Mixed Traffic Flow Conditions Research Articles

Method for utilizing the reserved lane capacity: Formation of the mixed traffic flow

As the surge in demand for the motor travel continues, the lane capacity is becoming increasingly ineffective in matching the operation of the traffic flow. A method that can utilize the reserved lane capacity and thereby effectively increase the lane capacity is urgently needed for this problem. It is considered in this paper that the formation of a mixed traffic flow which includes both the human-driven vehicles (HDVs) and the connected autonomous vehicles (CAVs) is one such method. Relying on the exploration of the following rules between the HDVs and the CAVs, a heterogeneous vehicle following model (HVFM) can be established as a guide for the formation of the mixed traffic flow. Under the guidance of the HVFM, the effects of different following mode types on the formation characteristics of the mixed traffic flow can be defined, determined and evaluated. At the same time, with the applicability of the three-phase traffic theory in mind, a three-phase traffic flow model under the mixed traffic flow condition (M-TTFM) is established for providing guidance on the operating mechanism of the mixed traffic flow, the determining method of the lane capacity and the utilizing method of the reserved lane capacity at the micro-theoretical level. The maximum lane capacity under the mixed traffic flow conditions can be up to 205.94 % of the lane capacity under HDV traffic flow conditions with the formation of the mixed traffic flow, which indicates that the reserved lane capacity can be greatly utilized by forming the mixed traffic flow. In particular, by mixing the CAV fleets platooned by the CAVs into the HDV traffic flow, the utilizing effect for the reserved lane capacity can be improved with a maximum level of 194.25 %, which is called the in-depth utilization of the reserved lane capacity. What is more, the fundamental diagrams expressing the relationship between the traffic flow rate and the density under the mixed traffic flow condition can be obtained and the recommended value of the lane capacity under the mixed traffic flow can be measured. In summary, the utilizing method for the reserved lane capacity in this paper is expected to further enhance the lane capacity and contribute to solving the problems caused by the lack of the lane capacity.

Impacts of connected autonomous vehicle platoon breakdown on highway

Connected Autonomous Vehicles (CAVs) are seen as an opportunity to improve traffic efficiency and safety. However, further studies are needed to prove such positive effects. Particularly, there is a lack of quantitative research on the impacts of CAV breakdown in mixed traffic flow conditions (i.e., CAVs and Human Driven Vehicles, HDVs). The aim of this research is to explore the impacts generated by the breakdown of the leading vehicle of a CAV platoon in mixed traffic conditions, which in turn generates CAV platoon breakdown (i.e., platoon dispersion), by considering several CAV market penetration rates (MPRs) and platoon size. In this perspective, a control algorithm (“avoidance algorithm”) for modelling CAVs and HDVs behaviour to avoid obstacles (i.e., breakdown CAV platoon) has been developed and tested on some simulation scenarios in order to derive key traffic flow parameters. The dynamic characteristics of traffic flow with CAV platoon breakdown have been explored for both low and high traffic flow volumes. Finally, potential conflicts, congestions, as well as energy consumption and CO2 emissions resulting from the breakdown of CAV platoons in mixed traffic streams have been assessed and discussed. Results suggest that (1) CAV platoon breakdown can reduce the traffic capacity by about 20 %; (2) higher CAV MPRs are more suitable for enhancing highway safety even in breakdown conditions, decreasing energy consumption, and reducing CO2 emissions; (3) platoon size should be limited to 4, since larger sizes affect traffic safety, increases vehicle average delay time as well as energy consumption. The obtained results provide useful insights for transportation planners and transport infrastructure management companies to design and apply policies aimed at improving driving conditions, traffic quality, and safety on highways.

MODELLING ROUNDABOUT ENTRY CAPACITY FOR MIXED TRAFFIC FLOW USING ANN: A CASE STUDY IN INDIA

Roundabouts, as an unsignalized intersection, have an effective preventative measure designed to control straight-line crashes. Efficient traffic flow in cities depends upon appropriate capacity estimation of roundabouts. This study attempts to develop models for roundabout entry capacity by applying Artificial Neural Network (ANN) analysis for mixed traffic flow conditions. Data was gathered from 27 roundabouts spread across India. The influence area for gap acceptance (INAGA) concept was used as a graphical method to identify critical gap (Tc) of entry flow at roundabouts. This study indicated that the Bayesian Regularisation Neural Network (BRNN) based model has the best R2 and RMSE of 0.97 and 167.8. The connection weight approach and Garson algorithm evaluate the significance of each explanatory variable and identify follow-up time (Tf) as a critical parameter with values of 11.10 and 21.15%, respectively.

Development of a Finite Element Model to Analyze the Lateral Drift of Autonomous Vehicles and Its Impacts on Rutting Depth on Flexible Pavements Under Mixed Traffic Scenarios

The continuous development of technologies, including intelligent networking, machine vision, and new energy vehicles, has made autonomous driving vehicles a research focus. Autonomous vehicles significantly affect road performance under mixed traffic flow conditions with their excellent lateral control ability and driving stability. A finite element model is established to analyze the impact of these modes on pavement deformation under maximum air temperature in Nanjing, China. Based on the simulation results, it has been shown that lateral control of autonomous vehicles significantly reduces pavement deformation. The proportion of autonomous vehicles affects the difference in distribution modes, and the uniform distribution mode is the most favorable for horizontal distribution. Additionally, the edge lane experiences less pavement deformation than the center lane and varies more when the distribution pattern changes. By comparing the deformation of the center and edge lanes, the edge lane experiences a significant reduction in deformation under the uniform distribution mode, with a maximum reduction of 73.7%. Comparing the pavement deformation of center and edge lanes under normal distribution mode and uniform distribution mode shows that safe solutions for the lateral distribution of autonomous vehicles depend on the proportion of autonomous vehicles. The optimal driving speed for autonomous vehicles is 80 km/h under the uniform distribution model, while under the normal distribution model it is 90 km/h or 110 km/h. These findings provide a theoretical basis for the lateral control of autonomous vehicles in the future and propose safe solutions for the lateral distribution of autonomous vehicles.

Impacts of bus holding strategies on the performance of mixed traffic system

The holding strategy performs well in resisting bus bunching in the dedicated bus route. Yet, its efficiency in a non-dedicated bus route has not been well studied, and its external effects on other road participants are unclear. We study this topic in a circular two-lane traffic system consisting of buses and cars. A cellular automaton model is used to depict the vehicles’ dynamic behaviors. By numerical simulations, we obtained the phase diagram of the bus system, and identified the four states concerning the stability and level of service. Then we analyzed the flow and velocity characteristics and distinguished three states of the traffic system. Our simulations prove the separation effect of car flows on the bus headway regulation. Combined with this effect, the holding strategy makes the bus running more homogeneous and the bus utilization more evenly in the mixed traffic flow condition. Interestingly, from a macro perspective, the holding strategy incurs no detrimental effects on the whole traffic system, though it might intensify local interference between buses and cars near bus stops. Under certain conditions, the average speed of buses and cars increases, eventually increasing the system’s capacity.

The Model of the Optimal Number of Public Transport Vehicles in Mixed Traffic Flow Conditions: A Case Study

Bus passenger transport is very important for sustainable urban mobility, and due to the characteristics of the street network, it is usually realized in the conditions of mixed traffic flow. Disturbances and sudden changes of traffic flow parameters occurring in the street network in a mixed traffic flow affect the disruptions in schedule and travel time of all vehicles in the traffic flow, including public transport (PT) vehicles. In order to keep to the planned schedule in the peak hours of PT lines carried out in the conditions of mixed traffic flow, the operators introduce new vehicles or reduce the vehicles’ dwell time at terminuses, which is often impossible to do. The use of a larger number of public transport vehicles increases the fuel consumption, pollutants’ emission, and the operating costs. In this paper, a network optimization model was developed for defining the influence of the change of traffic flow parameters in a mixed traffic flow on travel time of PT vehicles. The model takes into consideration uncertain time unevenness of the change of traffic flow parameters, which enables determining the optimization of travel time and defining the necessary number of public transport vehicles for the purpose of keeping to the planned schedule. In order to develop the transport model, counting and analysis of the characteristics of traffic flow at 61 intersections on the city territory were carried out. The model was tested on bus line number 4 of PT in Novi Sad. The model showed that it is possible to achieve certain savings regarding the number of vehicles with the unchanged headway, that is, the unchanged level of service which is offered to the users. With the application of the model in real traffic conditions, significant savings, as well as operating and external costs’ reduction, can be achieved, which contributes to the sustainability of public bus transport in urban environments.

Effect of vehicle composition on saturation flow at signalised intersections in mixed traffic conditions

Vehicular traffic in most of the developing countries is a mixed traffic flow condition with non-lane-based behaviour in urban roads. Vehicles with different static and dynamic characteristics share a common lane. Signalised intersections provide sequential movements of vehicular traffic from one leg to another leg. Saturation flow is an important parameter for the measurement of the level of service at signalised intersections. The various equations, developed for the estimation of saturation flow, for a mixed traffic flow condition do not consider the non-lane-based traffic conditions. There is a need to establish a model to estimate the saturation flow of a signalised intersection for a non-lane-based vehicular movement in mixed traffic flow conditions. This research work presents the findings of the analysis of saturation flow conducted at signalised intersections in three different cities, Warangal, Raipur, and Calicut, in India. Flow rate and traffic volume data are collected using a video graphic technique and the Transportation Research Record Laboratory direct vehicle count method is used to estimate saturation flow. The developed model shows good predictability in comparison with observed data and can be used to estimate saturation flow in non-lane-based traffic conditions.

Comparative Study of Pedestrian Crossing Behaviour at Uncontrolled Intersection and Midblock Locations

Understanding pedestrian-vehicular interaction and individual’s responsive behaviour under mixed traffic flow condition is a complex task. Individual’s perception and risk taking to cross the road varies with pedestrian characteristics (age, gender, luggage, and trip purpose), environmental characteristics, vehicular flow characteristics, land use type. The present study made a comparison of average pedestrian crossing speeds at different pedestrian crossing locations in medium size cities (Warangal and Thiruvananthapuram in India) under mixed traffic conditions to investigate the major factors affecting the pedestrian road crossing behaviour. Four hours of traffic data was collected using videography method from three uncontrolled intersections and two midblock locations. Significant test was done for crossing speeds between different locations and different pedestrian types. The statistical results showed that there is a significant difference between the crossing speed of midblock and intersection. Male and middle aged pedestrians have higher crossing speeds than female and young, old aged pedestrians respectively. It is concluded that the pedestrian crossing behaviour and their perception in risk taking varies with location, pedestrian’s characteristics. Simulation results showed that the average travel time delay changed with pedestrian age and gender and increased linearly with the pedestrian volume. The results can be used to understand pedestrian risk with vehicular flow.

A state-constrained optimal control based trajectory planning strategy for cooperative freeway mainline facilitating and on-ramp merging maneuvers under congested traffic

This paper presents a trajectory planning strategy for connected automated vehicles (CAVs) to cooperatively carry out mainline facilitating (i.e. gap development) and on-ramp merging maneuvers. The trajectory planning tasks of the mainline facilitating vehicle and the merging vehicle are formulated as two related optimal control problems. The motivation behind the proposed strategy is to restrain a facilitating maneuver’s impact on following traffic. To this end, the proposed strategy bounds the speed of the facilitating maneuver from below and meanwhile ensures that the task of gap development can still be fulfilled. Because of the existence of the speed bound, the optimal control problem of the facilitating vehicle becomes constrained in state, in addition to the control constraints. A Pontryagin Maximum Principle (PMP) with state constraints is applied to rigorously derive the analytical solution. The main difficulty of the analytical procedure exists in the fact that the first-order necessary condition on the extremality of the Hamiltonian cannot yield useful information on the property of the optimal control history with regard to making the optimal speed trajectory to satisfy the speed constraint. As a result, additional conditions have to be explored, notably the so-called “jump conditions”, among others. Taking advantage of the analytical solution, the proposed strategy is then implemented under a model predictive control framework.Simulation assessments of the proposed strategy are conducted at two levels – individual vehicle level and traffic flow level. At the individual vehicle level, the proposed strategy shows potential to reduce the risk of rear-end collision between the facilitating vehicle and the following vehicle, the most vulnerable pair of vehicles under the influence of gap development. At the traffic flow level, coupled with Aimsun, the proposed strategy is assessed under mixed traffic flow conditions, with various penetration rates of CAVs. The results show that it has potential to generate lower speed variations of traffic flow, a critical factor in traffic flow safety. Meanwhile it does not show negative impact on traffic efficiency in the simulation, and is likely to improve traffic efficiency in the real world. A sensitivity analysis of the effect of the facilitating maneuver’s lower speed bound is also conducted. Although there exist several limitations with this study, it sheds some light on future research.

Effects of mixed traffic and elderly passengers on city bus drivers’ work-related fatigue

City bus drivers are facing increasingly stressful work situations. In urban areas, bus drivers are competing for limited road space with various vehicles in mixed traffic conditions. This mixed traffic flow condition may not only cause traffic congestion problems but also increase the driving fatigue of a city bus driver. In addition, the average number of elderly passengers are increasing. Constrained by their physical conditions, elderly passengers usually take more time to get on or off a bus and require a city bus driver’s special attention or help. An increase in elderly passengers using city buses may increase the bus driver’s stress and/or fatigue levels. This study developed a structural equation model to investigate the causal relationships between a vector of stress factors and city bus drivers’ fatigue levels from a risk management perspective. The empirical study results based on a questionnaire survey indicated that mixed traffic flow conditions and the characteristics of elderly passengers are positively correlated with the levels of driving fatigue in city bus drivers. An increase in the number of motor scooters in a traffic stream and/or elderly passengers on a bus will lead to higher levels of mental fatigue for a city bus driver. This study discussed the effects of several stressors on a city bus driver’s fatigue and provided suggestions for changes in policies to ensure the fatigue mitigation of city bus drivers.

Modelling automobile users’ response pattern in defining urban street level of service

This paper presents a qualitative study on automobile users’ response pattern to assess the provided transportation service quality under heterogeneous traffic flow conditions. An Automobile Users’ Satisfaction index (AUSi) is established using data sets of questionnaire survey collected from 34 urban street segments of three midsized Indian cities. About 977 respondents with a suitable cross-section of gender, age, driving experience etc. were participated in travellers’ intercept survey. Rasch Model (RM) was applied to identify a set of quantitative measures to analyse the complex process of measuring perceived service quality and degree of drivers’ satisfaction together. The present study comprehends the multidimensional nature of users’ perception to evaluate AUSi with the help of six-dimensional variables such as roadway geometry, traffic facilities, traffic management, pavement condition, safety and aesthetics. RM offers a particular score to each user and each dimensional attribute along with a shared continuum. This way, the attributes those are more demanding to produce satisfaction as well as the variation in response of different modes of transport are evidently identified. The key findings indicate that the participants reported lower satisfaction level mainly due to the absence of separate bike/bus pull-out lanes, improper parking facilities and interruption by non-motorised vehicles/public transit or roadside commercial activities. Fuzzy C-Means (FCM) clustering was applied to classify AUSi scores into six auto Levels Of Service (LOS) categories (A–F) for each street segment. The model was well validated with a significant matching of predicted Automobile users’ LOS (ALOS) service categories with the users’ perceived Overall Satisfaction (OS) scores for fourteen randomly selected segments. This prediction model is new to mixed traffic flow condition, which uses linguistic information and real-life issues of drivers for the current state of services. Hence, the proposed method would be more credible than conventional models to support the decision makers for long term planning and designing road networks on a priority basis

Traffic Oscillation using Stochastic Lagrangian Dynamics: Simulation and Mitigation via Control of Autonomous Vehicles

The phenomenon of stop-and-go waves is frequently observed in congested traffic. With the development of connected and autonomous vehicle (CAV) technologies, it is possible to reduce traffic oscillation via control of CAVs in a mixed traffic flow with both human drivers and autonomous vehicles (AVs). This paper introduces a stochastic Lagrangian model which is capable of simulating stop-and-go traffic considering the heterogeneity of drivers. The sample paths of the stochastic process are smooth without aggressive oscillation. The model is further extended to the mixed traffic flow condition, considering stochastic human driving behavior and deterministic behavior of AVs. With the proposed model, the variation of performance of AV control strategies can be quantified in addition to the average performance. A numerical example with a single lane circular road is used to investigate the impact of the AV control strategy on mitigating stop-and-go waves. Both qualitative and quantitative results show that the phenomenon of stop-and-go waves can be reduced significantly with only one AV, while the increase of AVs from 10% (two AVs) to 50% (10 AVs) offers just marginal improvement in relation to the ensemble-averaged performance and 95% confidence interval of the ensemble-averaged performance. The proposed simulation approach based on the stochastic Lagrangian model can effectively investigate the impact of AV control strategies on traffic oscillation, considering in particular the uncertainty of human driver behavior.

Modeling and analysis of mixed flow of cars and powered two wheelers

In modern cities, a rapid increase of motorcycles and other types of Powered Two-Wheelers (PTWs) is observed as an answer to long commuting in traffic jams and complex urban navigation. Such increasing penetration rate of PTWs creates mixed traffic flow conditions with unique characteristics that are not well understood at present. Our objective is to develop an analytical traffic flow model that reflects the mutual impacts of PTWs and Cars. Unlike cars, PTWs filter between cars, have unique dynamics, and do not respect lane discipline, therefore requiring a different modeling approach than traditional “Passenger Car Equivalent” or “Follow the Leader”. Instead, this work follows an approach that models the flow of PTWs similarly to a fluid in a porous medium, where PTWs “percolate” between cars depending on the gap between them.Our contributions are as follows: (I) a characterization of the distribution of the spacing between vehicles by the densities of PTWs and cars; (II) a definition of the equilibrium speed of each class as a function of the densities of PTWs and cars; (III) a mathematical analysis of the model’s properties (IV) an impact analysis of the gradual penetration of PTWs on cars and on heterogeneous traffic flow characteristics.The proposed model could contribute as an enabler for ‘PTW-aware’ future Cooperative Intelligent Transport Systems technologies and traffic regulations.

Evaluating Service Criteria of Urban Streets in Developing Countries Based on Road Users’ Perception

The objective of this research is to develop a model that can be used to assess level of service (LOS) delivered by urban street segments in developing countries. An innovative survey questionnaire was developed taking 33 questions related to the quality of service (QOS) attributes affecting road user’s satisfaction under mixed traffic flow condition. A road user’s satisfaction survey was carried out, in which participants were requested to assess the QOS attributes and overall satisfaction (OS) on a seven-point Likert scale ranging from strongly disagree to strongly agree. The 33 responses were summarized into eight uncorrelated sets of variables using factor analysis. A Kaiser–Meyer–Olkin value of 0.836 indicates that the sample size is suitable for factor analysis. The model was developed using multiple linear regression analysis to predict the OS of urban street taking eight principal components as independent variables. The prediction performance of the developed model and significance of the input data sets were statistically checked. An R2 value of 0.709 and adjusted R2 value of 0.683 signifies the suitability of the model for its universal application. The predicted OS scores are classified into six categories by applying k-means clustering to assign the threshold values for six LOS classes. Most of the road segments were found out with provided service categories “C” or below. Hence necessary actions should be undertaken by the transportation authorities to achieve higher LOS scores.

Roundabout Capacity in Heterogeneous Traffic Condition: Modification of HCM Equation and Calibration

Abstract The highway capacity manual (HCM-2010) is widely referred document around the globe for planning and design of roads. However, the transferability of HCM recommendations for heterogenous traffic condition represents a significant research issue as they are often not suitable to adequately explain the traffic complexities of a mixed-traffic state. This research investigates the suitability of HCM equations for determining the entry capacity of a four-legged roundabout under mixed traffic condition and proposes a methodology for validating and calibrating HCM equations for performance evaluation. Data corresponding to traffic composition, traffic volume, critical gap and follow-up time have been extracted from the video records collected at two roundabouts. The relationship between entry flow and circulatory flow has been plotted from the observed data when there is a complete saturation in the approach leg and depicted that it follows a negative exponential behavior. It implies that the entry capacity reduces exponentially with the increase in circulating flow. The critical gap has been estimated by various methods such as Maximum Likelihood Method (MLM), Root Mean Square (RMS) method and Probability Equilibrium Method (PEM). Further, a stream equivalent critical gap of 1.60 seconds and stream equivalent follow-up time of 1.24 seconds have been derived due to the mixed traffic scenario at the study location. A multiplicative adjustment factor of 1.1 is suggested for the use of HCM 2010 equation directly to estimate entry capacity under heterogeneous traffic condition. The study results may use for planning and designing of roundabout under mixed-traffic flow condition.

A Traffic Control System Using Inductive Loop Detector

This paper presents the development of an inductive loop traffic sensor device that can detect the vehicles under heterogeneous and lane less traffic conditions. The existing available loop systems are only suitable for lane based and homogeneous traffic conditions. The developed multiple loop system has a new loop structure that can detect large vehicles like bus, truck etc., as well as small vehicles like bicycle, motorcycle etc., occupying any available space in the road. The proposed system detects, segregates the vehicle type and also counts the number of vehicle even in mixed traffic flow condition.

Highway capacity through vissim calibrated for mixed traffic conditions

The present study demonstrates applicability of VISSIM software to determine capacity of multilane highways under mixed traffic flow conditions. Traffic flow data collected on a section of four-lane divided highway are used to develop the speed-flow curve. The same set of field data is used in VISSIM and simulated speed-flow curve is compared with field curve. It was found that VISSIM in its original form overestimates both speed and capacity of the highway. Driver behaviour parameters CC0 and CC1 are first determined for homogeneous traffic conditions having only one of the four types of vehicles in the stream and then results are aggregated to get the values of these parameters for a mixed traffic stream. Further analysis of field data with calibrated values of CC0 and CC1 indicated a good match between field and simulated capacity. The procedure is shown to work on another section of four-lane divided highway with paved shoulders, where simulated capacity was 5329 pcu/hr against the field capacity of 5277 pcu/hr.

Preface: special issue on advanced traffic and transportation systems

Traffic and transportation systems impact our everyday lives significantly. By nature, the transportation system is a complex system. This complexity presents a challenge to engineering scientists and applied mathematicians. This special issue will focus on the engineering science and applied mathematics oriented contributions related to traffic and transportation systems. The topics in this special issue cover a wide range of areas in transportation and traffic modeling. The papers highlight the coming together of technology and human factors and how this impacts the transportation system. A key issue in transportation is safety. There are two papers in this special issue that addresses traffic safety. Darbha and Rajagopal outline the major safety issues associated with sudden breaking operations of automated vehicles. With recent developments in the area of driverless cars and with the imminent possibility of automated vehicles sharing space with human drivers, there is an urgent need to understand fundamental issues with respect to safety of such systems. This paper is a seminal contribution in this regard. The other paper on safety focusses on driver drowsiness detection and remediation. Dasgupta et al. propose a system to monitor the loss of attention of drivers due to drowsiness. The system includes a hardware system coupled with image processing algorithms that is shown to work under demanding conditions often encountered inside a moving vehicle. It is an excellent example of innovative interdisciplinary solutions to transportation problems. The next three papers focus on transportation planning. Sikder et al. provide a comprehensive review of spatial transferability of travel forecasting models. The review is comprehensive and presents both theoretical and practical considerations. Several important open issues are identified and the paper promises to be an important reference to both transportation planning researchers and practitioners. Gopisetty and Srinivasan present a joint model for trip frequency and vehicle ownership based on data from Chennai city, India. The presence of both two wheelers and four wheelers among households in developing countries and their varying impact on trip frequency requires joint models that can capture this endogeneity. The paper highlights the importance of capturing this endogeneity and presents practical implications of the model results for management decisions. The third paper on planning by Aziz and Ukkusuri explores a novel idea of using tradable credit schemes to minimize and manage vehicular emissions. This paper is timely because of the urgent need to address global warming impacts of transportation emissions. The mathematical model presented in the paper also explores a more acceptable trade-off between traditional objectives of minimizing travel time along with reduced emissions. The final two papers in this special issue deal with traffic flow modeling and capacity estimation. Ranju and Ramadurai present a review of state-of-the-art of macroscopic traffic flow models. Unlike earlier reviews that have covered traffic flow models in general, the focus here is on macroscopic models. Since the last review that appeared over a decade ago, the field has seen the emergence of new higher-order macroscopic models as well as different models for capturing flow along links and at nodes. This review is timely and is likely to encourage more research into advanced macroscopic traffic flow models. Puwala et al. estimate the capacity of eight-lane divided urban expressway in the presence of mixed-traffic flow conditions. The paper argues that expressways in India behave and operate differently when compared with countries L. D. Vanajakshi (&) G. Ramadurai K. K. Srinivasan Department of Civil Engineering, IIT Madras, Chennai, India e-mail: lelitha@iitm.ac.in

혼합교통류 신호교차로에서 자전거교통 좌회전 통행방식 평가연구

PURPOSES: This study proposes a novel method based on microscopic simulation models to evaluate bicycle passing ways in mixed traffic flow conditions at signalized intersections. METHODS: Both operational efficiency and safety are taken into consideration in the evaluation. A widely used performance measure, delay, is used for evaluating the operational efficiency. Regarding the safety evaluation, surrogate safety measures (SSM) to represent traffic conflicts and the level of crash severity, DeltaS and Max.DeltaV, are applied in the proposed method. RESULTS: Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS: The proposed method and outcomes of this study will be valuable for bicycle traffic operations and facility design.

A Multiple Inductive Loop Vehicle Detection System for Heterogeneous and Lane-Less Traffic

This paper presents a novel inductive loop sensor that can detect vehicles under a heterogeneous and less-lane-disciplined traffic and thus can be used to support a traffic control management system in optimizing the best use of existing roads. The loop sensor proposed in this paper detects large (e.g., bus) as well as small (e.g., bicycle) vehicles occupying any available space in the roadway, which is the main requirement for sensing heterogeneous and lane-less traffic. To accomplish the sensing of large as well as small vehicles, a multiple loop system with a new inductive loop sensor structure is proposed. The proposed sensor structure not only senses and segregates the vehicle type as bicycle, motor cycle, scooter, car, and bus but also enables accurate counting of the number of vehicles even in a mixed traffic flow condition. A prototype of the multiple loop sensing system has been developed and tested. Field tests indicate that the prototype successfully detected all types of vehicles and counted, correctly, the number of each type of vehicles. Thus, the suitability of the proposed sensor system for any type of traffic has been established.