Network-wide safety impacts of dedicated lanes for connected and autonomous vehicles
Hua ShaMohit Kumar SinghRajae HaouariEvita PapazikouMohammed QuddusClaire QuigleyAmna ChaudhryPete ThomasWendy WeijermarsAndrew Morris
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Cooperative, Connected and Automated Mobility (CCAM) enabled by Connected and Autonomous Vehicles (CAVs) has potential to change future transport systems. The findings from previous studies suggest that these technologies will improve traffic flow, reduce travel time and delays. Furthermore, these CAVs will be safer compared to existing vehicles. As these vehicles may have the ability to travel at a higher speed and with shorter headways, it has been argued that infrastructure-based measures are required to optimise traffic flow and road user comfort. One of these measures is the use of a dedicated lane for CAVs on urban highways and arterials and constitutes the focus of this research. As the potential impact on safety is unclear, the present study aims to evaluate the safety impacts of dedicated lanes for CAVs. A calibrated and validated microsimulation model developed in AIMSUN was used to simulate and produce safety results. These results were analysed with the help of the Surrogate Safety Assessment Model (SSAM). The model includes human-driven vehicles (HDVs), 1st generation and 2nd generation autonomous vehicles (AVs) with different sets of parameters leading to different movement behaviour. The model uses a variety of cases in which a dedicated lane is provided at different type of lanes (inner and outer) of highways to understand the safety effects. The model also tries to understand the minimum required market penetration rate (MPR) of CAVs for a better movement of traffic on dedicated lanes. It was observed in the models that although at low penetration rates of CAVs (around 20%) dedicated lanes might not be advantageous, a reduction of 53% to 58% in traffic conflicts is achieved with the introduction of dedicated lanes in high CAV MPRs. In addition, traffic crashes estimated from traffic conflicts are reduced up to 48% with the CAVs. The simulation results revealed that with dedicated lane, the combination of 40-40-20 (i.e., 40% human-driven - 40% 1st generation AVs- 20% 2nd generation AVs) could be the optimum MPR for CAVs to achieve the best safety benefits. The findings in this study provide useful insight into the safety impacts of dedicated lanes for CAVs and could be used to develop a policy support tool for local authorities and practitioners.Keywords:
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Market Penetration
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This paper has set out to identify the changing values of capacities over time as applied to freeway traffic conditions. The paper examines capacity in the context of observed volumes to date from both an Australian and international experience. This paper then examines the car following algorithm in the VISSIM microsimulation software to benchmark the similarity of the maximum freeway capacity against these observed volumes. This review of existing literature was initially undertaken when developing a VISSIM microsimulation model to examine the application of forecast future year traffic volumes on a motorway network. Initial discussion queried the method that microsimulation software packages such as VISSIM use to determine capacity. Microsimulation packages are capacity oriented rather than demand focused. For this reason, microsimulation models are regularly applied to capacity constrained transport situations such as town centre and urban design studies. Existing publications exploring the research behind VISSIM examined the appropriateness of components in the algorithm to recreate traffic operations. However, there was little documentation to identify the midblock capacities represented with the car driver following model to simulate freeway conditions. This paper sets out to explore the maximum capacities that can be achieved when simulating freeway operations for both current and future year conditions. (a) For the covering entry of this conference, please see ITRD abstract no. E216058.
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Traffic microsimulation is increasingly a preferred method of traffic analysis for today's transportation professionals. The importance of properly calibrating these traffic simulations is evidenced by the adoption of microsimulation calibration standards by several state and federal transportation authorities. A component of the calibration process is the calibration of the simulation for capacity. Capacity is a high-level measurement that is a function of many lower level user-defined input parameters. VISSIM utilizes psychophysical car-following models that rely on ten user-defined parameters to represent freeway driving behavior. Several VISSIM driver behavior parameters have been shown to have a significant impact on roadway capacity. This paper seeks further understanding of the performance of the VISSIM traffic microsimulator by investigating the impact of driver behavior parameter combinations on a measure of freeway capacity. This paper is intended to provide insight useful for manual calibration of VISSIM microsimulation or the development of calibration algorithms
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Application of microsimulation models in traffic analysis is a common professional practice. Methodology of calibration of microsimulation models is not finally adopted and various approaches are available. One of the available calibration methods is neural network approach for calibration of microsimulation traffic model. The comparison of the simulated and measured traffic indicators, in real traffic conditions, provides the best insight into the success of the model calibration process. The traffic indicator, used for the calibration of the model, is the travel time between the measuring points at a chosen urban intersection. The calibrated model has predicted the travel time for new sets of measured data at the same intersection with the prediction error smaller than 5%. This paper analyses the simulation results for the traffic indicators that were not used in the model calibration – the queue parameters. The selected queue parameters are the maximum queue at the entrance and number of stops at the intersection entrance. The model has been additionally applied to the other intersection, in order to simulate its queue parameters. This has provided us with an insight into the issue of whether the calibration model is applicable only to the intersection for which the calibration has been done or it can have a wider application. The VISSIM microsimulation traffic model was used for calibration, and two single-lane roundabouts served as the research basis for evaluation of the calibrated traffic microsimulation model by means of queue parameters.
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Traffic microsimulation has a functional role in understanding the traffic performance on the road network. This study originated with intent to understand traffic microsimulation and its use in modeling connected and automated vehicles (CAVs). Initially, the paper focuses on understanding the evolution of traffic microsimulation and on examining the various commercial and open-source simulation platforms available and their importance in traffic microsimulation studies. Following this, current autonomous vehicle (AV) microsimulation strategies are reviewed. From the review analysis, it is observed that AVs are modeled in traffic microsimulation with two sets of strategies. In the first set, the inbuilt models are used to replicate the driving behavior of AVs by adapting the models’ parameters. In the second strategy, AV behavior is programmed with the help of externalities (e.g., Application Programming Interface (API)). Studies simulating AVs with inbuilt models used mostly VISSIM compared to other microsimulation platforms. In addition, the studies are heavily focused on AVs’ penetration rate impact on traffic flow characteristics and traffic safety. On the other hand, studies which simulated AVs with externalities focused on the communication aspects for traffic management. Finally, the cosimulation strategies for simulating the CAVs are explored, and the ongoing research attempts are discussed. The present study identifies the limitations of present CAV microsimulation studies and proposes prospects and improvements in modeling AVs in traffic microsimulation.
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Comprehensive analysis of traffic behavior requires continuous studies to develop traffic theories explaining that behavior at the microscopic level.The study aims to develop a microsimulation program to evaluate the freeway weaving performance depending on the observed data.FWASIM represents a microscopic analysis of the freeway traffic features.It scans events periodically.The developed FWASIM involves the formulation of driver and vehicle behavior at freeway link, on-ramp, off-ramp, and combine them to produce a flexible, friendly use simulation model.Its concept is mainly depending on the car following and lane change theories.Analytical model validation was conducted based on a comparison of FWASIM output with the VISSIM output.Tests consider the important factors that may affect the traffic behavior for a given segment configuration.The obtained results show agreement between FWASIM and VISSIM outputs.Besides, the field data were used to validate FWASIM.Graphical and t-test methods were used to examine the results.The results are statistically significant which implies that the model provides reasonably accurate measures of effectiveness for the validated range of input data.
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Microsimulation models are able to model the stochastic nature of traffic flow at the multi- modal level, through a detailed movement modeling of each entity and their interactions. The micro-simulation models are unquestionably a very useful tool, but it is questionable whether they can be expected to give realistic modeling results that can be applied in the methodology, analysis and design in local conditions. The aim of this study is to demonstrate that the selected VISSIM microsimulation model can provide realistic modeling results when the calibration of the model is done. In this paper, a comparison of simulation results obtained by calibrated and non-calibrated microsimulation traffic model with field data measured in real traffic conditions was made. As an experimental base was taken single-lane roundabout in the urban transport network of Osijek, and selected traffic indicators are travel time and the queue parameters.
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Traffic microsimulation is increasingly a preferred method of traffic analysis for today's transportation professionals. The importance of properly calibrating these traffic simulations is evidenced by the adoption of microsimulation calibration standards by several state and federal transportation authorities. A component of the calibration process is the calibration of the simulation for capacity. Capacity is a high-level measurement that is a function of many lower-level user-defined input parameters. VISSIM utilizes psy-chophysical car-following models that rely on ten user-defined parameters to represent freeway driving behavior. Several VISSIM driver behavior parameters have been shown to have a significant impact on roadway capacity. This paper seeks further understanding of the performance of the VISSIM traffic microsimulator by investigating the impact of driver behavior parameter combinations on a measure of freeway capacity. This paper is intended to provide insight useful for manual calibration of VISSIM microsimulation or the development of calibration algorithms.
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VISSIM Microsimulation has become increasingly popular for the detailed assessment of many forms of traffic impact related projects for all types of networks and in particular detailed traffic signal control schemes; familiar subjects being exit blocking, public transport and demand dependency, to name just a few. However, the functionality, available within microsimulation, ie the ability to program any kind of traffic signal controller operation, traffic control strategy or its system, enables greater confidence and scope by developing design solutions based upon detail and robust analysis. In addition, new modules and in particular, the provision of the COM interface has increased the range of schemes tailored for the software. This paper illustrates some examples of sophisticated applications of VISSIM, based on VAP (Vehicle Actuated Programming) and the COM interface. (A)
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Abstract Traffic simulation models are one of the most important tools that are widely used to analyse and manage transport systems. These tools are used to model complex traffic sites and evaluate various traffic alternatives and testing their effect prior to application in real sites. Median U- turn is an example of such complicated sites. There are many microsimulation tools such as VISSIM, ALIMSUN and PARAMICS. The goal of this study is to develop the simulation model of median U-turns and compares between VISSIM and PARAMICS models. The data were collect from two-selected site at Al-Diwaniyah city, Iraq. The data used in verification of the developed model represent the through traffic volumes and turning traffic volumes at both directions as well as the average queue length created at the U-turn site. The calibration and validation process of the developed models show that both VISSIM and PARAMICS models can provides reasonable approximation for real traffic at the selected site. Further research is needed to examine these tools based on additional sites and to apply such tools to examine different scenarios to enhance traffic conditions at U-turn sites.
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In the transition step to the near future where autonomous vehicles fill the highways, the autonomous vehicles’ successful implementation counts on knowledge about their interaction with conventional vehicles. Due to the lack of numbers of the autonomous vehicles on roadways, many transportation professionals depend on simulations in order to examine the coexistence of both vehicle types and their interaction in the circumstance of higher market penetration rates of the autonomous vehicles. In this study, VISSIM microscopic simulator is used for inspecting the autonomous vehicles interactions and assessing their impacts on traffic stream. A case study that evaluates the effects on vehicles throughput, delay, queue length, and safety at the highway work zone merging area is investigated. The simulation was generated the proximity of the Louis-Hippolyte La Fontaine tunnel, which connects Boucherville and Montreal island. To simulate coexist periods, the autonomous vehicles were put into the simulation with different penetration rates starting at 20% and increasing 20% for each scenario until reaching 80% of the rates of the autonomous vehicles. Furthermore, the safety impact of the autonomous vehicles in the matter of conflicts was studied using the Surrogate Safety Assessment Model (SSAM). The simulation results showed that the tunnel work zone’s capacity per lane was increased when CAVs were added to the simulation. The average vehicle delay did not improve a low CAV penetration rates. However, as CAVs account for more than 40% of the total passenger vehicles, the vehicle delay improved. The simulated model also showed that the average queue length increased with the increase of CAV in the traffic stream. Nonetheless, the conflict analysis results proved that CAVs can improve overall traffic safety at the work zone.
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