Highways In India Research Articles

Developing Policy Framework of Dynamic Toll Pricing in India

There are 543 toll plazas across the National Highways and State Highways in India and most of them are currently operating under Manual Toll Collection (MTC) system. The Government of India has recently adopted Electronic Toll Collection (ETC) system over MTC system, but, due to the technical constraints of toll plazas, they are either operating with both ETC and MTC systems or with MTC system only. The motive of switching from MTC to ETC is to reduce congestion and delay time. However, due to the fix toll charges for a vehicle type and heterogeneity in traffic mix, the peak hour traffic causes congestion that ultimately returns to enormous delay to users. The present study proposes the policy framework of Dynamic Toll Pricing (DTP) that alleviate the congestion at toll plazas by consisting of shifting traffic volume from peak/congested hours to off-peak/non-congested hours. This type of pricing proved to be one of the methods to control the traffic by elevating the toll in peak hours and thus giving discounts in off-peak hours. Such type of study about dynamic toll is not yet carried out for Indian scenario where traffic is highly heterogeneous. Hence, the main goal of the present study is to evaluate the DTP for the Indian condition and thus to examine the effect of discount and time saving on the shift in peak hour traffic demand. The observations revealed that most of the respondents are willing to shift in the morning peak hour than evening peak hour. The maximum shift was observed for small cars and for 25 % discount in toll charges. Further, the price elasticities of demand are calculated and are found to vary between -0.03 and -1.19 i.e. with 1 percent of discount the traffic volume changes between 0.03 % to 1.19 %. The output of the present study may set up a framework for DTP in India and may be used for analysing the travel choice behaviour models in future studies.

Automatic Toll Collection System and Detection of Theft Vehicle by using RFID

The road transportation in India has growing day by day. The Indian road network carries about 65 percent of its Goods and about 85 percent of passengers. The national highways in India are now increased from 44,076 miles to 88,313 miles in 2018 to 2019. Along these road networks there are about 450 toll plazas totally in India. These toll plazas contribute some major part of India’s economy, it is estimated the toll revenue can swell up to 1 lakh crore rupees in next five years. In spite of this enormous growth the toll plazas have huge traffic during peak most of the time which incurs delay and loss human hours to surpass the toll. The proposed system focuses on an automatic toll collection system which will automatically debit the amount from vehicle owner’s bank. The automated registration and collection are based on using the RFID chip which is amalgamated in the vehicle’s windshield. By this method, the information about registration ID of the vehicle can be obtained therefore stolen vehicle can also be detected by this system as the vehicle ID is linked to the user’s account. Thus, this system provides fast and efficient surpassing of toll plazas without any delay.

Modeling Operating Speed Using Continuous Speed Profiles on Two-Lane Rural Highways in India

AbstractThe geometric elements of the road, such as tangents and curves, play a vital role in road safety because significant crashes are reported on the horizontal curves and tangent-to-curve tran...

Development of Model for Road Crashes and Identification of Accident Spots

The aim of this study is to assess the safety of multi-lane rural highway in India. This paper shows the application of a generalized linear modeling technique for the analysis of road accidents on the Indian National Highway. Speed, traffic flow and road characteristics data on four-lane dived rural highway in Dahod are analyzed. The study proposes a novel approach to include average daily traffic (ADT) and average spot speed (AS) in the accident prediction model for a rural highway. The model has been developed for accidents per km as a dependent variable and significant variables such as Junction density, village settlement nearby, ADT, AS as independent variables. The findings from the model offer a better estimate of accidents for a multilane divided rural highway. Statistical Models cannot fully reflect the characteristics of each section due to the heterogeneous nature of road accidents, so the association rule mining technique has been used to identify accident spots as it can deal with the heterogeneous nature of accidents. Accident spots have been assessed by correlating various attributes to the severity of the accident (fatal, non-fatal). This research will help to improve road safety on rural highways.

The Ecological Impact of Transportation Infrastructure

Abstract There is a long-standing debate over whether new roads unavoidably lead to environmental damage, especially forest loss, but causal identification has been elusive. Using multiple causal identification strategies, we study the construction of new rural roads to over 100,000 villages and the upgrading of 10,000 kilometers of national highways in India. The new rural roads had precisely zero effect on local deforestation. In contrast, the highway upgrades caused substantial forest loss, which appears to be driven by increased timber demand along the transportation corridors. In terms of forests, last mile connectivity had a negligible environmental cost, while expansion of major corridors had important environmental impacts.

Identifying Critical Safety Issues on Two-Lane National Highways in India – A Case Study from NH 117 and NH 60

Safety performance of two-lane highways is a primary concern for developing countries such as India. So, a study on the identification of risk factors on such highways is of immense interest in mitigating road accidents. Although, there are several recognized practices for identifying road safety deficiencies, most of them depend on accident records. However, Road Safety Audit (RSA) is a cost-effective proactive tool to check that the roads have been designed and built to the highest safety standards for all types of road users. It is an efficient method for improving road safety, especially in countries like India, where there is a lack of adequate maintenance of accident database. The present study aims to identify the critical safety issues observed during RSA on the two major two-lane undivided highways in the state of West Bengal, India. Both the highway carries a considerable amount of traffic and passes through numerous built-up areas, markets and industrial belts. Several risk factors were identified at different hazardous locations along the highway stretches during the RSA. Lack of infrastructure, interaction of vulnerable road users (VRU) with high-speed traffic, and faulty geometric design are some of the most alarming safety deficiencies identified through the audit process. The insights obtained from the RSA report could not have been gained from the accident reports alone. Finally, countermeasures were suggested based on the observations made during the RSA.

Passenger Car Equivalent Estimation for Rural Highways: Methodological Review

Level of service (LOS) determination is carried out with respect to the base stream which contains only passenger cars in the traffic stream. The actual traffic stream rarely contains only passenger cars, giving rise to the heterogeneous traffic conditions. Traditionally, passenger car equivalent (PCE) values are used to represent the heterogeneous flow in terms of passenger car flow. The objective of this review was to understand the basis of different PCE estimation methods and thereafter assess their applicability for the heterogeneous traffic conditions prevalent on the rural highways in India. To fulfil this objective, different PCE studies have been reviewed with the hope of finding the factors which influence the PCE estimation process. Thereafter, the ways to incorporate such factors for the PCE estimation have been discussed in this paper. Based on the review, it was found that the proper use of the simulation model and the selection of appropriate performance measure for defining the LOS are the two major factors that influence the PCE estimation process. Further, the concept of aggregate PCE should be used for representing the heterogeneous flow in terms of passenger car flow in the case of developing countries. The paper proposes speed drop as the performance measure for defining the LOS on rural highways. The paper provided few suggestions that the authors feel will improve the shortcomings of the speed-area method and modified density method.

Safety Performance Functions for Fatal Crashes on National Highways in India

This paper investigates factors contributing to fatal crashes on three National Highways (NHs) sections in India by developing safety performance functions. The generalized linear model technique is used for analysing linear and non-linear effect of continuous and categorical predictor variables on discreet dependent variable (fatal crashes) separately for each NH segments. In India, NHs are not usually access controlled, and heterogeneous vehicles travel on highways. The probable explanatory variables are short-listed after thorough literature review, and availability of data. These variables comprise of vehicular traffic (ADT), highway elements, and roadside land use. The fatal crash data for the past five years (2009-2013), traffic and highway inventory data have been collected for three NHs having varying lane configuration: two-lane NH-8, four-lane NH-24 and six-lane NH-1. The study results revealed negative binomial regression model fit the data statistically, and also identified number of statistically significant variables (‘segment length’, ‘roadside land use’, ‘presence of service road (SR)’ and ‘terrain type’) to estimate fatal crashes at NHs segments. The results of the safety performance functions (SPFs) showed that out of seven explanatory variables examined for each NH (segments), the significant explanatory variable is found to be ‘segment length’ in km for all three models of NHs (segments). Other significant variable is ‘land use’ along NHs for both two-lane NH-8 and four-lane NH-24. Similarly, the explanatory variables ‘presence of SR’ and ‘terrain type’ are found significant for four-lane NH-24 and two-lane NH-8 respectively. ADT (in vehicles) being an important variable in fatal crash modeling, is kept as an offset variable in each model.

Impact of Side Friction on Performance of Rural Highways in India

AbstractAbutting land-use patterns always play an important role in the performance of a road section. Land use along rural highways in developing countries is significantly different from that in ...

Determinants of commuter exposure to PM2.5 and CO during long-haul journeys on national highways in India

National Highways (NH) are the major road networks linking cities but exposure studies during long commutes on highways are limited. We assessed exposure concentrations of fine particles ≤2.5 μm in diameter (PM2.5) and carbon monoxide (CO) inside bus, ac (air-conditioned) and non-ac car and on an Indian NH over 200 km length. A total of nine round journeys were made in three modes. Analysis of variance (ANOVA) and generalized linear model (GLM) were applied to quantify the contribution of determinants that may explain the variability of exposure concentrations and their association with in-vehicle temperature and relative humidity (RH). The highest and lowest exposures concentrations to PM2.5 were observed in non-ac car (89 ± 32 μg m−3) and the ac car (55 ± 19 μg m−3). Exposures concentrations in non-ac car were higher during in-city travel (113 ± 36 μg m−3). The average CO exposure concentrations were highest in ac car (2.0 ± 0.9 ppm). Results of GLM analysis suggested that travel mode, highway segments (in/out-city) and the journey times are key determinants of personal exposure concentrations. Travel mode for PM2.5 (15%) and NH segments for CO (21%) explained maximum variability. Altogether, these explained 33% and 57% of the variability in PM2.5 and CO exposure concentrations, respectively. PM2.5 consists of soot, mineral and fly ash that are a proxy of fresh exhaust emissions, re-suspended road dust and industrial emissions, respectively. Additionally, EDX analyses revealed an abundance of Si, Al, Ca and Pb, confirming re-suspension, brake/tire wear and construction dust as important sources.

Support vector machine model for prediction of accidents on non-urban sections of highways

A support vector machine (SVM) model is proposed for accident prediction on non-urban sections of highways as an alternative to conventionally used fixed-effect or random-effect negative binomial (FENB/RENB) regression models. Road accident data over a period of 8 years on different sections of eight highways in India were collected from police records. In addition, data relating to road geometry, traffic and road environment related variables were collected through field studies. A total of 222 data points was gathered by dividing highways into sections with certain uniform geometric characteristics. Two modelling approaches were used (RENB and SVM models) to predict accident frequencies. The results showed encouraging performance of the SVM model in comparison with the RENB model in terms of both the correlation coefficient and root mean square error values. The SVM, originating from statistical learning theory, can better solve over-fitting and local minima problems and the results indicate that this approach can effectively be used as an alternative to the RENB approach if the sole aim is to predict crashes. The results clearly indicate that, to improve safety on Indian highways, minor access roads to highways and service roads need to be properly designed and controlled and the dispersion of speeds needs to be reduced.

Factors contributing to motorcycle fatal crashes on National Highways in India

ABSTRACTThis study analyses fatal crash patterns, and identifies the risk factors contributing to motorcycle versus non-motorcycle fatal crashes using binomial logistic regression on two-, four- and six-lane National Highways (NHs) in India utilizing police fatal crash data. The distribution of victims’ mode by striking vehicles shows that percentage share of striking vehicles (truck) against the victims’ vehicles (motorcycle) is 44%, 52% and 37% on two-lane NH-8, four-lane NH-24 and six-lane NH-1, respectively. Nine explanatory variables pertaining to fatal crash, victim, roadway and environment are considered for the model (using combined data of cited three NHs). The results of the logistic regression model (motorcycle versus non-motorcycle fatal crashes) show that for variable ‘collision type’, likelihood of occurrence of ‘rear-end’, ‘sideswipe’ and ‘head-on’ fatal crashes are 42-times, 35-times and 25-times more than ‘hit pedestrian’ respectively. Similarly, for variable ‘number of vehicle’, likelihood is thrice as ‘single-vehicle’ than ‘two or more vehicles’; and, for variable ‘number of lane’, probability is more on ‘two-lane’ NH-8 than ‘four-lane’ NH-24. Based on the study results, it is recommended to upgrade two-lane (undivided carriageway) to four-lane (divided carriageway) NHs to reduce ‘head-on’ collision.

Headway distribution models of two-lane roads under mixed traffic conditions: a case study from India

IntroductionThe time headway of vehicles is of fundamental importance in traffic engineering applications like capacity, level-of-service and safety studies. Further, the performance of traffic simulation depends on inputs into the simulation process and ‘accurate vehicle generation’ is critical in this context. Thus, it is important to define headway distribution pattern for the purpose of analyzing traffic and subsequently, taking infrastructure related decisions. In so far, majority of the researches on this subject are based on homogeneous traffic and effects of mixed traffic especially on two-lane roads are yet to be culminated. The present study, thus, aimed at investigating headway distributions on such roads under mixed traffic situation.MethodsField study was conducted on two-lane highways in India that exhibits heterogeneity in its traffic composition. Contestant headway distribution models were evaluated and four distribution functions namely, log-logistic, lognormal, Pearson 5 and Pearson 6 were considered while modeling the headway data. The appropriate models were selected using a methodology based on K-S test and subsequent field validation.ResultsLog-logistic distribution was found appropriate at moderate flow whereas, at congested state of flow it was Pearson 5. However, at unstable flow nearing capacity, both, following and non-following components of headways were observed to follow different distributional characteristics. Nomographs are developed for calculating the headway probabilities at different flow levels considering the appropriate distribution models. ‘Probability of headway less than‘t’s’ increases with the flow rate and rate of such increase is considerably high for headways 7.5 s or more. This attributes to the fact that at heavy flow more vehicles are entrapped inside platoons and they move in following with shorter headways. Further, a comparison was made between the headway probabilities obtained in the current study and road segments that exhibit more or less homogeneous traffic. It was found that at moderate flow level proportion of shorter headways are considerably high under mixed traffic.ConclusionsThe present paper demonstrates the effect of mixed traffic on distribution of time headways of two-lane roads. Presence of slower vehicles in such traffic leads to frequent formation of platoons, thereby, increases the risk taking behavior of drivers’ while overtaking. As a result, proportion of shorter headways increases resulting in highly skewed observations. Thus, the study proposed Log-logistic distribution under medium flow since it can model events which have ‘increased initial rate’ and Pearson 5 under heavy flow to model ‘highly skewed data’. The model outputs were accordingly compared with other studies and were found to explain the mixed traffic characteristics satisfactorily. The present study, thus, creates a starting point of further initiatives aimed at establishing a robust method of modeling headways on two-lane roads with mixed traffic.

A comparison of personal exposure to air pollutants in different travel modes on national highways in India

People often travel a long distance on highways to the nearest city for professional/business activities. However, relatively few publications on passenger exposure to pollutants on highways in India or elsewhere are available. The aim of this study was to examine the contribution of different travel modes to passengers' pollutant exposure for a long distance travel on a national highway in India. We measured PM2.5 and CO exposure levels of the passengers over 200km on a national highway using two portable air monitors, EVM-7 and EPAM-5000. Personal concentration exposures and per min-, per hour-, per trip- and round trip mass exposures for three travel modes were calculated for 9 trips. Association between pollutants and weather variables were evaluated using levels Spearman correlation. ANOVA was carried out to evaluate the influence of travel mode, the timing of trips, temperature and RH on personal exposures. On an average, PM2.5 personal concentration exposure levels were highest in the car (85.41±61.85μgm−3), followed by the bus (75.08±55.39μgm−3) and lowest in the car (ac) (54.43±34.09μgm−3). In contrast, CO personal exposure was highest in the car (ac) (1.81±1.3ppm). Travel mode explained the highest variability for CO (18.1%), CO2 (9.9%), PM2.5 (1.2%) exposures. In-city mass exposures were higher than trip averages; PM2.5:1.21–1.22, 1.13–1.19 and 1.03–1.28 times; CO: 1.20–1.57, 1.37–2.10 and 1.76–2.22 times for bus, car and car (ac) respectively. Traveling by car (ac) results in the lowest PM2.5 exposures, although it exposes the passenger to high CO level. Avoiding national highways passing through cities can reduce up to 25% PM2.5 and 50% CO mass exposures. This information can be useful for increasing environmental awareness among the passengers and for framing better pollution control strategies on highways.

Speed Distribution on Two-Lane Rural Highways with Mixed Traffic: A Case Study in North East India

This work focuses on minimising inaccuracies in distributional assumptions of speed data on two-lane roads with heterogeneous traffic to improve accuracy in capacity and level of service analysis. Accordingly, field study was conducted on a two-lane highway in India that exhibits heterogeneity in its traffic composition. Two distribution functions, namely, normal and logistic were examined for the observed speed data. The appropriate function was chosen using a methodology based on K–S test and field validation. Logistic distribution function was found to exhibit its aptness in describing speed under such traffic and was, thereby, considered in estimating the limiting speed of slower vehicles that tends to obstruct the flow of traffic. Vehicles that move at or below this speed cause delay to the faster ones resulting in formation of platoons at moderate and heavy flow when passing is restricted. Since the percent time-spent-following, a performance measure to assess level-of-service of two-lane highways, considers proportion of vehicles that are trapped inside platoons, it is imperative to estimate the limiting speed of slower vehicles correctly to approximate the delayed vehicles.

Preferred time headway of drivers on two-lane highways with heterogeneous traffic

This paper presents an investigation on the adequacy of one of the major performance indicators for two-lane highways, the percent-time-spent-following (PTSF) under changing driver’s behavior in choosing headways. Field study was conducted on a two-lane highway in India that exhibits heterogeneity in its traffic composition and a wide range of flow levels was covered while collecting data. The appropriate headway distributions were selected based on goodness-of-fit test. Exponential or Erlang distributions exhibit their aptness in describing headways up to a volume to capacity ratio of 0.3 and gamma and exponential distributions were compatible for headway data corresponding to a volume to capacity ratio of 0.4 and above. Around 40% drivers were observed to adopt headways 2 s or less at heavy flow when a car-following situation prevails; these headways are considered unsafe in several instances. Further, speed–headway relationships were established to assess a headway threshold beyond which vehicles could be considered free. Empirical investigation indicates a value of about 6 s under such traffic unlike 3 s as considered in PTSF estimation. Another major implication on PTSF is a few drivers move in a platoon by choice even if they have a gap of more than 6 s and passing opportunities.

Effects of access, geometric design, and heterogeneous traffic on safety performance of divided multilane highways in India

ABSTRACTSafety of the national highways (NHs) has been a major concern in India. Using 5 years of crash data from a 65-km stretch of a divided multilane NH, this study employs random parameter panel data models to identify factors affecting total crashes, rear-end and head-on crashes. Besides geometric design elements, this study focuses on the effect of access management strategies such as provision of service lane and presence of median opening on crash types. To capture the effect of mixed traffic on crash occurrence, vehicle composition is considered in addition to average daily traffic (ADT). Results suggest that the effects of segment length and ADT are generally fixed and consistent across crash types, but there exists variation in safety performance of horizontal alignment, access management strategies, and type of vehicles. Although the coefficient for proportion of motorized two wheelers is found to be random for rear-end crashes, higher proportions of truck traffic are found to be always associated with higher head-on collisions. Although segments with service lanes are associated with fewer rear-end and head-on crashes, median opening presence is found to increase both of these crash types even though the effect on total crashes is random.

Factors Contributing to Motorcycle Fatal Crashes on National Highways in India

Abstract The objectives of the study are to analyse fatal crash patterns, and to identify the factors contributing to motorcycle fatal crashes. An attempt is made to establish relationship between motorcycle versus non-motorcycle fatal crashes and probable contributory factors for three National Highways in India using binomial logistic regression. The distribution of victims’ mode by striking vehicles shows that per cent share of striking vehicles as truck against the victims’ vehicles, i.e., motorcycle are 44%, 52% and 37% on two-lane, four-lane and six-lane NHs respectively. The results of the model (motorcycle versus non-motorcycle fatal crashes) show that for variable “collision type”, likelihood to occur rear-end, sideswipe and head-on collision are forty-two times, thirty-five times and twenty-five times more than hit pedestrian respectively; for variable “number of vehicle”, likelihood is thrice as “single vehicle” than “two or more vehicles”; and, for variable “number of lane”, probability is more on two-lane NH than four-lane NH. To reduce the likelihood of motorcycle fatal crashes especially head-on, rear-end and sideswipe collisions on NHs, it is recommended that riders including pillion riders’ use properly fastened standard helmets and compulsorily use of reflective tapes on motorcycles to make them more conspicuous in night.

Analysing Road Regulation in India Through the Arie Freiberg Framework of Regulation

Road regulation, especially of National Highways in India, is done by administrative structures at the Union government level using legislation and policies. The legal framework in India alone has been found to be inadequate with reference to the issues of land records, boundary marking and citizen rights. What is legal becomes a matter of definitional and jurisdictional conflict. The Arie Frieberg toolkit of regulation offers six segments into which government regulation can be categorised. This study analyses the regulation of National Highways in India using this regulatory framework. The authors conclude that regulatory space in the context of National Highways uses a mixture of tools from the framework.

M5 model tree based predictive modeling of road accidents on non-urban sections of highways in India

This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2–6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down.