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The gradual deployment of Connected and Automated Vehicles (CAV) in traffic will result in a transition period in which vehicles with various levels of automation and connectivity will have to co-exist with non-connected and non-automated road users for quite some time. Consequently, new types of interactions will emerge (and old types of interactions are likely to become more complicated) between vehicles at different levels of automation and other road users which could have significant implications on traffic safety and efficiency. Understanding the nature of these interactions, how humans might adapt their behavior, how connectivity can be utilized to proactively enhance drivers char63 driving performance, and how automated vehicles can be programmed to behave in different driving situations to guarantee safety and efficiency remain among the key knowledge gaps that require scientific research. This knowledge is crucial for the development of adequate integration policies of connected and automated vehicles in mixed traffic environment, for updating and improving automated vehicles char63 algorithms and software, for designing the physical and digital road infrastructure, and for operating and managing traffic on the road network.

The gradual deployment of automated vehicles on the existing road network will lead to a long transition period in which vehicles at different driving automation levels and capabilities will share the road with human driven vehicles, resulting into what is known as mixed traffic. Whether our road infrastructure is ready to safely and efficiently accommodate this mixed traffic remains a knowledge gap. Microscopic traffic simulation provides a proactive approach for assessing these implications. However, differences in assumptions regarding modeling automated driving in current simulation studies, and the use of different terminology make it difficult to compare the results of these studies. Therefore, the aim of this study is to specify the aspects to consider for modeling automated driving in microscopic traffic simulations using harmonized concepts, to investigate how both empirical studies and microscopic traffic simulation studies on automated driving have considered the proposed aspects, and to identify the state of the practice and the research needs to further improve the modeling of automated driving. Six important aspects were identified: the role of authorities, the role of users, the vehicle system, the perception of surroundings based on the vehicle’s sensors, the vehicle connectivity features, and the role of the infrastructure both physical and digital. The research gaps and research directions in relation to these aspects are identified and proposed, these might bring great benefits for the development of more accurate and realistic modeling of automated driving in microscopic traffic simulations.

Microscopic traffic simulation is a useful tool for the planning of motorized traffic, yet bicycle traffic still lacks this type of modeling support. Nonetheless, certain microscopic traffic simulators, such as Vissim, model bicycle traffic by applying models originally designed for car traffic. The gradient of a bicycle path has a significant impact on the speed of cyclists; therefore, this impact should be captured in microscopic traffic simulation. We investigate two calibration approaches to reproduce the effect of gradient on the speed of cyclists using the default driver behavioral model in Vissim. The first approach is to modify the simulated gradient to represent different values of the gradient-acceleration parameter: a fixed value that represents a decrease in the maximum acceleration that cyclists can apply on an uphill. The second approach is to adjust the maximum-acceleration function. We evaluate both approaches by applying a Vissim model of a bidirectional bicycle path with a 3% gradient in Stockholm. The results show that the current default implementation in the Vissim model underestimates the effect of gradient on speed. Moreover, the gradient-acceleration parameter does not directly reduce the maximum acceleration of all cyclists, but only of those cyclists riding above a certain speed. We conclude that by using a higher gradient-acceleration value than the default, we accurately estimate the observed mean speed on the uphill. However, neither of the investigated calibration approaches provides accurate estimates of the speed distributions. We emphasize the need for developing more accurate behavioral models designed for cyclists.

Studies of bicycle traffic characteristics are essential for understanding bicyclist behavior and developing suitable microscopic models for traffic simulation. Based on empirical data on real-world bicycle traffic, obtained through video-based data collection techniques, we describe characteristics of free-riding, following, and overtaking that facilitate the simulation of bidirectional bicycle traffic. In total, we analyze data from 195 605 bicyclists across seven bicycle paths in Sweden, with five located in Stockholm and two in Gothenburg. The analysis reveals multimodal distributions of speed and lateral position due to the distinct preferences of bicyclists that vary according to the type of bicycle used. Moreover, speeds are generally highest during morning rush hours at the locations under investigation. Based on wind measurements, we conclude that there is no statistically significant effect on mean free speed from wind speeds in the range of ±3 m/s. The distribution of speed differences between bicyclists at overtakings indicates a broad range of speed disparities among bicyclists, and is significantly influenced by infrastructure design. Furthermore, infrastructure design (path width, horizontal alignment, and presence of fixed objects along the edge) and traffic volumes significantly lateral positioning. Our results demonstrate the inherent heterogeneity in the characteristics of bicyclists, underscoring the need to advance modeling to incorporate these distinct characteristics into microscopic traffic simulation.

•An approach to scale up the impacts of Intelligent Transport Systems is developed.•The approach uses scenario-building and micro-simulation.•Application to eco-driving systems shows that it is possible to scale up local results to the European level.•Scaling up provides useful results for (policy) decision making.•Data availability is a key issue in scaling up.

“Automation-ready” is currently defined in the H2020 CoEXist project as the capability to conduct transport and infrastructure planning with the incorporation of connected and automated vehicles (CAV) in the same comprehensive manner as for existing modes in future plans, where they complement and coexist with conventional vehicles, public transport, pedestrians and cyclists, to achieve and support higher sustainable mobility goals. This definition will be fine-tuned through stakeholder engagement processes. The H2020 CoEXist project started in May 2017 and will run until April 2020. This paper introduces this project and covers its progress until January 2018, with a focus on the methodology of the “Automation-ready framework” that provides a planning framework for urban road authorities to prepare for the introduction of CAVs on the road network. The two Stuttgart use cases (among the eight use cases in CoEXist) are also elaborated in this paper. The framework includes elements about strategic urban mobility planning for CAVs and a clear guide for urban transport planners with a list of concrete actions that cities can do now to plan for CAVs on their road network.

The rapid growth of traffic congestion has led to an increased level of emissions and energy consumption in urban areas. Well designed infrastructure and traffic controllers along with more efficient vehicles and policy measures are required to mitigate congestion and thus reduce transport emissions. In order to evaluate how changes in the traffic system affect energy use and emissions, traffic analysis tools are used together with emission models. In large urban areas emission models mainly rely on aggregated outputs from traffic models, such as the average link speed and flow. Static traffic models are commonly used to generate inputs for emission models, since they can efficiently be applied to larger areas with relatively low computational cost. However, in some cases their underlying assumptions can lead to inaccurate predictions of the traffic conditions and hence to unreliable emission estimates. The aim of this paper is to investigate and quantify the errors that static modeling introduces in emission estimation and subsequently considering the source of those errors, to suggest and evaluate possible solutions. The long analysis periods that are commonly used in static models, as well as the static models’ inability to describe dynamic traffic flow phenomena can lead up to 40 % underestimation of the estimated emissions. In order to better estimate the total emissions, we propose the development of a post processing technique based on a quasi-dynamic approach, attempting to capture more of the excess emissions created by the temporal and spatial variations of traffic conditions.

Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles (AV) are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about the driving environment. Studies have proved that automated driving have the potential to decrease traffic congestion by reducing the time headway (THW), enhancing the traffic capacity and improving the safety margins in car following. Despite different encouraging factors, automated driving raise some concerns such as possible loss of situation awareness, overreliance on automation and system failure. This paper aims to investigate the effects of AV on driver’s behavior and traffic performance. A literature review was conducted to examine the AV effects on driver’s behavior. Findings from the literature survey reveal that conventional vehicles (CV), i.e. human driven, which are driving close to a platoon of AV with short THW, tend to reduce their THW and spend more time under their critical THW. Additionally, driving highly AV reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of AV on traffic performance, a simulation case study consisting of a 100% AV scenario and a 100% CV scenario was performed using microscopic traffic simulation. Outputs of this simulation study reveal that the positive effects of AV on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably improved by 8.09% during p.m. peak hours in the AV scenario, while the average travel speed enhanced relatively by 8.48%. As a consequent, the average travel time improved by 9.00% in the AV scenario. The outcome of this study jointly with the previous driving simulator studies illustrates a successful practice of microscopic traffic simulation to investigate the effects of AV. However, further development of the microscopic traffic simulation models are required and further investigations of mixed traffic situation with AV and CV need to be conducted.

This paper presents an investigation of capacity reduction in connection with roadwork. The paper presents a state-of-the-art description on roadwork effects on capacity. The state-of-the art has been used to develop a model for estimation of capacity reduction at roadwork zone on Swedish roads. The model has partly been validated with empirical data from a full scale test at the freeway network in Gothenburg. The studies presented in the literature shows that capacity differs not only between different roadwork designs but also between roadwork with similar design. Thus, one can conclude that there is a high variation between the roadwork zone due to effects of surrounding elements, such as the type of work and external effects such as rain (which affects the capacity even under normal conditions). The differences that exist in the estimation of capacity for motorway sections next to a roadwork zone can be said to consist of four situation-specific variables. These four variables are: the percentage of heavy vehicles, type of road, the width of the remaining lanes and diversion of traffic to the opposite carriageway. An increasing proportion of heavy vehicles have a negative impact on roadwork zone capacity. An increasing complexity of work, from light barrier works to extensive bridge repair, has a negative impact on performance. An increased lane width has a positive effect on capacity. The diversion of traffic to the opposite carriageway is often the cause of the bottleneck and therefore has a significance effect on capacity. The conclusion from the literature review is that the most important parameters that should be incorporated in a Swedish capacity manual for the operation and maintenance of roadwork are: the proportion of heavy traffic, lane width, type of roadwork, number of closed lanes, closed road shoulder, proportion of commuter traffic and length of roadwork zone. In general, there have been (too) few empirical studies focusing on the differences in capacity caused by these situation-specific variables. The paper presents a comparison between the Dutch model for computation of capacity reduction and a composite model of reduction factors from Germany, USA and Denmark. The comparison show that the two models essentially gives the same results. Based on these results a new model was developed. In the developed model, the capacity for the remaining lane is calculated. The paper presents results from a field study in Gothenburg where throughput was measured in three cases during a morning hour and one afternoon hour. The capacity was calculated from the normal site conditions according to historical traffic flow and speed data. The result shows that the empirically estimated confidence interval of capacity reduction is consistent with the reduction calculated with the new model for the different cases. The conclusion is that the model can be used to calculate capacity reductions for different roadwork zone configurations but that validation for more configurations is desirable.

The first Swedish 2+1 median barrier road was opened in 1998. The concept was to retrofit the standard existing two-lane 13 m paved width cross-section at 90 and 110 kph posted speed limit without widening. This design has one continuous lane in each direction, a middle lane changing direction every one to three kilometres with a median barrier separating the two traffic directions. Today over 2 700 km 2+1 median barrier roads are opened for traffic. AADT’s vary from some 3 000 to 20 000 with an average just below 10 000 nowadays normally with 100 kph. The concept has lately been enhanced also to cover the existing 9 m paved width cross-section. The design concept is the same from a driver’s viewpoint, one continuous lane in each direction with a middle lane changing direction and a separating median barrier. This is created by introducing a continuous median barrier and adding overtaking lanes within an overtaking strategy. The differences are the existence of 1+1-sections, less overtaking opportunities and a slightly more narrow cross-section. Some 15 projects are opened. The purpose of this paper is to summarize present knowledge on level-of-service issues as they are presented in Swedish design and assessment guidelines and to give an overview of field measurements and theoretical analytical and simulation studies supporting the recommendations.

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

This paper presents a micro-simulation model that takes flared design of rural intersections into consideration. The intersection model is designed with input parameters that describe the geometric conditions of the flare. The behavior model includes both a traditional gap-acceptance sub-model and a passage model for modelling of vehicles’ possibility to pass other vehicles using the flare. The intersection model developed has been implemented in the traffic micro simulation model RuTSim. The gap-acceptance part of the model has been calibrated using data for stop and yield 3-way intersections. The validation was performed by using video recordings to calculate delay for the yield regulated intersection and time in queue and service time for the stop regulated intersection. The results from the validation simulations correspond well with the empirical validation data. The effect of the flare on delay has been studied by using 3 different intersection lay-outs and different levels of minor and major flow. The result shows that the delay is decreasing with increasing intersection radius.

Microscopic traffic simulation is often used as an alternative or complementary tool to analytical methods and procedures for level-of-service analyses of road traffic facilities. The increased usage of traffic simulation for level-of-service analysis has raised a need for guidelines on how to apply and use traffic simulation models. Many countries have developed or are currently developing traffic simulation guidelines. This is also the case in Sweden, were the new Swedish highway capacity manual will include a chapter on traffic simulation. This paper presents a survey of the current traffic simulation guidelines in USA, Germany, UK, Denmark and Sweden. The guidelines have been analysed with respect to the aspects covered: when to apply simulation; the workflow of a simulation study; data collection needs; calibration and validation; experimental design; statistical analysis; and calculation of level-of-service measures. The guidelines analysed are focused on different aspects and none of them covers all of the topics listed above. Some of the guidelines are connected to specific simulation software packages and some are written in a more general manner. Most of the aspects covered are general and applicable in any country. The main reason for developing country specific guidelines is often a need for guidelines in the local language. Experimental design and statistical analysis are not treated extensively in the guidelines; neither do the guidelines discuss how to deal with calibration based on limited real world measurements. Calculation of level-of-service measures are quite extensively treated in some of the guidelines and to a little extent in others. All of the guidelines contain important contributions for the simulation chapter of the new Swedish highway capacity manual. © 2011 Published by Elsevier Ltd.

Roundabouts have become a more common type of intersection in Sweden over the last 30 years. In order to evaluate the roundabout level-of-service both analytical models and simulation models are being used. Analytical traffic models for intersections, such as the Swedish capacity model Capcal, has difficulties estimating the level-of-service of a roundabout if there are pedestrians and cyclists at crossings located close to the roundabout. It is well known that a crossing located after a roundabout exit can cause an up-stream blocking effect that affects the performance of the roundabout. But how the upstream blocking effect depends on the different flows of vehicles and pedestrians is not known. In this paper an existing analytical model by Rodegerdts and Blackwelder has been investigated and compared to simulations in VISSIM and measurements from Swedish roundabouts. The purpose of this investigation is to examine if the model by Rodegerdts and Blackwelder is suitable for implementing into existing analytical models such as Capcal. The results show that the model by Rodegerdts and Blackwelder can estimate if a capacity loss will occur, but the magnitude of this loss is more difficult to evaluate. The conclusion and recommendation is that the model by Rodegerdts and Blackwelder should be implemented into the Swedish capacity model Capcal. The model by Rodegerdts and Blackwelder is to be used as a warning system if the results in Capcal are too uncertain to use for analysis of the roundabout performance. © 2011 Published by Elsevier Ltd.