Microscopic Simulation and Calibration of an Integrated Freeway and Toll Plaza Model

In this paper, the development of a microscopic simulation model of the New Jersey Turnpike (NJTPK) using Paramics microscopic simulation software is presented. The model is validated/calibrated using the detailed vehicle-by-vehicle toll data at each toll plaza in the NJTPK. The dataset includes the entry toll plaza, exit toll plaza, entry and exit times, entry and exit lanes, etc. for each vehicle. This dataset is used to extract the origin-destination demand matrices and individual vehicle travel times between each interchange. Toll plazas are the most important components of the NJTPK. However, the default toll plaza model in Paramics cannot fully model the complex lane changing and lane choice behavior at toll plazas. It is shown that the Application Programming Interface (API) of Paramics is required for this purpose. The detailed data are also used to validate the developed toll plaza model. TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 3 INTRODUCTION AND OBJECTIVES It is often very difficult to accurately estimate the impacts and benefits of operational strategies in complex transportation networks. Most of the macroscopic models are too aggregate to capture time-dependent changes in traffic patterns due to these operational strategies. Microscopic traffic simulation has thus been gaining popularity due to the ever-increasing computational power of modern workstations, and its ability to capture the time-dependent dynamics of traffic flow and demand. Paramics is a widely used microscopic traffic simulation tool. It has a large set of functionalities that can be used to simulate and evaluate various policies and control strategies and their effects on the transportation system, such as vehicle delays and emissions. The most important feature of Paramics is the ability of overriding or extending the default models such as car following, lane changing, route choice, etc. using its Application Programming Interface (API). This feature helps the modelers to incorporate customized functionalities and test their own models. The goal of this paper is to describe the development and validation/calibration efforts of an integrated freeway and toll plaza model of the New Jersey Turnpike (NJTPK). The developed model is an invaluable tool for conducting many analyses such as evaluation of traveler information systems, incident management strategies, the effect of changes to the infrastructure, and the impact of congestion pricing. However, due to the major role of the toll plazas in the operations of the overall system, a reliable model of the toll plaza operations is essential for building a valid network model of this facility. It is shown in this study that with the application of simple decision-making rules using the Paramics API, a more realistic toll plaza operation can be achieved First the methodology followed in the generation of the complete NJTPK network is explained. A description of the toll plaza and network modeling effort is presented next. The detailed description of the input data and the validation/calibration procedure are then presented. Finally, the validation and calibration results and the conclusions are presented. NETWORK CREATION The first step in the process of microscopic modeling of any transportation system is the preparation of a detailed geometry of the road network. However, obtaining and incorporating the correct geometric characteristics and the correct scale of a network is a demanding task. The level of difficulty of this task increases as the network size increases. The geometric details of NJTPK were obtained from TransCAD® built-in data files. TransCAD networks can be exported in the format of ArcView® shape files. “Shape to Paramics” (S2P), a software developed by Vehicle Intelligence and Transportation Analysis Laboratory at University of California, Santa Barbara, converts the ArcView shape files to Paramics network files (1, 2). In this study, S2P was used to create the basic network. Finally, additional corrections had to be made to ensure the accuracy of the network characteristics. The NJTPK network developed in Paramics consists of 4244 nodes, 8800 links, and 26 zones. The network includes 26 interchanges (entries and exits), each zone acting as an origin and a destination for each interchange. TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 4 TOLL PLAZA AND NETWORK MODEL Toll plazas on the NJTPK areas are not barrier toll plazas located en route, but they are located at separate areas where users enter or exit the freeway. This kind of toll plaza configuration does not impede the traffic flow on the freeway. However, they are important features of the network because they affect the travel times between origin and destination (OD) pairs. Therefore, it is essential to develop an accurate model of the toll plaza operations to obtain a realistic simulation model of the network. Literature Review of Toll Plaza Simulation Models Most of the microscopic simulation software packages including Paramics do not have a built-in toll plaza model. Some researchers have taken up the task of developing customized toll plaza simulation models. Al-Deek and Mohamed (3), Al-Deek et al (4), (5) developed a toll plaza simulation model for the Holland East toll plaza in Orange County, Florida for different lane configurations and vehicle characteristics. The model has various input variables such as approach speed, acceleration, deceleration, etc. and it generates various output variables such as throughput and delays. Chien et al. (6) investigated the effect of various lane configurations and the removal of toll plazas on the Garden State Parkway, New Jersey. For five toll plazas the optimal lane configuration was determined using a Paramics simulation model. The authors used the lane changing behavior that was provided by the default Paramics simulation package. Moreover, the toll plazas on the Garden State Parkway are barrier tollbooths (located on the freeway) and the complexity of lane changing is much less as compared to the toll plazas located on the NJTPK, where the toll plazas are not on the freeway. In other words, since most of the vehicles follow the same path after crossing the toll plaza, the lane changing behavior at the barrier toll plazas is not as complicated. (The effect of different paths on the lane changing behavior is explained in the Modeling Procedure section). Correa et al (7) implemented an object-oriented simulation model (TOLLSIM) of a toll plaza in MODSIM III simulation software. The lane choice is based on shortest queue at the toll booth lanes. Danko and Gulewicz (8) used a spreadsheet to model the toll plaza and calculate the throughput and queue length at the toll plaza. Burris and Hildebrand (9) created a discrete-event microscopic simulation model of a toll plaza to study the toll plaza at A. Murray MacKay Bridge at Halifax, Canada. The lane selection by a vehicle is based on a logistical routine, which is based on queue length, traffic volume, and proximity of the preferred payment-type lane. Ceballos and Curtis (10) used VISSIM simulation software to model the toll plazas and parking toll plazas and compared their results to multi-server queuing analysis. Astarita et al. (11) developed a microscopic simulation model of a toll plaza with a lane changing, car-following and a utility-based lane selection model. Although Paramics has some of the basic features that can be used to build a toll plaza model, additional work using the API had to be performed to represent toll plaza operations accurately. The novelty of this study can be summarized as follows: • Unlike other models presented in (3) and (7), the toll plaza model presented in this study is fully integrated with the freeway model. • It is not a set of barrier tollbooths but it is a stand-alone configuration at the exit or entry points. This type of configuration requires improved lane changing and merging logic. Toll Plaza Model Inputs In order to model the toll plaza in Paramics the necessary inputs are: TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 5 • Toll plaza geometry: Satellite pictures available on the Internet were used as overlays to procure the information about the number of lanes in the toll plazas and the geometry of each toll plaza area. • Toll plaza configuration: There are only two user and lane types at the NJTPK namely, the electronic toll collection (ETC), called E-ZPass and manual toll payment. The number of lanes dedicated for each payment type was obtained from the New Jersey Turnpike Authority (NJTA) staff. • Service time distribution at the toll plaza for each vehicle type: In the literature, there is very limited amount of information that distinguishes the entry and exit service times for toll plazas similar to NJTPK (12). Wilbur Smith Associates’ (13) study on the benefits of E-ZPass on the NJTPK prepared for the NJTA used different entry and exit service time. An entry service time for the cash users of around 4.0 seconds and exit service time of around 7.5 seconds were used as the mean service time, adapted from the study by Wilbur Smith Associates (13). The service time for each individual vehicle was randomly generated from a normal distribution with this mean service time. Most of the available studies in the literature specify only the mean of the service time (6), (10), (12), (13). Because the variance of service time is not available, a variance of 1.0 second was chosen arbitrarily in this study. Also, choosing a higher service time variance resulted in unrealistic (negative) service times. Modeling Procedure The toll plaza simulation model involves the following processes: Updating the Queue Lengths The queue length is updated at every time step for each lane in the toll plaza. In the case of cash users, the lane change decision depends to a large extent on the queue length. This assumption leads to the concept of perceived queue length when lane choice decisions are made. Lane Choice Decision of Vehicles The lane changing behavior at a toll plaza is complicated to simulate, more so if the number of service lanes is high and the lane configuration at the toll plaza does not clearly isolate the EZPass and the cash lanes. Also, the traffic flow at the toll plaza also influences the lane choice decisions. Lane Choice – Driver Behavior Mechanism: When the toll plazas are external to the freeway, the vehicles must be allowed to enter and exit the freeway in their intended direction of travel (northbound or southbound in the case of NJTPK). This requires a system of ramps at each toll plaza that should allow for movement in various directions, as shown in FIGURE 1. As a result of this configuration, the northbound or southbound users tend to choose the lanes closer to the median and eastbound users tend to choose lanes closer to the curb (See FIGURE 1). Paramics by default does not support this type of lane choice behavior, since it does not have a path-based route choice model. Instead, it uses a route choice model that is linkbased. It uses a lookup table that stores the cost involved in traversing each link. Vehicle routes are built up of the links based on this lookup table. Whereas, in reality drivers have an abstract idea of the route as a path connected by points, where a decision of which path to choose next is made (e.g., an intersection or a split). This behavior is illustrated in Oh et al. (14), Jayakrishnan et al. (15) in detail. Although, there is no specific reference to the lane choice at toll plazas in TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 6 current literature, the lane choice made by a driver, in general, is path-based. Hence, a path-based route choice model, which is similar to the process explained above, is more realistic and was employed in the model. The routing decision in Paramics is made two links ahead of the current link for each vehicle (14), (15). So, in the case where the network has short links (such as toll plaza links) the vehicles are not able to make realistic routing decisions. As a result, the appropriate lane decisions cannot be made at the intended point in time and space, which causes unrealistic delays.. An extended lane choice model at the toll plaza has to be incorporated using an API developed in the Paramics. Path-based Lane choice model: The need for a “path-based” approach in Paramics is mentioned in (14), (15). There is a way to circumvent the problem of memory and computational burden for the present case when using path-based approach. For the network under study, there is only one possible path between each OD pair (though there are few toll plazas where the passenger car users have the option of using either of the dual-dual roadway, this choice is not made immediately after the toll plaza and hence does not affect the lane choice at the toll plaza). Therefore, the paths for all OD pairs are fixed and need not be dynamically updated. In other words, there is only one location where the vehicles have to make lane choice based on their path. In this regard, a path matrix, which stores the information about the entry ramp that the user should take to reach his/her destination, is created. This concept is similar to the path dynamics approach used in several other studies (14), (15). The Path Matrix is an n x n matrix, where n is the number of zones, since the decision is made only at one location i.e. at the entry Toll Plaza. A value of 1 implies that the user has to be in a lane range closer to the median, –1 indicates that the user has to be closer to the curb, and a value of 0 indicates the user can choose any lane range. The lane choice models are implemented using Paramics API (16). TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 7 FIGURE 1 Path-based Lane Choice at the Toll Plaza and Links at the Toll Plaza. The assumptions of the model described below are similar to the ones used in (3), (4), (5), (8): • The primary assumption is that vehicles start making decisions about their path-based lane choices two links before the toll plaza link (see FIGURE 1). • For E-ZPass vehicles, if the difference in queue length between the “target” lane and the current lane is two vehicles or less, the user does not make a lane change to the target lane. Two vehicles can be called as the perceived queue for the driver, based on which lane changes and choices are made. • Also, it is assumed that E-ZPass users do not make lane changes that are more then 4 lanes away from the current lane, since the processing of queues in E-ZPass lanes is relatively fast. • In the case of the “path-based” model, in addition to the above assumptions, another assumption is that the user decides the lane range (based on the Path Matrix) in the first decision TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 8 link, and then decides which particular queue or lane to join in the second decision link. The flow chart of this decision process is shown in FIGURE 2. Danko and Gulewicz (8) used the General Purpose Simulation System to evaluate the optimal staffing requirements at a toll plaza. This study suggested that most drivers exit the plaza from the same side as they have entered. This indirectly substantiates the path-based lane choice at a toll plaza. FIGURE 2 Flow Chart of the Lane Changing Behavior. Processing of Vehicles The processing of vehicles in the toll plaza model is based on the service time, which is expressed as stop-time at the end of the toll plaza link (see FIGURE 1) for manual toll payment TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal. Ozbay, K., Mudigonda, S., Bartin, B. 9 vehicles at the location of the tollbooth. The E-ZPass vehicles would just pass through the tollbooth (at the end of the Toll Link) at a specified speed limit namely, 5 mph. Apart from the manual (cash) and electronic (E-ZPass) payment lanes, there are some mixed payment lanes at the NJTPK toll plazas. Paramics does not have the capability to model mixed-transaction type lanes. An API for the toll plaza model was coded to incorporate the mixed payment lanes. Also, Paramics Modeller has the capability for modeling only the uniformly distributed service times at the toll plaza (17). However, usually the service time distribution at the booths handled by human operators is a normal distribution (Al Deek and Mohamed (3) use an empirical distribution of observed service times at toll plazas in Florida, which is close to normal distribution). This API also incorporates the use of a normal distribution for the service times at toll plazas. It should be noted that in this particular effort of microscopic simulation, the aim was to model the vehicular traffic on the entire network of NJTPK (which, as stated above, is 150 miles long and consists of 52 toll plazas). Hence, not only the computational time for the simulation, but also the calibration involves high amount of time and effort. Also, the toll plazas constitute a small part of the simulation model of the network. The simulation of each of the 52 toll plazas to a very high degree of accuracy necessitates large amount resources for the purpose of field data collection, processing of the data and incorporating the resulting observations in the model. The refinement of the simulation model is an on-going process and will be performed for the future studies. Other Network Features Inclusion of “Cars Only” lanes From Interchange 8A to Interchange 14 the NJTPK is a dual-dual roadway. Namely, there are both inner (cars only) and outer (car, truck and bus) travel lanes in both the northbound and southbound directions. So, to model the “Cars Only” lanes, the truck route was changed to the alternate roadway when they are present on the “decision making” links. DESCRIPTION OF THE INPUT DATA AND CALIBRATION OF THE NETWORK MODEL