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

Right Turn Split: A New Design To Alleviate Weaving On Arterial Streets

While weaving maneuvers occur on every type of roadway, most studies have focused on freeway maneuvers. Weaving occurring on non-freeway facilities, such as arterial streets, can cause significant operational problems. Arterial streets weaving typically occur when vehicles coming from a side street at an upstream intersection attempt to enter the main street from one side to reach access points on the opposite site at a downstream intersection by crossing one or more lanes. This dissertation investigates the type of problems occurring on arterial streets due to the weaving movements and recommends a new design to alleviate weaving on arterial streets. Firstly, the dissertation examined the different weaving movements occurring between two close-spaced intersections at two sites in Florida and explained the breakdown conditions caused by the weaving movements at the two sites. Secondly, the dissertation proposed a new design, Right Turn Split (RTS), to alleviate the delay caused by the weaving movements. The new design proposed separating the worst weaving movement entering the arterial from the other movements and providing a separate path for this movement. The new method is easy to implement and does not require much right of way. Thirdly, the dissertation compared two microscopic models, SimTraffic and VISSIM, to choose the most suitable model to be used to study the operational benefits of the RTS design. Based on the results of the comparison, it was decided to use SimTraffic for the analysis. Fourthly, the dissertation proposed a new calibration and validation procedure for microscopic simulation models. The procedure was applied on SimTraffic using the traffic data from the two studied sites. The proposed procedure appeared to be properly calibrating and validating the SimTraffic simulation model. Finally, the calibrated and validated model was used to study the operational benefits of the RTS design. Using a wide range of geometric and volume conditions, 729 before and after pairs were created to compare the delay of similar scenarios before and after applying the RTS design. The results were analyzed graphically and statistically. The findings of the analysis showed that the RTS design provided lower delay on the arterial street than the original conditions

Multi-resolution Modeling of Dynamic Signal Control on Urban Streets

Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures

Multi-resolution Modeling of Dynamic Signal Control on Urban Streets

Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures

Developing Emergency Preparedness Plans For Orlando International Airport (MCO) Using Microscopic Simulator WATSim

Emergency preparedness typically involves the preparation of detailed plans that can be implemented in response to a variety of possible emergencies or disruptions to the transportation system. One shortcoming of past response plans was that they were based on only rudimentary traffic analysis or in many cases none at all. With the advances in traffic simulation during the last decade, it is now possible to model many traffic problems, such as emergency management, signal control and testing of Intelligent Transportation System technologies. These problems are difficult to solve using the traditional tools, which are based on analytical methods. Therefore, emergency preparedness planning can greatly benefit from the use of micro-simulation models to evaluate the impacts of natural and man-made incidents and assess the effectiveness of various responses. This simulation based study assessed hypothetical emergency preparedness plans and what geometric and/or operational improvements need to be done in response to emergency incidents. A detailed framework outlining the model building, calibration and validation of the model using microscopic traffic simulation model WATSim (academic version) is provided. The Roadway network data consists of geometric layout of the network, number of lanes, intersection description which include the turning bays, signal timings, phasing sequence, turning movement information etc. The network in and around the OIA region is coded into WATSim with 3 main signalized intersections, 180 nodes and 235 links. The travel demand data includes the vehicle counts in each link of the network and was modeled as percentage turning count movements. After the OIA network was coded into WATSim, the road network was calibrated and validated for the peak hour mostly obtained from ADT with 8% K factor by comparing the simulated and actual link counts at 15 different key locations in the network and visual verification done. Ranges of scenarios were tested that includes security checkpoint, route diversion incase of incident in or near the airport and increasing demand on the network. Travel time, maximum queue length and delay were used as measures of effectiveness and the results tabulated. This research demonstrates the potential benefits of using microscopic simulation models when developing emergency preparedness strategies. In all 4 main Events were modeled and analyzed. In Event 1, occurrence of 15 minutes traffic incident on a section of South Access road was simulated and its impact on the network operations was studied. The averaged travel time under the incident duration to Side A was more than doubled (29 minutes, more than a 100% increase) compared to the base case and similarly that of Side B two and a half times more (23 minutes, also more than a 100% increase). The overall network performance in terms of delay was found to be 231.09 sec/veh. and baseline 198.9 sec/veh. In Event 2, two cases with and without traffic diversions were assumed and evaluated under 15 minutes traffic incident modeled at the same link and spot as in Event 1. It was assumed that information about the traffic incident was disseminated upstream of the incident 2 minutes after the incident had occurred. This scenario study demonstrated that on the average, 17% (4 minutes) to 41% (12 minutes) per vehicle of travel time savings are achieved when real-time traffic information was provided to 26% percent of the drivers diverted. The overall network performance in delay for this event was also found to improve significantly (166.92 sec/veh). These findings led to the conclusion that investment in ITS technologies that support dissemination of traffic information (such as Changeable Message Signs, Highway Advisory Radio, etc) would provide a great advantage in traffic management under emergency situations and road diversion strategies. Event 3 simulated a Security Check point. It was observed that on the average, travel times to Sides A and B was 3 and 5 minutes more respectively compared to its baseline. Averaged queue length of 650 feet and 890 feet worst case was observed. Event 4 determined when and where the network breaks down when loaded. Among 10 sets of demand created, the network appeared to be breaking down at 30% increase based on the network-wide delay and at 15% based on Level of Service (LOS). The 90% increase appeared to have the most effect on the network with a total network-wide delay close to 620 seconds per vehicle which is 3 and a half times compared to the baseline. Conclusions and future scope were provided to ensure continued safe and efficient traffic operations inside and outside the Orlando International Airport region and to support efficient and informed decision making in the face of emergency situations

Freeway lane-changing: some empirical findings

Lane changing activity is thought to play an important role in the capacity degradation of congested freeways. However, proofs of this negative impact are scarce due to the difficulties in obtaining suitable data. In this paper, the lane changing activity in the B-23 freeway accessing the city of Barcelona is analyzed. Lane changes (LC) were video recorded in six different stretches from where loop detector measurements were also available. The obtained database allowed finding a consistent relationship between LC activity and congestion. LC peaks in all analyzed sections when they become congested. This is particularly intense at the traffic breakdown, between congested and free flowing conditions. As an example, it is observed that LC activity peaks just downstream of a fixed bottleneck where free-flowing conditions are recovered. In addition, data show that the larger the lane changing rates, the smaller the maximum observable flows, supporting the hypothesis that LC is a key contributor to a capacity drop. In spite of all these findings, this research highlights the difficulty in obtaining a suitable database to definitively answer most of the research questions regarding freeway lane-changing. The spatial coverage of measurements is one of the major drawbacks. To this end, a careful planning of the data collection is necessary in order to obtain meaningful conclusions.Postprint (published version