Perimeter Control as an Alternative to Dedicated Bus Lanes: A Case Study

Dedicated bus lanes (DBLs) are a common traffic management strategy in cities as they improve the efficiency of the transit system by preventing buses from getting trapped in traffic jams. Nevertheless, DBLs also have certain disadvantages: they consume space, reduce available capacity for general traffic, and can thus lead to even more congested car traffic situations. It is appealing to find more efficient alternatives that maintain a sufficient network supply for general traffic while guaranteeing high commercial speeds for the bus system. This paper investigates whether perimeter control (gating) could be such an alternative to DBL strategies. This solution aims at controlling the traffic conditions of a given area by monitoring vehicle accumulations and adapting traffic signal parameters to reach the targeted conditions. If free-flow states can be maintained within the zone, then DBLs become superfluous. This hypothesis is examined through a simulation case study with an urban arterial acting as the targeted area. A dual-objective control approach was applied to allow for not only the vehicle accumulation inside the area but the queue lengths at its perimeter, thereby addressing one of the main issues associated with gating schemes. Due to the gating strategy, traffic performance in the arterial, measured through vehicle accumulation plus mean speed and density, improved significantly. Moreover, results showed that bus operations reach almost the same efficiency level when DBLs are replaced by perimeter control. Furthermore, the availability of an additional lane for general traffic in the control case significantly increased the arterial capacity for cars.

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Effectiveness of Predictive Weather-Related Active Transportation and Demand Management Strategies for Network Management

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2667-08 ◽

2017 ◽

Vol 2667 (1) ◽

pp. 71-87 ◽

Cited By ~ 3

Author(s):

Zihan Hong ◽

Hani S. Mahmassani ◽

Xiang Xu ◽

Archak Mittal ◽

Ying Chen ◽

...

Keyword(s):

Traffic Management ◽

Demand Management ◽

Management Strategies ◽

Weather Conditions ◽

Active Transportation ◽

Operational Conditions ◽

Traffic Conditions ◽

Adverse Weather ◽

Traffic Performance ◽

The Impact

This paper presents the development, implementation, and evaluation of predictive active transportation and demand management (ATDM) and weather-responsive traffic management (WRTM) strategies to support operations for weather-affected traffic conditions with traffic estimation and prediction system models. First, the problem is defined as a dynamic process of traffic system evolution under the impact of operational conditions and management strategies (interventions). A list of research questions to be addressed is provided. Second, a systematic framework for implementing and evaluating predictive weather-related ATDM strategies is illustrated. The framework consists of an offline model that simulates and evaluates the traffic operations and an online model that predicts traffic conditions and transits information to the offline model to generate or adjust traffic management strategies. Next, the detailed description and the logic design of ATDM and WRTM strategies to be evaluated are proposed. To determine effectiveness, the selection of strategy combination and sensitivity of operational features are assessed with a series of experiments implemented with a locally calibrated network in the Chicago, Illinois, area. The analysis results confirm the models’ ability to replicate observed traffic patterns and to evaluate the system performance across operational conditions. The results confirm the effectiveness of the predictive strategies tested in managing and improving traffic performance under adverse weather conditions. The results also verify that, with the appropriate operational settings and synergistic combination of strategies, weather-related ATDM strategies can generate maximal effectiveness to improve traffic performance.

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Analyzing Simulation-Based Active Traffic Management Impact on a Large-Scale Regional Network

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119845650 ◽

2019 ◽

Vol 2673 (8) ◽

pp. 638-647

Author(s):

Minha Lee ◽

Chenfeng Xiong ◽

Zheng Zhu ◽

Weiyi Zhou ◽

Lei Zhang

Keyword(s):

Traffic Management ◽

Large Scale ◽

Dynamic Traffic Assignment ◽

Management Strategies ◽

Ramp Metering ◽

Vast Number ◽

Traffic Conditions ◽

Road Systems ◽

Traffic Impacts

A vast number of real-time corridor management strategies have been introduced because the dynamics of traffic patterns and increased congestion result in challenging problems on road systems. Although these strategies can offer positive impacts on regional traffic, their evaluation tools are often limited to the scope of one specific corridor. To fill this gap, this study integrates a mesoscopic dynamic traffic assignment simulation model with an existing traffic-responsive ramp metering strategy. This integrated model is suitable for network-wide analysis and large-scale simulation of integrated corridor management strategies. The integrated modeling platform is demonstrated as a practice-ready tool. We present a case study that explores the benefits of metering control under various traffic conditions in a real-world network in Maryland. Both local and network-wide impacts are illustrated in the case study. This is one of the first attempts to simultaneously analyze network-wide traffic impacts and capture minute-by-minute demand–supply interactions under managed corridor strategies. The results indicate that ramp metering is beneficial even under non-recurrent traffic conditions at multiple spatial resolutions.

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A Study of Urban Traffic Management- A Case Study of Lagos State Traffic Management Authority

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.62-64.599 ◽

2009 ◽

Vol 62-64 ◽

pp. 599-605 ◽

Cited By ~ 1

Author(s):

E.I. Bello ◽

C.I. Usifo

Keyword(s):

Traffic Management ◽

Petroleum Products ◽

Urban Traffic ◽

Transit System ◽

The Road ◽

Lagos State ◽

Structure Strength ◽

Management Challenge ◽

Accident Statistics

Lagos state is the commercial and financial capital of Nigeria. It is a coastal city with a population of 12 million and covers 2000 square kilometers. The road network extends over 2700 km with a vehicle density of 740 vehicles per kilometer. It consumes over 85% of petroleum products imported into the country. It has no rail or sea mass transit system and all movements of people and goods are by road. This has created a major traffic Management challenge and government intervention is the establishment of the Lagos State Traffic Management Authority( LASTMA). To understand the structure, strength, and weaknesses of the authority, the enabling law and accident statistics, were obtained from the Authority, the Nigerian Police, and the Federal Road Safety Commission. Questionnaires were administered to drivers unions and the general public. The results were analyzed and it was discovered that conflicts across agencies, corruption and high handedness exist. It was also established that the authority has to a great extent succeeded in improving orderliness on Lagos roads. LASTMA needs to pursue an aggressive public enlightenment to change driver’s behaviors.

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Development and Evaluation of a Control System for Regional Traffic Management

Advances in Civil Engineering ◽

10.1155/2011/724897 ◽

2011 ◽

Vol 2011 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

John L. McLin ◽

William T. Scherer

Keyword(s):

Control System ◽

Traffic Control ◽

Traffic Congestion ◽

Traffic Management ◽

Performance Model ◽

Preliminary Evaluation ◽

Traffic Incidents ◽

Traffic Conditions ◽

Traffic Performance ◽

Traffic Control System

Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system using traffic microsimulation demonstrates that it has the potential to improve system conditions during traffic incidents. In addition, several enhancements were identified which will make the system more robust in a real traffic control setting. An assessment of the control system elements indicates that there are no substantial technical barriers in implementing this system in a large traffic network.

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Black Spot Identification and Audit Analysis for Heterogeneous Traffic Conditions in Hyderabad City � a Case Study

i-manager’s Journal on Structural Engineering ◽

10.26634/jste.4.3.3729 ◽

2015 ◽

Vol 4 (3) ◽

pp. 34-42

Author(s):

T. Sri Lakshmi Sowmya ◽

◽

A. Ramesh ◽

B.N.M. Rao ◽

M. Kumar ◽

...

Keyword(s):

Black Spot ◽

Heterogeneous Traffic ◽

Traffic Conditions

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Queue Length Forecasting in Complex Manufacturing Job Shops

Forecasting ◽

10.3390/forecast3020021 ◽

2021 ◽

Vol 3 (2) ◽

pp. 322-338

Author(s):

Marvin Carl May ◽

Alexander Albers ◽

Marc David Fischer ◽

Florian Mayerhofer ◽

Louis Schäfer ◽

...

Keyword(s):

Operations Management ◽

Queue Length ◽

Manufacturing Systems ◽

Production Control ◽

Data Sets ◽

Job Shops ◽

Static Data ◽

Queue Lengths ◽

Operational Excellence

Currently, manufacturing is characterized by increasing complexity both on the technical and organizational levels. Thus, more complex and intelligent production control methods are developed in order to remain competitive and achieve operational excellence. Operations management described early on the influence among target metrics, such as queuing times, queue length, and production speed. However, accurate predictions of queue lengths have long been overlooked as a means to better understanding manufacturing systems. In order to provide queue length forecasts, this paper introduced a methodology to identify queue lengths in retrospect based on transitional data, as well as a comparison of easy-to-deploy machine learning-based queue forecasting models. Forecasting, based on static data sets, as well as time series models can be shown to be successfully applied in an exemplary semiconductor case study. The main findings concluded that accurate queue length prediction, even with minimal available data, is feasible by applying a variety of techniques, which can enable further research and predictions.

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Evaluation of the Applicability of the Ramp Metering to a Freeway Using Microsimulation: A Case Study in Riyadh, Saudi Arabia

Applied Sciences ◽

10.3390/app9204406 ◽

2019 ◽

Vol 9 (20) ◽

pp. 4406

Author(s):

Seongkwan Lee ◽

Amr Shokri ◽

Abdullah Al-Mansour

Keyword(s):

Saudi Arabia ◽

Traffic Congestion ◽

Traffic Management ◽

Fixed Time ◽

Ramp Metering ◽

Traffic Data ◽

Geometrical Data ◽

Overall Performance ◽

Length Reduction

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.

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