction completion is possible due to the applied noise protection measures: vehicle speed limit, smooth of traffic flow, use of road pavement of reduced noise emission and the technical improvement of the tramway.

scholarly journals Characterization of Road Condition with Data Mining Based on Measured Kinematic Vehicle Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Johannes Masino ◽  
Jakob Thumm ◽  
Guillaume Levasseur ◽  
Michael Frey ◽  
Frank Gauterin ◽  
...  
Keyword(s):  
Data Mining ◽  
Support Vector ◽  
Matlab Toolbox ◽  
Data Set ◽  
The Road ◽  
Acceleration Sensors ◽  
Road Surfaces ◽  
Road Condition ◽  
Sensor Signals

This work aims at classifying the road condition with data mining methods using simple acceleration sensors and gyroscopes installed in vehicles. Two classifiers are developed with a support vector machine (SVM) to distinguish between different types of road surfaces, such as asphalt and concrete, and obstacles, such as potholes or railway crossings. From the sensor signals, frequency-based features are extracted, evaluated automatically with MANOVA. The selected features and their meaning to predict the classes are discussed. The best features are used for designing the classifiers. Finally, the methods, which are developed and applied in this work, are implemented in a Matlab toolbox with a graphical user interface. The toolbox visualizes the classification results on maps, thus enabling manual verification of the results. The accuracy of the cross-validation of classifying obstacles yields 81.0% on average and of classifying road material 96.1% on average. The results are discussed on a comprehensive exemplary data set.

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.

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