Traffic congestion

Lately, the attractiveness of cities has contributed to a rise in vehicle movements to and from cities. The growth of freight movements in cities predictably will be one of the critical issues of the near future. Congestion caused by the increased movements of freight impacts the flow of private and transit vehicles. Thus, it is crucial to reduce the congestion on multimodal corridors. Components of the Intelligent Transportation System (ITS) such as Freight Signal Priority (FSP) and Transit Signal Priority (TSP) that promote the freight and transit vehicles may not only help solve these conditions but may assist with the sustainability of the system. The primary objective of this research is to develop guidelines for traffic agencies to implement signal priorities based on identified decision factors on certain corridors. Besides, this study evaluates the efficiency of FSP and TSP in improving the performance of freight and transit systems. Finally, inclusive guidelines are drawn up based on the literature and the conducted simulation. The developed guidelines apply to corridors where freight delay plays a vital role in the assessment of corridor benefits.

Traffic congestion is one of the most concerning issues in the transportation system. Recurrent congestion and non-recurrent congestion are explored in this research. This research will investigate one of the most concerning issues with the transportation system, congestion, using an overall delay analysis study. A developed fused database program was used to access and analyze the complete database data. Two online databases were used for obtaining traffic, incident and weather data. Eleven different scenarios such as peak-hours, rain scenario, incidents scenario, and work zone scenario were developed for the analysis. An overall delay study was performed on all
scenarios to find the impact recurring and non-recurring congestion on the highway. The results of this research were interesting for future adjustment and improvements on the two segments of highways selected.

Exclusive bus lanes and the Transit Signal Priority are often not effective in saturated peak-traffic conditions. An alternative way of providing priority for transit can be queue jumpers, which allows buses to bypass and then cut out in front of waiting queue by getting an early green signal. Utah Transit authority deployed Bus Rapid Transit system at Salt Lake County, Utah along W 3500 S. This research evaluates the impacts of queue jumpers with TSP on Bus Rapid Transit (BRT) and private vehicular traffic. Four VISSIM models were developed for analysis : Basic scenario, no TSP with queue jumpers, TSP with no queue jumbers, and TSP with queue jumpers. In TQ scenario travel time was reduced between 13.2-19.82% with respect to basic scenario. At the same time, travel time of private traffic increased very little 0.38-3.28%. Two TSP strategies : green extension and red truncation are implemented in this research work.

This study describes analytical model as one innovative way to simulate Light Rail Transit (LRT) operations and calculate vehicular, transit and person delays at LRT crossings through Microsoft Excel. Analytical model emulates LRT trajectories from field and use these trajectories to clearly define train and car phases through Visual Basic for Applications (VBA) logic, which is part of analytical model. Simulation of train trajectories and calculations of delays were done for different LRT strategies and estimated roadway condition, Testing and validation of analytical model were performed in one case study in Salt Lake City (UT). Results show that analytical model is capable of emulating LRT trajectories and estimating delay at isolated LRT crossing. However, analytical model is not capable of simulating different train strategies at two or more LRT crossings, at the same time. Finally, extracted strategy provides savings from $100.000 to $200.000 in study area, on annual basis for projected year.

We propose a distributed, collaborative traffic congestion detection and dissemination system using VANET that makes efficient use of the communication channel, maintains location privacy, and provides drivers with real-time information on traffic congestions over long distances. The system uses vehicles themselves, equipped with simple inexpensive devices, as gatherers and distributors of information without the need for costly road infrastructure such as sensors, cameras or external communication equipment. Additionally, we present a flexible simulation and visualization framework we designed and developed to validate our system by showing its effectiveness in multiple scenarios and to aid in the research and development of this and future VANET applications.