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Globally, the increase in pedestrian fatalities due to road traffic crashes (RTCs) on transport networks has been a major concern. In low- and middle-income countries (LMICs), pedestrians face a high risk due to RTCs on the rural highway network. The safety evaluation methods, such as observational before-after, empirical Bayes, full Bayes, and cross-sectional methods have been used to identify risk factors of RTCs. However, these methods are data-intensive and have associated limitations. Thus, this study employed a matched case--control method to identify the risk factors of fatal pedestrian crashes. This study utilized crash, traffic volume, speed, geometric, and roadside environment data of a 175 km six-lane rural highway in India. The identified major risk factors, such as clear zone width, the presence of habitation, service roads, and horizontal curve sections, increase the likelihood of a fatal pedestrian crash. This study provides specific insights for modifying the speed limit of highway sections passing through habitation. On such highway sections, designers should shift focus to pedestrian safety. It also suggests that the service road design needs to be reconsidered from a pedestrian safety viewpoint. The proposed method can be used in any other setting having similar traffic and socio-economic conditions. [ABSTRACT FROM AUTHOR]

This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NO x (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH 3 (ammonia), 0.26 Gg for N 2 O (nitrous oxide) and 11.38 Gg for CH 4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (>50 %) across all pollutants except PM, BC and NO x , and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NO x emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022). [ABSTRACT FROM AUTHOR]

This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first the traffic volume and congestion (travel time delay) relation is applied to model the 24-hour traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning-evening rush hours. We estimated an annual emission of 1.82 Gg for PME (Exhaust particulate matter), 0.94 Gg for BC (Black Carbon), 0.75 Gg for OM (Organic matter), 221 Gg for CO (Carbon monoxide), 56 Gg for NOx (Oxide of Nitrogen), 64 Gg for VOC (Volatile Organic Carbon), 0.28 Gg for NH3 (Ammonia), 0.26 Gg for N2O (Nitrous Oxide) and 11.38 Gg for CH4 (Methane) for 2018. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (> 50 %) across all pollutants except PME, BC and NOx, and within them the 2W (Two-wheeler motorcycles) are the major contributors. Diesel fuelled vehicles contribute most of the PME emission. Diesel and CNG vehicles have a substantial contribution in NOx emission. This study provides very detailed spatio-temporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022). [ABSTRACT FROM AUTHOR]

• The paved shoulder reduces the risk of fatal crashes. • The effect of paved shoulder width on the safety of VRUs, especially M2W users, has been assessed. • Paved shoulder improves the safety of M2W users and slow-moving vehicles on multilane highways. • The paved shoulder has limited safety benefits for rear-end only fatal crashes. • The matched case-control method is an effective viable safety evaluation method in limited crash data availability, as in LMICs. Research has revealed the safety benefits of shoulder improvements on highways are significant. The study aimed to assess the impact of paved shoulder width on the frequency of fatal crashes in case of heterogeneous traffic on a rural four-lane divided highway in India. A matched case-control design was employed to evaluate the safety effectiveness of the paved shoulder width on fatal crashes. The impact of shoulder widths on victims of motorized two-wheelers (MTW) users, slow-moving vehicles and rear-end fatal crashes were also analyzed. The study stretch was divided into segments of 100 m. Each segment was linked to the traffic volume, speed, geometric characteristics, and roadside hazards characteristics. Analysis of the crash data revealed that 39% of the total crashes are due to rear-end collisions, mostly occurring at nighttime. The model results are interpreted concerning segments with no shoulder as the baseline category. Model results suggest that paved shoulder has safety benefits for all road users up to 1.5 m shoulder width. The provision of paved shoulders reduced the risk of all fatal crashes and improved the safety of pedestrians and slow-moving vehicles. However, the safety of MTW users reduced on segments having paved shoulder width more than 2 m. Also, segments with a paved shoulder width of more than 1.5 m have a higher risk of rear-end fatal crashes than no shoulder segments. This study findings have a direct bearing on the geometric standards recommended by the road authorities in India. [ABSTRACT FROM AUTHOR]

The continuity equation involving traffic flow expresses the relationship between density, flow, and speed. Density equals the flow divided by space mean speed. The formulation of this equation in the year 1952 has two important assumptions. One assumption is that spacing and speed are constant, i.e., uncongested conditions with moderate to slightly high volumes. The other assumption is that homogeneous traffic prevails, vehicle composition is uniform and vehicles behave within strict lane discipline rules. To determine if the continuity equation is valid under nonhomogeneous traffic conditions, one performs an experiment involving data collection of density, flow, and speed at three midblock sites in India. Data collection occurred when uncongested conditions prevailed with moderate to slightly high volumes. Comparing the average density derived from observed densities in the field to the density derived from the continuity equation reveals whether or not the continuity equation accurately predicts average density under nonhomogeneous traffic conditions. Similar traffic operating characteristics served as the basis for grouping vehicles into five traffic entity types. The association between average density based on observed densities of nonhomogeneous traffic and density derived from the continuity equation had a correlation coefficient of +0.88 for light, four-wheeler type, +0.85 for heavy vehicle type, +0.90 for motorized, three-wheeler type, +0.83 for motorized, two-wheeler type, and +0.50 for nonmotorized, two- and three-wheeler type. Additionally, a nonparametric test, i.e., Wilcoxon signed-rank test, compared observed and derived densities. At a 95% confidence level, no significant difference existed between observed and derived densities of light four-wheeler type, heavy vehicle type, motorized two-wheeler type, nonmotorized two- and three-wheeler type, and between cumulative observed and cumulative derived density. Only in the case of the motorized three-wheeler type, the observed, and derived densities are significantly different. These moderate to strong correlations coupled with the results of the nonparametric test validate the application of the continuity equation when traffic is nonhomogeneous. [ABSTRACT FROM AUTHOR]

Implementing bus rapid transit (BRT) raises many challenging issues of technical, operational, and institutional nature. The present study sets the groundwork for a methodology that can be used to selectively target corridor for BRT modeling in India. Traffic quality parameters, such as traffic flow, speed, travel time, delay time, stop time, and fuel consumption, were modeled to investigate the impact of BRT as compared to present day mixed traffic on traffic and commuter mobility. A microsimulation traffic model was developed for BRT and mixed traffic systems. A developed microscopic model was validated with field measured data using statistical methods and was found good against measured data. A dedicated lane-based public transport system shows the promising results and has to play a significant role in developing sustainable transport systems. These findings can be used to form the basis for developing public transport corridor in present Indian traffic conditions. [ABSTRACT FROM AUTHOR]

• Urban freight flow estimation for developing urban settings like India. • Integration of direct flow estimation models with origin destination synthesis model. • Spatio-temporal Kriging and machine learning direct flow estimation models performance comparison. • Demonstration of road link speed estimation using map application programming interfaces. This paper presents an innovative methodological framework for determining urban freight flows using a multimodal origin–destination synthesis (ODS) model, which we ran with a novel combination of primary and secondary data. Primary data included classified traffic volume counts at limited locations, whereas secondary data, enriched with certain techniques, came from (a) map application programming interfaces used to extract real-time speeds and calibrate a disaggregated speed–volume relationship and (b) advanced techniques for estimating direct flow models (e.g. spatio-temporal Kriging and machine learning models). The paper also discusses the sensitivity of multimodal ODS models to variations in base–seed matrices. [ABSTRACT FROM AUTHOR]