Heterogeneous Traffic Flow Research Articles

Modeling connected and autonomous vehicles in heterogeneous traffic flow

The objective of this study was to develop a heterogeneous traffic-flow model to study the possible impact of connected and autonomous vehicles (CAVs) on the traffic flow. Based on a recently proposed two-state safe-speed model (TSM), a two-lane cellular automaton (CA) model was developed, wherein both the CAVs and conventional vehicles were incorporated in the heterogeneous traffic flow. In particular, operation rules for CAVs are established considering the new characteristics of this emerging technology, including autonomous driving through the adaptive cruise control and inter-vehicle connection via short-range communication. Simulations were conducted under various CAV-penetration rates in the heterogeneous flow. The impact of CAVs on the road capacity was numerically investigated. The simulation results indicate that the road capacity increases with an increase in the CAV-penetration rate within the heterogeneous flow. Up to a CAV-penetration rate of 30%, the road capacity increases gradually; the effect of the difference in the CAV capability on the growth rate is insignificant. When the CAV-penetration rate exceeds 30%, the growth rate is largely decided by the capability of the CAV. The greater the capability, the higher the road-capacity growth rate. The relationship between the CAV-penetration rate and the road capacity is numerically analyzed, providing some insights into the possible impact of the CAVs on traffic systems.

A Dual Ring Connectivity Model for VANET Under Heterogeneous Traffic Flow

Vehicular ad-hoc network (VANET) is characterized as a highly dynamic wireless network due to the dynamic connectivity of the network nodes. To achieve better connectivity under such dynamic conditions, an optimal transmission strategy is required to direct the information flow between the nodes. Earlier studies on VANET’s overlook the characteristics of heterogeneity in vehicle types, traffic structure, flow for density estimation, and connectivity observation. In this paper, we have proposed a heterogeneous traffic flow based dual ring connectivity model to enhance both the message disseminations and network connectivity. In our proposed model the availability of different types of vehicles on the road, such as, cars, buses, etc., are introduced in an attempt to propose a new communication structure for moving vehicles in VANETl under cooperative transmission in heterogeneous traffic flow. The model is based on the dual-ring structure that forms the primary and secondary rings of vehicular communication. During message disseminations, Slow speed vehicles (buses) on the secondary ring provide a backup path of communication for high speed vehicles (cars) moving on the primary ring. The Slow speed vehicles act as the intermediate nodes in the aforementioned connectivity model that helps improve the network coverage and end-to-end data delivery. For the evaluation and the implementation of dual-ring model a clustering routing scheme warning energy aware cluster-head is adopted that also caters for the energy optimization. The implemented dual-ring message delivery scheme under the cluster-head based routing technique does show improved network coverage and connectivity dynamics even under the multi-hop communication system.

Development of Roundabout Entry Capacity Model Using INAGA Method for Heterogeneous Traffic Flow Conditions

The main objective of the study is to develop a roundabout entry capacity model by employing Influence Area for Gap Acceptance (INAGA) method under heterogeneous traffic flow conditions. In this regard, data collection has been carried out to extract the traffic flow and gap acceptance parameters which were significantly contributing to modelling the roundabout entry capacity. The traffic flow data were found to be heterogeneous in nature because of the percentage of traffic share in entry leg varying (0–55.8)%, (10–79.5)%, (18–76.5)%, (0–25.5)% and (0–7)% of heavy vehicles, light motor vehicles, motorcycles/scooters, bicycles and human-drawn vehicles, respectively. The critical gap (\(t_\mathrm{c}\)) and follow-up time (\(t_\mathrm{f}\)) were found by (INAGA) method ranging between (0.88–2.68) s and (0.86–2.65) s, respectively, via comprised all sites together. Then, multivariate regression analysis was carried out by utilizing M1 distribution function. The analysis of variance demonstrates that the model was statistically significant at 95% confidence level with measured R square is 0.78. To assess the prediction performance of the model, data splitting method was employed in model validation process and revealed that field capacity varies 2.5% w.r.t model capacity in which the measured R square is 0.9758. The newly developed model was compared with different existing models to judge the appropriateness of the model. HCM 2000 and HCM 2010 models showed nearly same results as the developed model. While the Brilon–Wu formula (Germany) and GIRABASE formula (France) overestimated and underestimated the capacity for all flow ranges, respectively.

Redesign of the cross-section of bicycle lanes considering electric bicycles

The design of a bicycle lane's cross-section has a significant influence on the riding behaviours of cyclists. Wider bicycle lanes can encourage users of electric bicycles (e-bikes) to ride within the lane by providing the necessary riding space, which will improve the safety and efficiency of overall multi-level heterogeneous traffic flow. An empirical cross-section design was obtained based on field observations of the riding characteristics of e-bike users at four road sections in Xi'an, China. Vehicle widths, the gaps between vehicles and additional security gaps were considered in order to optimise the design of the cross-section. The results indicate that users of e-bikes within heterogeneous traffic flow need more lateral space for safe riding. The cross-section of bicycle lanes should allow the completion of overtaking manoeuvres, and the results suggest the cross-section needs to be wider than 3 m and no less than 2·6 m. The recommendations of cross-sections with different physical separations were carefully calibrated in order to meet riding requirements. The findings of this study provide reference material for the design of bicycle lanes with consideration of e-bikes.

Modelling vehicular interactions for heterogeneous traffic flow using cellular automata with position preference

This paper proposes and validates a modified cellular automata model for determining interaction rate (i.e. number of car-following/overtaking instances) using traffic flow data measured in the field. The proposed model considers lateral position preference by each vehicle type and introduces a position preference parameter β in the model which facilitates gradual drifting towards preferred position on road, even if the gap in front is sufficient. Additionally, the model also improves upon the conventional model by calculating safe front and back gap dynamically based on speed and deceleration properties of leader and follower vehicles. Sensitivity analysis was carried out to determine the effect of β on vehicular interactions and the model was calibrated and validated using interaction rates observed in the field. Paired tests were conducted to determine the validity of the model in determining interaction rates. Results of the simulations show that there is a parabolic relationship between area occupancy and interaction rate of different vehicle types. The model performed satisfactorily as the simulated interaction rate between different vehicle types were found to be statistically similar to those observed in field. Also, as expected, the interaction rate between light motor vehicles (LMVs) and heavy motor vehicles (HMVs) were found to be higher than that between LMVs and three wheelers because LMVs and HMVs share the same lane. This could not be done using conventional CA models as lateral movement rules were dictated by only speeds and gaps. So, in conventional models, the vehicles would end up in positions which are not realistic. The position preference parameter introduced in this model motivates vehicles to stay in their preferred positions. This study demonstrates the use of interaction rate as a measure to validate microscopic traffic flow models.

End to end delay modeling of heterogeneous traffic flows in software defined 5G networks

In ultra-dense 5th Generation (5G) wireless networks, we believe that foreground User Datagram Protocol (UDP) traffic flow is ′squeezed′ by Transmission Control Protocol (TCP) background because of increasing queue waiting time and extra transmission delay for each timeout in TCP congestion control mechanism. Therefore, traffic Heterogeneity which is defined by the rate between number of UDP over TCP traffic flows for each forwarding device, has become more significant. According to the 3rd Generation Partnership Project (3GPP) Release 13, conventional Long Term Evolution - Self Organize Networks (LTE-SON) does not consider Heterogeneity rate of traffic flows while balancing load between neighbor eNodeBs (eNBs). In order to reduce end to end delay (e2eDelay) of foreground TCP traffic flow, an optimal path should be selected by considering both load Intensity and traffic Heterogeneity level of eNBs. To do this, we propose a Software-Defined Networks (SDN)-based softwarization approach brought by 5G networks with three fold contributions: virtualization of topology graph (G), e2eDelay optimization which is run in terms of both load Intensity (ρj(t)) and Heterogeneity rate(Hj(t)), and novel Queuing Theory based OpenFlow (OF) switch model. Moreover, due to being bottleneck, centralized SDN-Controller is proposed to accelerated with novel three heuristics including shortest path and e2eDelay optimization algorithms running in parallel manner. More specifically, this process is combined into a novel closed-form expression of e2eDelay(Ti(t)) in two main parts: Data plane effect and Control plane effect. As a result, proposed SDN-based e2eDelay model serves foreground TCP traffic flow upto 74% and 98% less e2eDelay than LTE-SON and conventional LTE.

Service levels of sidewalks for pedestrians under mixed traffic environment using Genetic Programming clustering

This study aims at developing a model for pedestrian to evaluate service measure at the roadside walking environment from the qualitative and quantitative analysis in developing countries. The potential primary factors influencing service measure of pedestrian were summarized taking consideration to heterogeneous traffic flow condition and perception of road users. Total 735 real-time sense of participant’s satisfaction when they are using the sidewalks, road geometric as well as operational characteristics of the road segments were collected from the 73 sites. The selected sites belong to midsized cities with varying geometric features. Different statistical investigations like factor analysis, Wilks’ lambda test and stepwise regression analysis were carried out to develop PLOS model for sidewalk facilities. From the results it has been observed that the variables taken such as width of sidewalk, vehicle volume, pedestrian volume etc. are significantly influencing the pedestrian service measure and the model was validated with a significance value of R2= 0.972. The PLOS scores got from the model are then classified using Genetic Programming clustering to find the six PLOS ranges (A-F) which show score for PLOS A ≤1.8 with best condition and PLOS F > 5.1 having worst condition of service.

Modeling heterogeneous traffic flow: A pragmatic approach

Modeling dynamics of heterogeneous traffic flow is central to the control and operations of today’s increasingly complex transportation systems. We develop a macroscopic heterogeneous traffic flow model. This model considers interplay of multiple vehicle classes, each of which is assumed to possess homogeneous car-following behavior and vehicle attributes. We propose the concepts of road capacity split and perceived equivalent density for each class to model both lateral and longitudinal cross-class interactions across neighboring cells. Rather than leveraging hydrodynamic analogies, it establishes pragmatic cross-class interaction rules aspired by capacity allocation and approximate inter-cell fluxes. This model generalizes the classical Cell Transmission Model (CTM) to three types of traffic regimes in general, i.e. free flow, semi-congestion, and full congestion regimes. This model replicates prominent empirical characteristics exhibited by mixed vehicular flow, including formation and spatio-temporal propagation of shockwaves, vehicle overtaking, as well as oscillatory waves. Those features are validated against numerical experiments and the NGSIM I-80 data. Realistic class-specific travel times can be computed from this model efficiently, which demonstrates the feasibility of applying this multi-class model to large-scale real-world networks.

Stability analysis and fundamental diagram of heterogeneous traffic flow mixed with cooperative adaptive cruise control vehicles

This paper is aimed at building a framework for string stability analysis of traffic flow mixed with different cooperative adaptive cruise control (CACC) market penetration rates. In addition to the string stability, the fundamental diagram of the mixed flow is also taken into consideration for evaluating the effect of CACC vehicles on capacity. In order to describe the car-following dynamics of real CACC vehicles, the CACC model proposed by PATH is employed, which is validated by real experimental data. The intelligent driver model (IDM) is used as a surrogate car-following model for traditional manual driven vehicles. Based on the guidelines proposed by Ward[Ward J A 2009 Ph. D. Dissertation (Bristol:University of Bristol)], a framework is developed for the analytical investigation of heterogeneous traffic flow string stability. The framework presented considers the instability condition of traffic flow as a linear function of CACC market penetration rate. Following the framework, the string stabilities of the mixed traffic flow under different CACC market penetration rates and equilibrium velocities are analyzed. For fundamental diagram of the heterogeneous traffic flow, the equilibrium velocity-spacing functions of manual vehicles and CACC vehicles are obtained respectively based on car-following model. Then, the fundamental diagram of the density-velocity relationship of the heterogeneous traffic flow is derived based on the definition of traffic flow density. In addition, the theoretical fundamental diagram is plotted to show the property of traffic throughput. The numerical simulations are also carried out in order to investigate the effect of CACC vehicle on the characteristics of fundamental diagram. Besides, sensitivity analyses on CACC desired time gap are conducted for both string stability and fundamental diagram. Analytical studies and simulation results are as follows. 1) The heterogeneous traffic flow is stable for different equilibrium velocities and CACC market penetration rates, if manual driven vehicles are stable. Otherwise, the instability of traditional traffic flow is improved gradually with the increase of the CACC market penetration rate. Additionally, the stability will become better when equilibrium velocity is away from the velocity range of 9.6-18.6 m/s. 2) Because CACC vehicles can travel at free-flow speed in a relatively small headway, CACC vehicles can improve the capacity of heterogeneous traffic flow. 3) The results of sensitivity analysis indicate that with the increase of the CACC desired time gap, the stable region of heterogeneous traffic flow increases. However, the capacity of the fundamental diagram drops. Therefore, the value of the desired time gap should be determined with considering the effects of the two aspects on the heterogeneous traffic flow. It is noted that the CACC model used in this paper is based on the current state-of-the-art real CACC vehicle experiments. In the future, more experimental observations will yield new CACC models. However, the framework presented in this paper can still be used for the analytical investigation of string stability of the heterogeneous traffic flow at that time.

Characteristic Analysis of Mixed Traffic Flow of Regular and Autonomous Vehicles Using Cellular Automata

The technology of autonomous vehicles is expected to revolutionize the operation of road transport systems. The penetration rate of autonomous vehicles will be low at the early stage of their deployment. It is a challenge to explore the effects of autonomous vehicles and their penetration on heterogeneous traffic flow dynamics. This paper aims to investigate this issue. An improved cellular automaton was employed as the modeling platform for our study. In particular, two sets of rules for lane changing were designed to address mild and aggressive lane changing behavior. With extensive simulation studies, we obtained some promising results. First, the introduction of autonomous vehicles to road traffic could considerably improve traffic flow, particularly the road capacity and free-flow speed. And the level of improvement increases with the penetration rate. Second, the lane-changing frequency between neighboring lanes evolves with traffic density along a fundamental-diagram-like curve. Third, the impacts of autonomous vehicles on the collective traffic flow characteristics are mainly related to their smart maneuvers in lane changing and car following, and it seems that the car-following impact is more pronounced.

Heterogeneous platoon flow dispersion model based on truncated mixed simplified phase‐type distribution of travel speed

SummaryExisting research on platoon dispersion models either describe homogeneous traffic flow feature, or are in lack of analytical solutions. By analyzing the field data, the truncated mixed simplified phase‐type distribution is proved to be capable of capturing the characteristics of heterogeneous traffic flow with an excellent fitting result. In light of this, we derive a generic heterogeneous platoon dispersion model with truncated mixed simplified phase‐type of speed in the forms of integrable functions. Numerical case studies are conducted to compare the performance of the proposed model and the conventional models (i.e., the Robertson model and truncated mixed Gaussian model). The results show that the proposed model not only better captures the platoon dispersion laws of heterogeneous traffic flow, but also presents higher computational efficiency, which provides practical implications on traffic signal control. Copyright © 2017 John Wiley & Sons, Ltd.

Influence of geometric design characteristics on safety under heterogeneous traffic flow

Abstract This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the ‘gap filling’ behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.

Estimating link travel time functions for heterogeneous traffic flows on freeways

SummaryOversized vehicles, such as trucks, significantly contribute to traffic delays on freeways. Heterogeneous traffic populations, that is, those consisting of multiple vehicles types, can exhibit more complicated travel behaviors in the operating speed and performance, depending on the traffic volume as well as the proportions of vehicle types. In order to estimate the component travel time functions for heterogeneous traffic flows on a freeway, this study develops a microscopic traffic‐simulation based four‐step method. A piecewise continuous function is proposed for each vehicle type and its parameters are estimated using the traffic data generated by a microscopic traffic simulation model. The illustrated experiments based on VISSIM model indicate that (i) in addition to traffic volume, traffic composition has significant influence on the travel time of vehicles and (ii) the respective estimations for travel time of heterogeneous flows could greatly improve their estimation accuracy. Copyright © 2016 John Wiley & Sons, Ltd.

Empirical capacity model for roundabouts under heterogeneous traffic flow conditions

It is crucial to measure the performance of existing roundabouts in terms of its ability to handle the present traffic scenario. The capacity of an entry flow is found to vary immensely with the changing geometrics of the roundabout. A meticulous study was conducted to gather data from roundabouts with varying geometry and traffic characteristics. A model was developed using empirical analysis based on five such geometric parameters, which proved to be significant for estimating the capacity. The parameters used in this equation had a multiplicative relation with the conflicting flow. Every geometric has been tested individually for its influence on capacity, keeping the flow conditions constant. The developed model satisfied the practicality when validated with the site data. A comparative study with some existing empirical models indicated that the capacities of roundabouts are underestimated/overestimated for Indian scenario.

Enhancements of the Dynamic TXOP Limit in EDCA Through a High-Speed Wireless Campus Network

IEEE802.11e is a concrete challenge to providing quality of service (QoS) aimed at interactive multimedia (IMM) applications due to the resource allocation parameter for heterogeneous traffic flows. This parameter is fixed for different specific IMM traffic flows in the IEEE802.11e standard. However, due to the variation in traffic load on wireless campus networks (WCNs), the fixed allocation of the channel resource parameter is not sufficient to guarantee QoS for IMM traffic flows. Thus, many researchers have investigated dynamic regulation of this resource allocation parameter to ensure QoS. However, there are still some unresolved problems with this parameter. This paper introduces an enhanced EDCA resource allocation parameter named dynamic transmission opportunity (TXOP) limit that regulates according to the variation in traffic load over WCN. This work also employs a mathematical modelling approach for the proposed parameter and numerical analysis of the existing and proposed parameters. The evaluation of the proposed model is simulated using Qualnet 5.1. The simulation results show that the proposed scheme allows improving the QoS performance of IMM traffic by reducing end-to-end delay. Additionally, the results show that the proposed scheme significantly improves global throughput.

A heterogeneous traffic flow model consisting of two types of vehicles with different sensitivities

A heterogeneous car following model is constructed for traffic flow consisting of low- and high-sensitivity vehicles. The stability criterion of new model is obtained by using the linear stability theory. We derive the neutral stability diagram for the proposed model with five distinct regions. We conclude the effect of the percentage of low-sensitivity vehicle on the traffic stability in each region. In addition, we further consider a special case that the number of the low-sensitivity vehicles is equal to that of the high-sensitivity ones. We explore the dependence of traffic stability on the average value and the standard deviation of two sensitivities characterizing two vehicle types. The direct numerical simulation results verify the conclusion of theoretical analysis.

Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India

Abstract In developing countries like India, the nature of the composition of traffic is heterogeneous. A heterogeneous traffic flow consists of vehicles that have different sizes, speeds, vehicle spacing and operating characteristics. As a result of the widely varying speeds, vehicular dimensions, lack of lane disciplines, honking becomes inevitable. In addition, it changes the urban soundscape of developing countries. In heterogeneous traffic conditions, horn events increase noise level (Lden) by 0.5–13 dB(A) as compared to homogenous traffic conditions. Therefore, the traffic prediction models that are used for homogenous traffic conditions are not applicable in heterogeneous traffic conditions. To increase the accuracy of noise prediction models, in depth understanding of heterogeneous traffic noise is required. Understanding the real traffic noise characteristics requires quantification of some of the basic traffic flow characteristics such as speed, flow, Level Of Service (LOS) and density. In a given roadway, the noise level changes with density and LOS on the road. In this paper, a new factor for horn correction is introduced with respect of Level Of Service (LOS). The horn correction values can be incorporated in traffic noise models such as CRTN, FHWA, and RLS 90, while evaluating heterogeneous traffic conditions.

Time occupancy as measure of PCU at four legged roundabouts

This study is carried out to estimate the passenger car unit (PCU) values of different vehicle categories at a typical four-legged roundabout based on the concept of time occupancy. A stream equivalency factor (k) has also been developed based on the estimated PCU to convert the heterogeneous traffic flow into a homogenous stream equivalent without making use of PCU factors. Relationship between entry flow and circulatory flow has been plotted based on the observed data corresponding to the time period in which there was queue formation in the approach. Further, estimated critical gap and follow-up time have been used to derive the capacity by HCM 2010 equation. A multiplicative adjustment factor is suggested for the use of HCM 2010 equation directly in the field to estimate entry flow under heterogeneous traffic condition. The study results may be suitable for revising the code of practice, named IRC 65–1976, and useful for ongoing national-level efforts of developing Indian Highway Capacity Manual.

Modelling travellers’ en-route path switching in a day-to-day dynamical system

ABSTRACTTravellers’ en-route path switching is a very common travel adjustment behaviour which can significantly influence the whole day-to-day network traffic flow evolution process. This study encapsulated travellers’ sequential path adjustment mechanism into a day-to-day dynamical system, to capture travellers’ en-route switching effect without actually building a complicated within-day model to go with. According to different path choice behaviours and traffic information sources, three traveller groups were contained in the dynamical system, including the conservative travellers, the adventurous travellers unequipped with advanced traveller information systems (ATISs) and the ATIS-assisted adventurous travellers. In the proposed day-to-day dynamical model, a fixed point problem was established for achieving the heterogeneous traffic flow caused by travellers’ en-route path switching. Some stability analysis of the proposed dynamical system was accomplished in the numerical experiment. The effect of en-route path switching behaviour was investigated and it was found to influence both the stability of the dynamical system and the average travel time of adventurous travellers.