Heterogeneous Traffic Conditions Research Articles

Laboratory analysis of driving behavior and self-perceived physiological impairment at 0.03%, 0.05% and 0.08% blood alcohol concentrations

BackgroundAlcohol-impaired driving is a critical factor leading to traffic crashes worldwide. Since decades, researchers from the developed nations have been investigating the effects of alcohol intoxication on their drivers. However, alcohol effects on the drivers of developing counties remain understudied. The extent of alcohol impairment may vary among the drivers of developed and developing nations due to the differences in drivers’ physiology, driving conditions, drinking habits, policy enforcement and driving attitude. MethodsThis study examined the effects of different Blood Alcohol Concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%) on 75 licensed Indian drivers (56 males and 19 females) with the help of a fixed-base driving simulator. Subjects completed driving simulations for all the BAC levels in a driving environment representing heterogeneous traffic conditions. Performance measures included longitudinal and lateral driving control indicators (obtained from simulator) along with the self-reported physiological changes in the drivers (obtained from questionnaire) with varying BAC levels. ResultsMean speed was the only performance measure significantly affected at 0.03% BAC. At 0.05% BAC, mean speed and mean steering wheel angle were the two significantly impaired measures. At 0.08% BAC, all the driving performance measures showed significant impairment except steering wheel angle variability. Physiological characteristics of drivers deteriorated with rising BAC levels. ConclusionsAlcohol significantly impaired the physiology of Indian drivers resulting in impairment in their driving performance. Mean speed was the only performance measure significantly affected by all the BAC levels, making it a suitable parameter to detect the alcohol-impaired state of the drivers.

Post encroachment time threshold identification for right-turn related crashes at unsignalized intersections on intercity highways under mixed traffic

Unsignalized intersections in developing countries experience many serious conflicts between cross-traffic due to indiscipline traffic manoeuvrability. Historically, Post Encroachment Time (PET) has gained attention as a proximal indicator to analyze crossing conflicts. However, identifying an appropriate PET threshold to classify critical conflicts for highly heterogeneous traffic scenario is still an unexplored area. Consequently, this study proposes a novel approach of PET threshold identification with proof of application by collecting data from ten intersections located on four-lane intercity highways in the National Capital Region (NCR), India. Both crossing conflicts and right-turn related crash data (for the left-hand drive) are collected. Their correlations are thoroughly studied for each PET threshold using a quantitative technique considering all and individual vehicle categories. Finally, a qualitative analysis is done by ranking the sites based on cumulative PET and related crashes to verify the proposed quantitative technique. A PET threshold of 1 s is obtained from both the techniques which can be used to identify critical conflicts for unsignalized intersections located on four-lane intercity highways. The proposed methodology will serve as an alternative, faster and effective tool to evaluate the hazardousness of unsignalized intersections located on intercity highways under highly heterogeneous traffic condition.

Development of Composite Level of Service for Signalized Intersections Under Heterogeneous Traffic Conditions

Level of Service (LoS) is the easiest and widely used method for the assessment of quality of service provided to the road users. Depending upon the measure of LoS, appropriate actions may be initiated by the decision makers to enhance the better function of the system if necessary. But intersections are the critical location, where improvement measures for motorized vehicle users might affect the non-motorized vehicle users undesirably. This study focuses on controlled intersections and the efficiency measures of the signalized intersection. Many guidelines have provided the values of LoS of motorized and non-motorized traffic separately, even though they share the same space and time at the intersection. But to understand the efficiency of the whole intersection, all the users should be quantitatively measured with respect to a single unit. This research identifies performance parameters namely, vehicular volume, vehicular delay, pedestrian volume and pedestrian delay which directly influence the cycle time and the operating characteristics of signalized intersection. Empirical traffic models were developed between these performance measures and the best fit relationships were established. A Composite Level of Service (CLoS) which quantitatively measures all the users of an intersection irrespective of mode of transport is estimated using stopped delay of the motorized vehicles and pedestrians of the intersection. This CLoS helps to identify the efficiency of the whole signalized intersection in a single unit. The empirical models and CLoS was validated and application of this study was explained further using ground data.

Calibrating HCM model for roundabout entry capacity under heterogeneous traffic

Roundabout is a channelized intersection where traffic moves around a central island, clockwise for left-side driving and anti-clockwise for right-side driving. Efficiently designed roundabouts can handle traffic very smoothly without causing any delay. The capacity of roundabouts used to be calculated by the weaving theory in India. However, calculation of the entry capacity in the recent literature is based on critical gaps and follow-up times, and the Highway Capacity Manual of US (HCM 2010) provides an equation to estimate the entry capacity of a roundabout by using the flow in passenger car unit per hour (PCU/h), critical gaps and follow-up times at the entry section. In order to examine whether the HCM equation applies to Indian traffic condition or not, we collected data from five roundabouts in India in this study. Relevant data were extracted/estimated to calibrate parameters of the HCM equation. The PCU for a vehicle was estimated on the basis of lagging headway and width of the vehicle, and the critical gap value for a vehicle was estimated by minimizing the sum of absolute difference in a gap with respect to the highest rejected and accepted gaps. Results show that the critical gap values obtained under heterogeneous traffic conditions are much lower than those given in the literature for homogeneous traffic conditions. In addition, the modified HCM equation based on the critical gap values was verified using the field data taken during the formation of a continuous and stable queue at the entry of a roundabout. It was found that a multiplicative adjustment factor needs to be calculated for different sizes of roundabouts to ensure the adjusted HCM equation represents well the traffic condition prevailing in developing countries like India. A test conducted at another roundabout validated that the entry capacity estimated from the calibrated and adjusted HCM model was consistent with the field entry capacity, and the calibrated and adjusted HCM model could predict the entry capacity of an approach to a roundabout quite accurately.

Development of a Video Image Processing-Based Micro-level Data Extractor for Non-lane-Based Heterogeneous Traffic Conditions

Limited studies are conducted to develop trajectory-level data extraction tools for non-lane-based heterogeneous traffic conditions prevalent in developing countries, like India. Comprehending this research gap, the development of an automation-based conceptual methodology is crucial, that would help researchers to understand and assess heterogeneous, non-lane-based traffic at micro-level. Microscopic parameters like individual vehicular trajectory and inter-vehicular spacing, in lateral as well as longitudinal dimensions, play significant roles in understanding traffic dynamics. A major hindrance in acquiring the huge data required for this purpose is the high demand of manpower and time in extracting traffic data manually with desirable accuracy. Implementing automated systems can mitigate the burden of data acquisition. One of the promising ideas for effective traffic analysis is video-based image processing, using which highly accurate data can be obtained by suitably calibrating the threshold values, thereby optimizing it for a given video. In this study, an attempt has been made to develop an automated image processing tool using MATLAB, to first classify vehicles under varying roadway and traffic conditions, and then to obtain lateral as well as longitudinal spacing maintained, based on the detected positions of vehicles on the road over time. The developed traffic data extractor also provides output on individual vehicle trajectory, and, hence, travel times and speed profiles of different vehicle categories. Evaluation results showed an MAPE of less than 13%, suggesting its reliability under varying mixed traffic conditions. The logic developed in this research is expected to cater well for similar traffic conditions in other Asian countries.

Capacity estimation of unsignalized intersections under heterogeneous traffic conditions

Capacity of movements at unsignalized intersections are usually estimated based on gap acceptance theory and accuracy of such estimation largely depends on the extent to which its inherent assumptions are satisfied. However, owing to the typical traffic operations at intersections in developing countries, many of these assumptions remain unsatisfied and hence, estimating capacity as per the procedure laid down in the capacity manuals of developed countries will prove inaccurate. The present research focuses on developing the entire procedure for estimating the capacities of movements at unsignalized intersections dealing with heterogeneous traffic. This study is based on data collected from eight different unsignalized intersections located in various parts of India and by using Harders’ capacity model as base, the procedure to estimate the parameters of this model is revised to suit the traffic operations in developing countries and further modifies the Harders’ model using the movement capacities measured in the field.

Calibration of choice model parameters in a transport scenario with heterogeneous traffic conditions and income dependency

ABSTRACT By raising the issue of data requirements for the purpose of modal development, validation and application, this study proposes an approach to calibrate choice model parameters in heterogeneous traffic condition using minimal empirical data. For this, a real-world scenario of Patna, India is chosen. For the calibration, a Bayesian framework-based calibration technique (CaDyTS: Calibration of Dynamic Traffic Simulations) is used. Commonly available, mode-specific, hourly-classified traffic counts are used to generate full day plans of agents and their initially unknown activity locations. While the proposed approach implements location choice implicitly, the approach can be applied to a variety of other problems. Further, the effect of household income is included in the utility function to incorporate the effect of income in the decision-making process of individual travelers and to filter out inconsistencies in the daily plans, which originate from the survey data.

Passenger Car Equivalents for Heavy Vehicles at Roundabouts. a Synthesis Review

Passenger Car Equivalents (PCEs) are used to convert a mixed traffic flow into an equivalent passenger car flow and to analyze capacity and level-of-service of roads and intersections. Most roundabouts guidelines propose constant values for PCEs but a single PCE value can result improper under heterogeneous traffic conditions. PCEs should be vary with traffic and road conditions so that PCEs used under undersaturated conditions may underestimate the effect of heavy vehicles or be not sensitive to the traffic level or characteristics of heavy vehicles. Compared to other at-grade intersections, the interaction between the operational performances of the heavy vehicles and the geometric features at roundabouts can produce significant impacts on the heavy vehicle paths and traffic operations due to the curvilinear nature of the roundabout design. Literature presents various estimation methods to obtain PCE values for heavy vehicles. The focus of this paper is to review statistical methods and traffic simulation studies based on microscopic approaches used to calculate PCEs for heavy vehicles driving roundabouts. Effects on capacity and PCE estimations based on models currently employed in roundabout analysis are also compared. The results obtained in this study aim at providing an overview of the existing knowledge concerning the estimation of PCEs at roundabouts and can represent a guideline for transportation engineers in the design and capacity analysis of roundabouts where mixed traffic conditions occur.

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

Geometric factors influencing entry capacity of roundabouts under heterogeneous traffic conditions

Roundabout entry capacity is influenced by geometric features of the roundabout, traffic flow characteristics, vehicle and driver characteristics, as well as, environmental conditions. The major methods for estimating roundabout entry capacity are based on either gap acceptance theory or on empirical relations. Roundabout geometry is the sole aspect which can be entirely manipulated by the designers to improve the entry capacity. Limited studies have been conducted to analyze the influence of geometric elements of a roundabout on its capacity, for heterogeneous traffic conditions. Many developing countries like India, Malaysia, Indonesia etc., have heterogeneous traffic conditions on their roads. Data is collected from twenty-one entries of six roundabouts, where heterogeneity in traffic is observed. Seven different vehicle categories are considered such as motorised two wheeler, three wheeler, car, mini bus, light commercial vehicle (LCV), heavy commercial vehicle (HCV) and bus. A non-linear regression model is proposed to predict entry capacity, based on the nature of variation with individual geometric elements. Various combinations of independent variables are used to estimate entry capacity. The non-linear correlations among the geometric variables are checked. In comparison with the existing empirical models such as the LR942 regression model and German empirical model, the proposed regression model produced better estimates and much lower RMSE values. Approach width is found to have the highest impact on entry capacity. The entry capacity is found to be negatively influenced by entry angle. Circulating flow is considered in terms of per metre width against the usual convention. This modification incorporates the effect of circulatory roadway width also into consideration. The circulatory roadway width has a diverse effect on entry capacity at different levels of circulating flow. Modification of inscribed circle diameter and circulatory roadway width is suggested as a potential solution for improving entry capacity. Sensitivity analysis is carried out to quantify the effect of variation of entry angle, circulatory roadway width, inscribed circle diameter and approach width on entry capacity based on the non-linear model. The sensitivity plots can be used to make subtle geometric modifications to improve capacity at congested roundabouts.

Micro-level safety risk assessment model for a two-lane heterogeneous traffic environment in a developing country: A comparative crash probability modeling approach

Introduction: There have been a number of studies that have led to the development of safety risk assessment models to quantify the probability of crash frequencies on roadway facilities (both at micro- and macro-levels), over a specified time period. However, past research has rarely focused on heterogeneous traffic conditions in developing countries. Method: This paper puts forward several models related to the traditional count approach to estimate crash frequency at a micro-level in a non-lane based bi-directional heterogeneous traffic environment. The paper shows the results of dispersion, zero-inflation, and random heterogeneity effects of different exogenous factors by comparing Poisson (P); Negative Binomial (NB); random and fixed parameter Zero-Inflated Poisson (ZIP); and Latent Class Models (LCM). The empirical analysis is based on data from a section of a major national highway in Bangladesh. The performance of the models was validated using different statistical goodness-of-fit measures that compared the estimated and observed average crash frequencies at individual locations. With the identification of the most significant influencing factors, the paper discusses the practical policy implications using partial effects analysis and spatial distribution. Results: It was found that the Zero-Inflated Random Parameter model gives a slightly better statistical fit when compared to alternative approaches. Practical applications: This micro-level modeling approach would be useful to identify significant crash risk factors; to prioritize road sections according to their safety level; to select site-specific appropriate counter-measures; and devise proactive target oriented safety management strategies. Thus, the results shown here could be a point of reference in the planning, designing, maintaining, and managing two-lane highway sections in developing countries.

Estimation of saturation flow under heterogeneous traffic conditions

Realistic estimation of saturation flow in passenger car units (PCU) is a challenging task for traffic engineers in developing countries. This paper introduces a new methodology for the determination of saturation flow in PCU/h under heterogeneous traffic conditions based on the area occupancy (AO) concept. AO is the proportion of time a set of observed vehicles occupies an observation region on a chosen stretch of a roadway. Traffic data collected from seven signalised intersections were analysed to determine AO and the equivalent number of standard car spaces (Ncs). Saturation flow in PCU/h was then estimated based on the Ncs. For easy and quick estimation of the saturation flow in PCU/h from the observed saturation flow in vehicles per hour, the occupancy conversion factor (OCF) is introduced. A multiple linear regression equation is proposed for prediction of the OCF. The proposed model is expected to circumvent the difficulties in the estimation of saturation flow adopting individual values of PCU. The results show that an increase in the compositional share of vehicles larger than a standard car increases the OCF while an increase in the percentage of two- and three- wheelers decreases the OCF.

A multi-commodity network flow model for railway capacity optimization in case of line blockage

ABSTRACTIn this study, a multi-commodity network flow model is proposed to optimize the railroad capacity under temporary line blockage. The proposed model enables the assessment of residual railroad capacity under heterogeneous traffic condition. The model searches for an optimized train timetable to maximize the number of possible train paths by maintaining acceptable percentages of delayed trains. Computational experiments are conducted on instances of Iran railway to evaluate the performance of the model regarding computational efficiency and solution quality. The outcomes demonstrate an average optimality gap of about 3.7% which quantifies the effectiveness of the optimization model within a reasonable computational time. The output of the optimization model has been compared with the UIC406 (International Union of Railway) standard. The proposed optimization model could generate a more realistic solution in comparison with UIC406 method. According to the obtained result, the maximum capacity of the rail line increases by approximately 26.7% compared with UIC 406 code.

Exploring stage-wise pedestrian-crossing behavioral patterns at vulnerable urban midblocks: a perspective under heterogeneous traffic conditions

Due to the rapid increase in the vehicular traffic, pedestrians in urban cities need to look for space for movement on roads, particularly while crossing at midblocks. While accepting the gap, pedestrians have to adjust their crossing speed and behavior that can be influenced by numerous factors in their surroundings while crossing. Generally, in developing countries like India, pedestrians as well as drivers do not follow the traffic regulation, thus, there is a chance of conflict between pedestrians and vehicles due to limited available space on road. The intensity of these conflicts depends on prevailing traffic volume on road, either motorized traffic or nonmotorized, like pedestrians and other surrounding variables. Present study is focused on demonstrating a detailed methodology adopted for data collection at midblock sections of urban roads first, under prevailing crossing patterns observed at nine study sections, and then further describing results pertaining to analysis of patterns emerging out of pedestrian crossing behavior. Different parameters describing pedestrian characteristics like age, gender, crossing times, waiting times and crossing speed of pedestrians, safety margin, type of movement, crossing stage, and approaching vehicle speed have been considered for the analysis. In addition to this, it is proven that safety margin value is significantly lower in oblique crossing (non/partial compliance) pattern than perpendicular (full-compliance) crossing. Study results show that the stages and type of movement/pattern, while crossing, that is, perpendicular or oblique is an important parameter in analyzing behavior of the crossing at midblock in developing countries like India.

Deriving capacity and level-of-service thresholds for intercity expressways in India

ABSTRACTThe knowledge of roadway capacity and level-of-service (LOS) are important for the effective planning, design, analysis, and operation of a roadway network. There is a limited body-of-knowledge available about highway capacity and LOS of intercity expressways in Asian countries, including India, where traffic composition and driver behavior are considerably different from that of the developed world. The primary objectives of the paper are to estimate capacity and to propose a new methodology of developing LOS thresholds for such intercity expressways. A microscopic traffic simulation model was developed using VISSIM and was calibrated and validated using real-world vehicular trajectory data. The LOS thresholds are then established using k-means clustering technique and further cross-validated statistically observing change in slopes of plots explaining speed–flow and speed–density variations. The capacity and LOS methods proposed in this paper are generic and should be applicable to other Asia-Pacific countries with heterogeneous traffic conditions.

2-D noise maps for tier-2 city urban Indian roads

Abstract In today’s era, vehicular noise pollution has been identified as a serious danger that influence the attribute of the urban regions. To identify the influence of noise effects, noise maps are very useful. A noise mapping study has been carried out to study the propagation of urban road traffic noise in the areas along with field measurements. The computer simulation model (Sound- PLAN software) is used to developed noise maps. In developing nations like India, traffic composition is heterogeneous. These traffic compositions contain vehicles, which have different sizes, speeds variations and operating systems. Because of fluctuating speeds, deficiency of lane disciplines, and non-authorized parking on main road lanes, honking events becomes inevitable, which changes and affects the urban soundscape of nations like India. Due to horn events (heterogeneous traffic condition), noise level (LAeq) increase by 0.5–8 dB (A) as compared to homogeneous traffic conditions.

An advanced approach for estimation of PCU values on undivided urban roads under heterogeneous traffic conditions

ABSTRACTMajority of the existing studies on passenger car unit (PCU) estimation are limited to inter-urban and divided urban roads. The characteristics of traffic on undivided urban roads are completely different from those on divided roads. This study aims to estimate the PCU values on undivided urban roads with varying traffic conditions. Estimation of PCU requires speed information for individual vehicle categories. Hence, a universal Kriging-based speed prediction model was developed and utilized for PCU estimation. The model was constructed based on the classified traffic volume and speed data that were collected by videography method on undivided urban road segments in different cities in India. The proposed model was utilized to study the effects of traffic volume, traffic composition, and carriageway width on PCU. An alternative approach of ‘Stream Equivalency Factor’ has also been suggested in this paper. Use of this approach can simplify the process of determining the homogeneous equivalent of a mixed traffic flow.

Evaluation of pedestrian safety margin at mid-block crosswalks in India

Amplified pedestrian-vehicle interaction especially at urban midblock crossings have ensued higher pedestrian fatalities and such situations further exacerbates under heterogeneous traffic conditions and therefore, it becomes indispensable to evaluate pedestrian safety especially at urban midblock crossings. To comprehend the factors influencing pedestrian safety, video-graphic survey was conducted at four urban midblock crossings located in different parts of India. Data was extracted from the video and model was developed using Multiple Linear Regression (MLR) Technique. The data includes mainly pedestrian demographics, vehicle characteristics and roadway characteristics out of which, eleven variables are identified and analysed, which are found to be significant. Regression model indicated that the PSM distinctly depends on the availability of gap in vehicular flow, pedestrian crossing behaviour and speed of the approaching vehicle. Further, it is found that safety margin increases with increase in pedestrian speed and vehicular gap, whereas the same decreases with rolling behaviour, while crossing the street. Elasticity analysis was also carried out among the different variables, wherein the vehicle speed, pedestrian speed and vehicle gap were found to be the most influencing variables, whereas, pedestrian age and platoon size had the least effect. It was also found that pedestrians are more likely to cross the road by maintaining least marginal vehicular gap with respect to light vehicles compared to heavier vehicles, highlighting that vehicle type influences pedestrian safety. Further, driver yielding behaviour significantly influences pedestrian safety. In addition, from the sensitivity analysis, it is corroborated that the safety margin against to pedestrian speed and vehicle speed increases with increase in the vehicle gap size. Moreover, PSM against waiting time decreases as the vehicle gap increases. The developed PSM model can enable engineers and planners to evaluate safety at existing crossings at unprotected mid-blocks. The results of the PSM model may be useful to design pedestrian facility and suggest appropriate remedial measures to enhance pedestrian safety.

Development of passenger car unit based on acceleration noise for urban arterials

Vehicular traffic in developing countries like India is highly heterogeneous in nature. For effective planning, design, operation and management of highways, determination of traffic volume in a standard unit is a prerequisite. Interactions among vehicles under heterogeneous traffic conditions are highly complex. The passenger car unit (PCU) was therefore developed to represent the amount of impedance caused to the flow of traffic by a vehicle type in comparison with that of a standard vehicle (usually a passenger car). Since urban roads are marked by frequent changes in acceleration–deceleration characteristics, the interaction among various categories of vehicles can be realistically determined using a parameter that represents the change in acceleration/deceleration. A methodology for determining the PCU values of vehicles based on the concept of acceleration noise was developed in this study. The PCU for a study section was determined as the ratio of the variance of acceleration noise of the vehicle under consideration to that of a passenger car. PCU values were determined for four basic categories of vehicles on four-lane divided urban road stretches.

Development of a simulation platform for safety impact analysis considering vehicle dynamics, sensor errors, and communication latencies: Assessing cooperative adaptive cruise control under cyber attack

While safety is one of the most critical contributions of Cooperative Adaptive Cruise Control (CACC), it is impractical to assess such impacts in a real world. Even with simulation, many factors including vehicle dynamics, sensor errors, automated vehicle control algorithms and crash severity need to be properly modeled. In this paper, a simulation platform is proposed which explicitly features: (i) vehicle dynamics; (ii) sensor errors and communication delays; (iii) compatibility with CACC controllers; (iv) state-of-the-art predecessor leader following (PLF) based cooperative adaptive cruise control (CACC) controller; and (v) ability to quantify crash severity and CACC stability. The proposed simulation platform evaluated the CACC performance under normal and cybersecurity attack scenarios using speed variation, headway ratio, and injury probability. The first two measures of effectiveness (MOEs) represent the stability of CACC platoon while the injury probability quantifies the severity of a crash. The proposed platform can evaluate the safety performance of CACC controllers of interest under various paroxysmal or extreme events. It is particularly useful when traditional empirical driver models are not applicable. Such situations include, but are not limited to, cyber-attacks, sensor failures, and heterogeneous traffic conditions. The proposed platform is validated against data collected from real field tests and tested under various cyber-attack scenarios.