The Fixed-Cycle Traffic-Light queue with multiple lanes and temporary blockages

Traffic-light modelling is a complex task, because many factors have to be taken into account. In particular, capturing all traffic flows in one model can significantly complicate the model. Therefore, several realistic features are typically omitted from most models. We introduce a mechanism to include pedestrians and focus on situations where they may block vehicles that get a green light simultaneously. More specifically, we consider a generalization of the Fixed-Cycle Traffic-Light (FCTL) queue. Our framework allows us to model situations where (part of the) vehicles are blocked, e.g. by pedestrians that block turning traffic and where several vehicles might depart simultaneously, e.g. in case of multiple lanes receiving a green light simultaneously. We rely on probability generating function and complex analysis techniques which are also used to study the regular FCTL queue. We study the effect of several parameters on performance measures such as the mean delay and queue-length distribution

Modeling Capacity and Delay at Signalized Intersections with Channelized Right-turn Lanes Considering the Impact of Blockage

Right-turn channelization is used to improve the capacity at busy intersections with a lot of right-turns. However, under heavy traffic conditions the through lane vehicles might backup and block the right-turn lane. This will affect the discharge rate of right-turning vehicles and reduce the approach capacity and, consequently, increase the approach delay. So if the right-turn channelization is blocked frequently, its advantage is neglected and serious capacity problems can be overlooked. This issue is not addressed in the Highway Capacity Manual (HCM) and no separate model is provided to estimate the capacity and delay of approaches with channelized right-turn lanes. Using conventional methods for estimating the capacity and delay without considering the effect of potential blockage results in overestimation of the approach capacity and underestimation of the approach delay. This research presents probabilistic capacity and delay models for signalized intersections with channelized right-turn lanes considering the possibility of the right-turning vehicles being blocked from accessing the lane.The capacity model was developed by considering the capacity under blockage and non-blockage conditions with respect to the probability of blockage. Subsequently, a model was developed to estimate the probability of blockage. The capacity model is significantly affected by the length of the short-lane section and proportion of right-turn traffic. The proposed capacity model under blockage conditions and also the blockage probability model were validated through VISSIM, a microscopic simulation model. The validation process showed that both models are reliable. For operational purposes, the recommended lengths of the short-lane section were developed which would be useful in evaluating adequacy of the current lengths, identifying the options of extending the short-lane section length, or changing signal timing to reduce the likelihood of blockage. The recommended lengths were developed based on different signal timing plans and several proportions of right-turn traffic. The queue accumulation polygons (QAPs) were used to estimate the approach uniform delay and the HCM procedure was followed for the computation of the incremental delay caused by the random fluctuation of vehicle arrivals. To investigate the effect of blockage on the uniform delay, two different QAPs were developed associated with arrival scenarios under blockage and non-blockage conditions. The proposed delay model was also validated through VISSIM. It was found that, the proposed model can provide accurate estimates of the delay by reflecting the delay increase due to the right-turn channelization blockage. The results showed that the delay of an approach with a channelized right-turn is influenced by the length of the short-lane section and proportion of through and right-turn traffic

Traffic Simulation Model for Urban Networks: CTM-URBAN

Congestion on urban transportation networks around the world is frequently encountered and its economic and environmental footprint cannot be ignored. One of the solutions used to alleviate this problem is deployment of Intelligent Transportation Systems (ITS). The effectiveness of ITS solutions to manage traffic demand more efficiently relies heavily on accurate travel time prediction, which is a difficult task to achieve using currently available simulation methods. This study proposes an urban network simulation model named CTM-URBAN, a modified version of the Cell Transmission Method (CTM) which was originally developed to simulate highway traffic. CTM-URBAN is a simple and versatile simulation framework designed to simulate more realistically traffic flows in an urban network with various traffic control devices. CTM-URBAN allows building, calibrating, and maintaining a large simulation network with a minimum of effort. A case study is presented to demonstrate that CTM-URBAN is able to predict travel time through signal-controlled intersections more accurately than the original CTM based on comparison with results from a microscopic simulator

Simulating the Impact of Traffic Calming Strategies

This study assessed the impact of traffic calming measures to the speed, travel times and capacity of residential roadways. The study focused on two types of speed tables, speed humps and a raised crosswalk. A moving test vehicle equipped with GPS receivers that allowed calculation of speeds and determination of speed profiles at 1s intervals were used. Multi-regime model was used to provide the best fit using steady state equations; hence the corresponding speed-flow relationships were established for different calming scenarios. It was found that capacities of residential roadway segments due to presence of calming features ranged from 640 to 730 vph. However, the capacity varied with the spacing of the calming features in which spacing speed tables at 1050 ft apart caused a 23% reduction in capacity while 350-ft spacing reduced capacity by 32%. Analysis showed a linear decrease of capacity of approximately 20 vphpl, 37 vphpl and 34 vphpl when 17 ft wide speed tables were spaced at 350 ft, 700 ft, and 1050 ft apart respectively. For speed hump calming features, spacing humps at 350 ft reduced capacity by about 33% while a 700 ft spacing reduced capacity by 30%. The study concludes that speed tables are slightly better than speed humps in terms of preserving the roadway capacity. Also, traffic calming measures significantly reduce the speeds of vehicles, and it is best to keep spacing of 630 ft or less to achieve desirable crossing speeds of less or equal to 15 mph especially in a street with schools nearby. A microscopic simulation model was developed to replicate the driving behavior of traffic on urban road diets roads to analyze the influence of bus stops on traffic flow and safety. The impacts of safety were assessed using surrogate measures of safety (SSAM). The study found that presence of a bus stops for 10, 20 and 30 s dwell times have almost 9.5%, 12%, and 20% effect on traffic speed reductions when 300 veh/hr flow is considered. A comparison of reduction in speed of traffic on an 11 ft wide road lane of a road diet due to curbside stops and bus bays for a mean of 30s with a standard deviation of 5s dwell time case was conducted. Results showed that a bus stop bay with the stated bus dwell time causes an approximate 8% speed reduction to traffic at a flow level of about 1400 vph. Analysis of the trajectories from bust stop locations showed that at 0, 25, 50, 75, 100, 125, 150, and 175 feet from the intersection the number of conflicts is affected by the presence and location of a curbside stop on a segment with a road diet

AN INTEGRATED CONTROL MODEL FOR FREEWAY INTERCHANGES

This dissertation proposes an integrated control framework to deal with traffic congestion at freeway interchanges. In the neighborhood of freeway interchanges, there are six potential problems that could cause severe congestion, namely lane-blockage, link-blockage, green time starvation, on-ramp queue spillback to the upstream arterial, off-ramp queue spillback to the upstream freeway segments, and freeway mainline queue spillback to the upstream interchange. The congestion problem around freeway interchanges cannot be solved separately either on the freeways or on the arterials side. To eliminate this congestion, we should balance the delays of freeways and arterials and improve the overall system performance instead of individual subsystem performance. This dissertation proposes an integrated framework which handles interchange congestion according to its severity level with different models. These models can generate effective control strategies to achieve near optimal system performance by balancing the freeway and arterial delays. The following key contributions were made in this dissertation: 1. Formulated the lane-blockage problem between the movements of an arterial intersection approach as an linear program with the proposed sub-cell concept, and proposed an arterial signal optimization model under oversaturated traffic conditions; 2. Formulated the traffic dynamics of a freeway segment with cell-transmission concept, while considering the exit queue effects on its neighboring through lane traffic with the proposed capacity model, which is able to take the lateral friction into account; 3. Developed an integrated control model for multiple freeway interchanges, which can capture the off-ramp spillback, freeway mainline spillback, and arterial lane and link blockage simultaneously; 4. Explored the effectiveness of different solution algorithms (GA, SA, and SA-GA) for the proposed integrated control models, and conducted a statistical goodness check for the proposed algorithms, which has demonstrated the advantages of the proposed model; 5. Conducted intensive numerical experiments for the proposed control models, and compared the performance of the optimized signal timings from the proposed models with those from Transyt-7F by CORSIM simulations. These comparisons have demonstrated the advantages of the proposed models, especially under oversaturated traffic conditions

Integrated Special Event Traffic Management Strategies in Urban Transportation Network

How to effectively optimize and control spreading traffic in urban network during the special event has emerged as one of the critical issues faced by many transportation professionals in the past several decades due to the surging demand and the often limited network capacity. The contribution of this dissertation is to develop a set of integrated mathematical programming models for unconventional traffic management of special events in urban transportation network. Traffic management strategies such as lane reorganization and reversal, turning restriction, lane-based signal timing, ramp closure, and uninterrupted flow intersection will be coordinated and concurrently optimized for best overall system performance. Considering the complexity of the proposed formulations and the concerns of computing efficiency, this study has also developed efficient solution heuristics that can yield sufficiently reliable solutions for real-world application. Case studies and extensive numerical analyses results validate the effectiveness and applicability of the proposed models

A dynamic traffic assignment model for highly congested urban networks

The management of severe congestion in complex urban networks calls for dynamic traffic assignment (DTA) models that can replicate real traffic situations with long queues and spillbacks. DynaMIT-P, a mesoscopic traffic simulation system, was enhanced and calibrated to capture the traffic characteristics in a sub-area of Beijing, China. The network had 1698 nodes and 3180 directed links in an area of around 18 square miles. There were 2927 non-zero origin–destination (OD) pairs and around 630,000 vehicles were simulated over 4 h of the morning peak. All demand and supply parameters were calibrated simultaneously using sensor counts and floating car travel time data. Successful calibration was achieved with the Path-size Logit route choice model, which accounted for overlapping routes. Furthermore, explicit representations of lane groups were required to properly model traffic delays and queues. A modified treatment of acceptance capacity was required to model the large number of short links in the transportation network (close to the length of one vehicle). In addition, even though bicycles and pedestrians were not explicitly modeled, their impacts on auto traffic were captured by dynamic road segment capacities.Beijing Transportation Research Cente

Case Studies to Develop a Highway-Rail Grade Crossing Analysis Framework Using Microsimulation

693JJ621C000017There are approximately 126,700 highway-rail at-grade crossings in the U.S. A portion of those involve high-volume public streets where crossing events result in measurable traffic backups and delays to the extent that mitigation efforts are needed. Conventional traffic analysis methods such as those in the Highway Capacity Manual are limited in their ability to quantify the impacts of traffic interruptions due to a train crossing. Microscopic traffic simulation methods are capable of analyzing these events and simulation software has been a part of the practitioner\u2019s toolbox now for 30 years. However, there has been no technical guidance nor consistency on how these tools should be applied to evaluate crossing events. Using microscopic simulation, researchers performed two case studies from which a framework has been developed that can be used by practitioners and decision makers for performing traffic operations analyses of at-grade crossings. The framework offers guidance for a consistent approach to the development and application of such models