Locating changeable message signs for advanced traffic information and management systems

2007 ◽  
Vol 34 (5) ◽  
pp. 651-663 ◽  
Author(s):  
Liping Fu ◽  
Jeffrey Henderson ◽  
Shuo Li
Keyword(s):  
Queuing Theory ◽  
Traffic Information ◽  
Planning Problem ◽  
Multiple Time ◽  
Driver Behaviour ◽  
Traffic Demand ◽  
Proposed Model ◽  
Changeable Message Signs ◽  
Model Realism ◽  
Message Signs

This paper presents an optimization model for locating changeable message signs (CMSs) on an integrated freeway-arterial network. Compared with existing models, the proposed model represents a well-balanced compromise between computational efficiency required to solve problems of realistic size, and model realism to ensure the quality of solutions. The model has three unique features: (1) it recognizes that locating CMSs is a planning problem that must take into account both current and future needs and benefits, (2) it evaluates benefits of CMSs over multiple time periods with different traffic distributions, and (3) it explicitly considers inherent variations in incident characteristics across links and over time. A sensitivity analysis is performed to examine the potential impacts on optimal CMSs locations resulting from uncertainties in various input parameters, such as traffic demand, incident attributes, and driver behaviour. Lastly, the proposed model is applied to the Highway 401 express-collector freeway system in Toronto for relocating the existing CMSs.Key words: changeable message signs (CMSs), location optimization, traffic assignment, queuing theory.

A network flow-based model for operations planning in home health care delivery

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fabián Castaño ◽  
Nubia Velasco
Keyword(s):  
Health Care ◽  
Home Health Care ◽  
Care Delivery ◽  
Real Life ◽  
Home Health ◽  
Planning Problem ◽  
Multiple Time ◽  
Content Type ◽  
Proposed Model ◽  
Care Workers

PurposeTo solve the problem, a mathematical model is proposed; it relies on a directed acyclic graph (DAG), in which arcs are used to indicate whether a pair of appointments can be assigned to the same route or not (and so to the same care worker). The proposed model aims at minimizing the personnel required to meet daily demand and balancing workloads among the workers while considering the varying traffic patterns derived from traffic congestion.Design/methodology/approachThis paper aims at providing solution approaches for addressing the problem of assigning care workers to deliver home health-care (HHC) services, demanding different skills each. First, a capacity planning problem is considered, where it is necessary to define the number of workers required to satisfy patients' requests and then, patients are assigned to the care workers along with the sequence followed to visit them, thus solving a scheduling problem. The benefits obtained by permitting patients to propose multiple time slots where they can be served are also explored.FindingsThe results indicate that the problem can be efficiently solved for medium-sized instances, that is, up to 100 daily patient requests. It is also indicated that asking patients to propose several moments when they can receive services helps to minimize the need for care workers through more efficient route allocations without affecting significantly the balance of the workloads.Originality/valueThis article provides a new framework for modeling and solving a HHC routing problem with multiskilled personnel. The proposed model can be used to identify efficient daily plans and can handle realistic characteristics such as time-dependent travel times or be extended to other real-life applications such as maintenance scheduling problems.

Modeling Bus Capacity for Bus Stops Using Queuing Theory and Diffusion Approximation

2021 ◽  
pp. 036119812110302
Author(s):  
Chao Wang ◽  
Weijie Chen ◽  
Yueru Xu ◽  
Zhirui Ye
Keyword(s):  
Approximation Method ◽  
Service Time ◽  
Diffusion Approximation ◽  
Coefficient Of Variation ◽  
Queuing Theory ◽  
Queuing Model ◽  
Bus Stop ◽  
Proposed Model ◽  
Bus Stops ◽  
Bus Service

For bus service quality and line capacity, one critical influencing factor is bus stop capacity. This paper proposes a bus capacity estimation method incorporating diffusion approximation and queuing theory for individual bus stops. A concurrent queuing system between public transportation vehicles and passengers can be used to describe the scenario of a bus stop. For most of the queuing systems, the explicit distributions of basic characteristics (e.g., waiting time, queue length, and busy period) are difficult to obtain. Therefore, the diffusion approximation method was introduced to deal with this theoretical gap in this study. In this method, a continuous diffusion process was applied to estimate the discrete queuing process. The proposed model was validated using relevant data from seven bus stops. As a comparison, two common methods— Highway Capacity Manual (HCM) formula and M/M/S queuing model (i.e., Poisson arrivals, exponential distribution for bus service time, and S number of berths)—were used to estimate the capacity of the bus stop. The mean absolute percentage error (MAPE) of the diffusion approximation method is 7.12%, while the MAPEs of the HCM method and M/M/S queuing model are 16.53% and 10.23%, respectively. Therefore, the proposed model is more accurate and reliable than the others. In addition, the influences of traffic intensity, bus arrival rate, coefficient of variation of bus arrival headway, service time, coefficient of variation of service time, and the number of bus berths on the capacity of bus stops are explored by sensitivity analyses.

scholarly journals Optimal Planning for the Development of Power System in Respect to Distributed Generations Based on the Binary Dragonfly Algorithm

2020 ◽  
Vol 10 (14) ◽  
pp. 4795
Author(s):  
Mohammad Hossein Kakueinejad ◽  
Azim Heydari ◽  
Mostafa Askari ◽  
Farshid Keynia
Keyword(s):  
Distribution Network ◽  
Planning Problem ◽  
Distributed Generations ◽  
Dragonfly Algorithm ◽  
Expansion Planning ◽  
Optimal Network ◽  
Proposed Model ◽  
Solution Methods ◽  
Planning Methods ◽  
The Cost

With the increasing number of population and the rising demand for electricity, providing safe and secure energy to consumers is getting more and more important. Adding dispersed products to the distribution network is one of the key factors in achieving this goal. However, factors such as the amount of investment and the return on the investment on one side, and the power grid conditions, such as loss rates, voltage profiles, reliability, and maintenance costs, on the other hand, make it more vital to provide optimal annual planning methods concerning network development. Accordingly, in this paper, a multilevel method is presented for optimal network power expansion planning based on the binary dragonfly optimization algorithm, taking into account the distributed generation. The proposed objective function involves the minimization of the cost of investment, operation, repair, and the cost of reliability for the development of the network. The effectiveness of the proposed model to solve the multiyear network expansion planning problem is illustrated by applying them on the 33-bus distribution network and comparing the acquired results with the results of other solution methods such as GA, PSO, and TS.

scholarly journals Lane-Based Traffic Signal Simulation and Optimization for Preventing Overflow

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1368
Author(s):  
Chi-kwong Wong ◽  
Yiu-yin Lee
Keyword(s):  
Traffic Signal ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Design Constraint ◽  
Traffic Demand ◽  
Cycle Times ◽  
Simulation And Optimization ◽  
The Road ◽  
Proposed Model ◽  
Lane Based

In the lane-based signal optimization model, permitted turn directions in the form of lane markings that guide road users to turn at an intersection are optimized with traffic signal settings. The spatial queue requirements of approach lanes should be considered to avoid the overdesigning of the cycle, effective red, and effective green durations. The point-queue system employed in the conventional modeling approach is unrealistic in many practical situations. Overflow conditions cannot be modeled accurately, while vehicle queues are accumulated that block back upstream intersections. In a previous study, a method was developed to manually refine the traffic signal settings by using the results of lane-based optimization. However, the method was inefficient. In the present study, new design constraint sets are proposed to control the effective red and effective green durations, such that traffic enters the road lanes without overflow. The reduced cycle times discharge the accumulated vehicles more frequently. Moreover, queue spillback and residual queues can be avoided. One of the most complicated four-arm intersections in Hong Kong is considered as a case study for demonstration. The existing traffic signal settings are ineffective for controlling the observed traffic demand, and overflow occurs in short lanes. The optimized traffic signal settings applied to the proposed optimization algorithm effectively avoided traffic overflow. The resultant queuing dynamics are simulated using TRANSYT 15 Cell Transmission Model (CTM) to verify the proposed model. The model application is extended to handle the difficult residual queue scenario. It is found that the proposed model can optimize the traffic signal settings in cases where there are short initial residual queues.

scholarly journals Estimation of Origin-Destination Trip Matrices for Small Cities

2014 ◽  
Vol 26 (5) ◽  
pp. 419-428 ◽  
Author(s):  
Luka Novačko ◽  
Ljupko Šimunović ◽  
Davor Krasić
Keyword(s):  
Average Rate ◽  
Trip Generation ◽  
Small Cities ◽  
Traffic Demand ◽  
Step Model ◽  
Proposed Model ◽  
Data Assessment ◽  
Traffic Count ◽  
The Republic ◽  
Using Data

This paper presents a model of data assessment for the requirements of a classical four-step model of traffic demand in individual traffic in small cities. The procedure is carried out by creating an initial origin-destination trip matrix using data from the traffic count and by defining the average rate of trip generation within single households. The research applied fuzzy logic for the correction of the initial trip matrix. The paper also presents the recommendations for defining the borders of traffic zones, as well as the locations of traffic counts. A flowchart has been used to show a summarized presentation of the proposed model. In the last part of the paper the model was tested on an example of a smaller city in the Republic of Croatia.

scholarly journals Cross-Vendor and Cross-State Analysis of GPS Probe Data Latency

2018 ◽  
Vol 2672 (42) ◽  
pp. 180-191 ◽  
Author(s):  
Zhongxiang Wang ◽  
Masoud Hamedi ◽  
Elham Sharifi ◽  
Stanley Young
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Ground Truth ◽  
Traffic Information ◽  
Incident Detection ◽  
Dynamic Message Signs ◽  
Real Time Traffic ◽  
Outsourced Data ◽  
Message Signs

Crowd sourced GPS probe data have become a major source of real-time traffic information applications. In addition to traditional traveler advisory systems such as dynamic message signs (DMS) and 511 systems, probe data are being used for automatic incident detection, integrated corridor management (ICM), end of queue warning systems, and mobility-related smartphone applications. Several private sector vendors offer minute by minute network-wide travel time and speed probe data. The quality of such data in terms of deviation of the reported travel time and speeds from ground-truth has been extensively studied in recent years, and as a result concerns over the accuracy of probe data have mostly faded away. However, the latency of probe data—defined as the lag between the time at which disturbance in traffic speed is reported in the outsourced data feed, and the time at which the traffic is perturbed—has become a subject of interest. The extent of latency of probe data for real-time applications is critical, so it is important to have a good understanding of the amount of latency and its influencing factors. This paper uses high-quality independent Bluetooth/Wi-Fi re-identification data collected on multiple freeway segments in three different states, to measure the latency of the vehicle probe data provided by three major vendors. The statistical distribution of the latency and its sensitivity to speed slowdown and recovery periods are discussed.

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