A micro-simulation study on proactive coordinated ramp metering for relieving freeway congestion

2016 ◽  
Vol 43 (7) ◽  
pp. 599-608 ◽  
Author(s):  
Xu Wang ◽  
Tony Z. Qiu ◽  
Lei Niu ◽  
Ruhua Zhang ◽  
Lu Wang

To relieve freeway congestion during peak periods, ramp metering (RM) is often implemented to control the input flow from onramps on freeways. Many studies focus on proactive coordinated RM controls; however, successful implementation of proactive RM control still requires a more accurate prediction model and a less complex control algorithm. To this end, this study tests a proactive RM approach in micro-simulation, with goals to improve network-wide travel time and traffic flow. A METANET-based dynamic traffic model was adopted as a prediction model within a predictive control framework. The evaluation revealed a 6.50% amelioration in total travel time on the mainline and a 2.52% reduction of total time spent in the network. The applied algorithm was compared with the HERO algorithm and implemented in various peak demand scenarios. This analysis could lead to efficient and effective field applications of proactive coordinated RM control to improve freeway operation.

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hari Hara Sharan Nagalur Subraveti ◽  
Victor L. Knoop ◽  
Bart van Arem

Control measures at merging locations aimed at either the mainline traffic or on-ramp traffic do not lead to a fairness in the distribution of total delay across the two streams. This paper presents a control strategy of combining a lane change control with a ramp metering system at motorway merges. The control strategy presents the opportunity to control the delays incurred at the two traffic streams of the merge. An optimization problem is formulated for a multilane motorway with an on-ramp with the aim to minimize the total travel time of the system. The proposed strategy is tested using an incentive-based lane-specific traffic flow model. Results revealed a 17% reduction in the total travel time due to the proposed strategy. Moreover, it was shown that the distribution of delays over the mainline and on-ramp could be controlled via the proposed strategy. The performance of the combined control was also compared to the individual control measures. It was observed that the individual control measures (lane change only and ramp metering only) lead to high delays on either the mainline or on-ramp compared to the combined control, where the balance between the delay for the drivers on the mainline and on-ramp could be regulated. The combined lane change and ramp metering control presents opportunities for the road authorities to manage the total delay distribution across the two traffic streams.


Author(s):  
Cynthia Taylor ◽  
Deirdere Meldrum ◽  
Les Jacobson

A fuzzy logic ramp-metering algorithm was designed to overcome the limitations of conventional ramp-metering strategies. The fuzzy controller demonstrated improved robustness, prevented heavy congestion, intelligently balanced conflicting needs, and tuned easily. The objective was to maximize total distance traveled and minimize total travel time and vehicle delay, while maintaining acceptable ramp queues. A multiple-ramp study site from the Seattle I-5 corridor was modeled and tested using the freeway simulation software, FRESIM. For five of the six testing sets, encompassing a variety of traffic conditions, the fuzzy controller outperformed the three other controllers tested.


1998 ◽  
Vol 1645 (1) ◽  
pp. 152-159
Author(s):  
Bruce N. Janson

Whether freeway ramp metering can reduce total travel time in a corridor of several alternative routes depends on changes in route volumes and travel times. Ramp metering effectiveness and ramp metering algorithms have been evaluated mainly on the basis of improved freeway operations. Most studies have not evaluated the impact on alternative routes because of the complexity of the problem (e.g., which routes and what lengths of routes should be studied). An analysis of ramp metering impact in a network corridor is presented, first for simple steady-state cases and then for more complex cases involving time-varying demand, upstream and downstream queueing on freeway and alternative routes, and variable ramp metering rates based on freeway conditions. Time-varying examples are solved with a dynamic traffic assignment model called DYMOD. The analysis shows that ramp metering yields total travel time savings if (a) downstream freeway capacities are sufficiently restrictive, and (b) competitive alternative routes exist to accommodate the diverted traffic. The conditions under which ramp metering can be effective is illustrated by an examination of these simplified cases, and a useful modeling approach to analyzing systemwide impact in a larger corridor is demonstrated.


Author(s):  
Eun Hak Lee ◽  
Kyoungtae Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho

As the share of public transport increases, the express strategy of the urban railway is regarded as one of the solutions that allow the public transportation system to operate efficiently. It is crucial to express the urban railway’s express strategy to balance a passenger load between the two types of trains, that is, local and express trains. This research aims to estimate passengers’ preference between local and express trains based on a machine learning technique. Extreme gradient boosting (XGBoost) is trained to model express train preference using smart card and train log data. The passengers are categorized into four types according to their preference for the local and express trains. The smart card data and train log data of Metro Line 9 in Seoul are combined to generate the individual trip chain alternatives for each passenger. With the dataset, the train preference is estimated by XGBoost, and Shapley additive explanations (SHAP) is used to interpret and analyze the importance of individual features. The overall F1 score of the model is estimated to be 0.982. The results of feature analysis show that the total travel time of the local train feature is found to substantially affect the probability of express train preference with a 1.871 SHAP value. As a result, the probability of the express train preference increases with longer total travel time, shorter in-vehicle time, shorter waiting time, and few transfers on the passenger’s route. The model shows notable performance in accuracy and provided an understanding of the estimation results.


2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Chao Lu ◽  
Yanan Zhao ◽  
Jianwei Gong

Reinforcement learning (RL) has shown great potential for motorway ramp control, especially under the congestion caused by incidents. However, existing applications limited to single-agent tasks and based onQ-learning have inherent drawbacks for dealing with coordinated ramp control problems. For solving these problems, a Dyna-Qbased multiagent reinforcement learning (MARL) system named Dyna-MARL has been developed in this paper. Dyna-Qis an extension ofQ-learning, which combines model-free and model-based methods to obtain benefits from both sides. The performance of Dyna-MARL is tested in a simulated motorway segment in the UK with the real traffic data collected from AM peak hours. The test results compared with Isolated RL and noncontrolled situations show that Dyna-MARL can achieve a superior performance on improving the traffic operation with respect to increasing total throughput, reducing total travel time and CO2emission. Moreover, with a suitable coordination strategy, Dyna-MARL can maintain a highly equitable motorway system by balancing the travel time of road users from different on-ramps.


2021 ◽  
Vol 35 (09) ◽  
pp. 2150153
Author(s):  
Minghui Ma ◽  
Yaozong Zhang ◽  
Shidong Liang

The vehicle exhaust has been one of the major sources of greenhouse gas emissions. With an increase in traffic volume, it has been found that the introduced intelligent traffic control is necessary. This paper investigated a novel VSL strategy considering the dynamic control cycle to improve the traffic efficiency and environmental benefit on freeway. An extension of the cell transmission model (CTM) was used to depict the traffic characteristics under VSL control, and integrated with the microscopic emission and fuel consumption model VT-Micro to estimate the pollution emission of each cell. The VSL strategy was designed to provide multiple control cycles with different length to adjust the scope of VSL changes, furthermore, a probability formula was developed and used to determine the optimal quantity of control cycles to reduce the computational complexity of controller. An objective optimization function was formulated with the aim of minimizing total travel time and CO emission. With simulation experiments, the results showed that the proposed VSL strategy considering the dynamic control cycle outperformed uncontrolled scenario, resulting in up to 8.4% of total travel time reductions, 26.7% of delay optimization, and 14.5% reduction in CO emission, which enhanced the service level of freeway network.


Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.


2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Qinrui Tang ◽  
Bernhard Friedrich

Urban road networks may benefit from left turn prohibition at signalized intersections regarding capacity, for particular traffic demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. With the flows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length, and the green durations using a stage-based method which can handle the case that stages are sharing movements. The final output is a list of the prohibited left turns in the network and a new signal timing plan for every intersection. The optimal list of prohibited left turns was found using a genetic algorithm, and a combination of several algorithms was employed for the signal timing plan. The results show that left turn prohibition may lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered on a par with other left turn treatment options.


2020 ◽  
Vol 3 (4) ◽  
pp. 1305
Author(s):  
Gerwyn Persulessy ◽  
Basuki Anondho

Development of high-level building construction projects that require complex equipment that can be used in high-level construction, equipment used to help complete construction projects called heavy equipment. One of the heavy equipment used in high-rise buildings is a tower crane. The use and layout of tower cranes can speed up the schedule and save on project costs. Therefore many methods have been developed to determine the tower crane layout. This study will discuss determining the location of tower cranes by discussing simulations. The location will be determined based on the site map data which is processed in the form of a geometric arrangement and tower crane data specifications. Location determination is done by comparing the total travel time of several simulated locations according to several different speed criteria in a construction project. Speed criteria are divided into four times the jib speed and trolley speed. Location of the location with the total travel time will be taken as the final result. Different speed criteria will make the total travel time change. ABSTRAKPerkembangan proyek pembangunan gedung bertingkat tinggi yang semakin kompleks menyebabkan diperlukannya peralatan yang dapat mempermudah pembangunan gedung bertingkat, peralatan yang digunakan untuk membantu menyelesaikan tugas konstruksi disebut alat berat. Salah satu peralatan berat yang digunakan pada gedung bertingkat tinggi adalah tower crane. Penggunaan dan tata letak tower crane yang baik dapat mempercepat jadwal dan menghemat biaya proyek. Oleh karena itu banyak dikembangkan metode-metode untuk menentukan tata letak tower crane. Penelitian ini akan membahas penetapan letak lokasi tower crane dengan pendekatan  simulasi. Letak lokasi akan ditetapkan berdasarkan data site map yang diolah dalam bentuk geometric layout dan data spesifikasi tower crane. Penetapan lokasi dilakukan dengan cara membandingkan total travel time dari beberapa lokasi yang disimulasi sesuai dengan beberapa kriteria kecepatan yang berbeda-beda pada suatu proyek konstruksi. Kriteria kecepatan terbagi menjadi empat berdasarkan besarnya kecepatan jib dan kecepatan trolley. Letak lokasi dengan total travel time terkecil akan diambil sebagai hasil akhir. Kriteria-kriteria kecepatan yang berbeda disimulasi akan membuat total travel time berubah.


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