Urban Mobility Research in India

The COVID-19 pandemic has precipitated significant disruptions in urban transportation systems, challenging long-held urban planning practices. This study uses a convergent parallel mixed-methods approach to investigate the pandemic's impact on transportation spaces and urban design in India. Our research aims to (1) assess changes in transportation mode usage across demographic groups, (2) explore perceptions of traditional urban planning approaches, and (3) identify opportunities and challenges for sustainable transportation and urban spaces in a post-pandemic context. Quantitative analysis of survey data from 100 urban residents in major Indian cities revealed a 70% decrease in public transit usage, particularly among students and retirees. In contrast, private vehicle usage and active transportation modes like walking and cycling significantly rose. Chi-square tests indicated a significant association between occupational status and views on urban planning effectiveness (χ2(2) = 6.11, p = 0.047). One-way ANOVA showed notable differences in perceived mobility challenges across urban areas (F(2,97) = 4.28, p = 0.017, η 2 =  0.15). Regression analysis further linked decreased transit use to increased support for public transit enhancements (β = 0.61, p = 0.002). Qualitative insights from interviews with 15 urban planning experts underscored the need to rethink high-density, transit-oriented development in favor of more adaptable and resilient urban design strategies. This study contributes to urban resilience and sustainable mobility discourse, providing empirical evidence to guide policy interventions to foster more adaptable, equitable, and sustainable urban environments post-pandemic.

Urban mobility systems worldwide are buckling under unprecedented strains from rising urbanization, motorization, and climate imperatives. As legacy transportation paradigms falter, emerging data-driven solutions offer renewed hope. This pioneering research elucidates the transformational potential of artificial intelligence and machine learning (AI/ML) to enable intelligent mobility ecosystems through a robust mixed-methods approach. By synergizing insights from an exhaustive literature review encompassing cutting-edge technical scholarship and comparative case study analysis of pioneering global implementations, this work comprehensively investigates AI/ML applications across the urban mobility spectrum. The findings unveil profound enhancements in sustainability, efficiency, and equity outcomes achieved by leading cities on the vanguard of mobility innovation. However, equitably extending these capabilities remains contingent on purposeful governance, ethics, and social justice frameworks. This agenda-setting research crystallizes integral insights, lessons, and policy pathways to responsibly harness AI/ML's immense potential in service of accessible, green, and livable transportation futures for all. The knowledge generated propels both scholarship and practice at the nexus of technological capabilities and the public good.

Understanding the impact of geometrical features such as gradients, sharp curves, sight distances, etc. on the capacity of hill roads is crucial for efficient and safe traffic operations. This study aims to provide a comprehensive analysis of the influence of geometrical characteristics on the capacity of hill roads. By rigorously collecting and analyzing extensive data, this study investigates the correlation between diverse geometrical factors and road capacity. Data was collected from four different stretches on the Rishikesh-Badrinath Highway (NH-7), representing different topographical and geometrical conditions. The study also investigates potential interactions and the relationships between these factors. The findings highlight the critical role played by geometrical characteristics in determining road capacity on hill roads. Steeper gradients, sharper curves, and restricted sight distances were found to have a substantial negative impact on capacity. Additionally, the study investigates the estimation of capacity loss while negotiating from the tangent to the curved section of the hill road. The research provides valuable insights into the relationship between tangent gradient, capacity loss, and curve radius, which can aid in the design and planning of hilly roads. The findings highlight the importance of considering the effects of gradient and curve radius on road capacity.

In our country, there has been a limited amount of research conducted on inland water transport due to its relatively uncommon usage. However, it is crucial for cities with access to waterways to promote and optimize this affordable and sustainable mode of transportation. Kochi, a city in Kerala, is one such example with an existing inland water transport system that offers significant travel time reduction compared to road transport. Despite this advantage, the ridership of the water transport system in Kochi has not met expectations. With the road infrastructure and public transportation nearing saturation, there is a pressing need to prioritize and enhance the utilization of water transport for the city's future. The purpose of this study is to analyze Kochi's existing water transport system, evaluate its current usage, and assess both its strengths and weaknesses. A gap observed is that not much research has been done on water transport as it is not a common means of public transport service. The study investigates the demographic and socioeconomic profiles of the catchment areas surrounding these stations, as well as their accessibility, dispersal patterns, and overall characteristics. To assess the potential impact of proposed improvements, stated preference data and fuzzy logic mode choice modeling were utilized. By employing this approach, the study aims to evaluate how ridership may change following the implementation of recommendations derived from identified issues and concerns. In summary, the study delves into the existing water transport system in Kochi, taking into account its ridership and various characteristics of selected stations. By addressing the identified challenges, the aim is to encourage greater utilization of water transport and ensure its viability and effectiveness as a mode of transportation in the city. The concluding observations revealed a notable 15% rise in the modal shift towards water transport within the chosen catchment areas. This shift can be attributed to modifications in factors such as waiting times, passenger comfort, and the travel fare between road and water transport. Significantly, these factors were identified as the most crucial considerations for individuals when making decisions about their mode of transportation.

The design of transportation facilities mostly focuses on the need for vehicle and road geometries with less emphasis placed on pedestrian safety, comfort, and convenience. Pedestrian speed plays a crucial role in both transportation planning and the design of pedestrian facilities. So, the present study is focused on pedestrian crossing behavior at signalized intersections and mid-block sections considering the presence and absence of possible affecting parameters. Several parameters like the signal countdown display at the intersection, length of crossway, age and gender of the pedestrians, pedestrians moving alone or in a group, road geometry, and existing traffic volume in mid-block sections were considered while assessing the crossing characteristics of pedestrians. Considering the most effective parameters, multiple regression models were developed for estimating the speed of pedestrians while crossing through the signalized intersections and mid-block sections. The performance of the proposed models indicates an accurate assessment of pedestrian crossing speed in Indian traffic scenarios. Therefore, the present study will be useful for designing pedestrian signals and providing required facilities in mid-block sections to increase the ease and safety of pedestrian movements in crossways.

Transportation is a critical lifeline to sustain human lives and interactions during emergencies, facilitating the movement of commodities and services. However, the interconnected network system serving the affected region is vulnerable to disruptions during these events. Damaged network systems impede emergency response efforts and prevent the timely dispatch of personnel and supplies. Extreme weather events have increased significantly in recent years, and with the interdependency on transportation expected to grow, there is significant emphasis on the resilience of transportation systems. Studying the resilience of transportation systems for a region requires investigating a few fundamental research questions: (i) What are the dimensions of resilience in the transportation sector? (ii) What is the current state of research on integrating resilience into transport sectors? (iii) What are the gaps and barriers to attaining resilience? (iv) What is the scope of future research on improving the resilience of the transportation system? The purpose of this study is to provide the answers to these pertinent questions. This paper presents a comprehensive literature review to derive an in-depth understanding of integrating resilience into the transportation sector. Focusing on India’s transportation system, the study gives insight into its transportation sector and identifies critical opportunities for advancement. The review focuses on a specific timeframe to select relevant papers. The assessment and findings provide a greater understanding of the extent of resilience integration in India’s transport sector and its deficiencies.

Trip chaining is explored in this chapter, where individuals combine multiple activities into one trip to save travel time and cost. The study focuses on commuter choices and identifying the link between trip chain and mode choice. A questionnaire survey was conducted in Kota, Rajasthan, to collect data on travel patterns, trip chain behaviour, mode choice, and sociodemographic variables from December 2022 to February 2023. This complex relationship was examined using Structural Equation Modelling (SEM). The study identifies factors influencing trip chaining, including mode choice, income, travel expenditure, trip distance, vehicle ownership, education level, and age. Walking was the most significant mode, highlighting the importance of pedestrian infrastructure. The findings have implications for policymakers and urban planners to improve efficiency and sustainability by understanding these factors and promoting walkability and public transportation options.

Women are essential to our society due to their contributions to cultural diversity, education, health care, and economic growth. Women often face challenges and hindrances while commuting that affect their access to various locations. To create safe travel options, it is vital to understand the mode choice behaviour of women commuters and develop practical models to address their specific needs and issues. This paper examines the various factors that affect the mode choice of women commuters. The study was conducted in the capital city of the Kashmir region of the Union Territory of Jammu and Kashmir, India. A questionnaire survey resulting in 465 valid responses was conducted. The respondents predominantly belonged to the age group of 18–41 years and primarily used paratransit mode for commuting. A multinomial logit model was developed to analyse the factors affecting the mode choice of women commuters. The model results revealed that travel expenses, annual household income, car ownership, reason, and harassment are the most significant factors in predicting the mode choice behaviour of women commuters. Findings from this study show that women are three times more likely to feel safe in the car than in bus transportation. It can also be inferred that the car mode is considered the safest option among the modes of transportation analysed. The results of this study will be helpful for decision-makers in making policies for the promotion and betterment of women's mobility.

The availability of proper pedestrian infrastructures like sidewalks or crosswalks significantly affects the constructive performance of the road and also promotes walking commuters. The government of India has made significant investments in various pedestrian facilities including sidewalks, zebra crossings, foot-over bridges, and subways for safe walking and crossing of pedestrians. Despite the availability of these pedestrian crossing facilities, most of them are often disliked by pedestrians and are underutilized. The present study aims at identifying the factors that affect the utilization of various pedestrian crossing facilities. A questionnaire survey was conducted among 400 pedestrians in order to record their perception about the factors affecting the utilization of various pedestrian crossing facilities like Foot Over Bridges (FoBs) and crosswalks, at five different locations in Bhopal city. The descriptive analysis results reveal that the majority of the respondents are male students belonging to the age group of 15–29 years. The results show that 21% of the respondents have agreed that they would use the facilities when less no. of heavy vehicles are plying on the roads, 33% of the respondents have agreed that they would use the facilities when fellow pedestrians are present, 32% have agreed that they would use them when there are no criminal activities, 37% agreed on proper lighting, 47% highly agreed on the availability of direct approach, and 29% highly agreed on the presence of proper sidewalk. The findings observed from the study would help in formulating various policies measures and moderations for enhancing the usage of pedestrian crossing facilities in Bhopal and bringing down the pedestrian fatality rate at crossings.

At urban traffic intersections, stopping, idling, and acceleration behavior of traffic results in increased pollution levels and makes them pollution hotspots. Among all the pollutants, particulate matter (PM) significantly accelerates human mortality and morbidity rates. This study was conducted to find the effect of peak and off-peak traffic on PM exposure concentrations at a traffic intersection. PM data was collected for a week during the day for 15 min every three hours intervals at one of the busiest traffic intersections in Varanasi. Meteorological parameters like atmospheric temperature (AT) and relative humidity (RH) were also logged along with PM measurements to establish a relationship between PM exposure and meteorological parameters. The study found higher exposure values during off-peak and lower during peak traffic hours. The lowest exposure (26 µg m−3) was found during the early morning. In contrast, higher exposure (41 µg m−3) was observed during midday and evening off-peak traffic hours. In addition, the commuters are exposed to a higher inhaled dosage of PM2.5 during off-peak traffic hours. PM2.5 emitted from vehicle’s tailpipes and resuspension of road dust stays in the air as aerosol and does not disperse instantaneously. Thus, the accumulation of PM during morning and afternoon peak traffic might result in higher concentrations during midday and evening off-peak traffic hours. It might be one of the reasons behind higher exposure in off-peak traffic hours and lower exposure in peak traffic hours. However, the lowest PM exposure during the early morning might be due to continuous off-peak hours at night.

Access to proper means of mobility is a primary need that allows citizens to obtain economic and social opportunities. However, gender, a key demographic variable that influences travel behaviour is often neglected in city transport planning. Various studies have shown that the travel requirements and behaviour of women differ widely from men. Yet historically, urban transport planning has overlooked the mobility needs of women, who are more likely to use low-carbon emitting modes. The failure of urban transport systems to consider gender as an important variable for transport planning places heavy constraints on women, particularly those belonging to low-income groups because of their greater dependence on public transport. In this context, the current study delved into mobility and sociological parameters that influence travel patterns of female commuters in Delhi based on online surveys conducted to bring forth the influence of different travel characteristics. Among non-motorised transport, men prefer to both walk and cycle; however, women prefer only walking. A larger proportion of women prefer public transport to men and access to personal transport is limited for women than men in long-distance travel segment. Most of the women who are currently not using public transport have indicated willingness to shift, provided public transport stops are located within a comfortable distance. Based on the survey analysis, the paper argues for a more comprehensive and gender‐inclusive transport policy that provides a strong foundation for attaining Sustainable Development Goals, especially SDG 11.2.

Urban road street cross-section has components such as main carriageway, service road, NMT track, Footpath, median, and multi-utility zones, each meant to provide a smooth and safe vehicular and pedestrian traffic flow. It is needless to emphasize the need to make our cities pedestrian-friendly, as it directly impacts pollution control, the health and safety of the citizens, and general well-being in all respects. This research proposes a cost-effective, easy-to-implement design solution that excludes or inhibits the movement of two-wheelers from using the footpaths meant for pedestrians and persons with disabilities (PWD), especially wheelchair users. The proposed design solution was validated through Swept Path Analysis using vehicular simulation tools, on-site experimentation, and calibration. The final design proposal uses the existing products for controlling accessibility on footpaths, like using concrete bollards. Still, the solution lies in the placement and spacing of these design elements on varying cross sections/widths of footpaths. The final solution is in the form of a series of triple bollard system (TBS) meticulously designed, calculated, calibrated, and validated drawings along with strategies to discourage the two-wheelers from using footpaths and cycle tracks meant otherwise for pedestrians/cyclists and thus creating barrier-free and user-friendly walkways across the urban landscapes, through minimum governance and on-site traffic regulation.

Transportation plays an indispensable role in bolstering economic growth and social inclusivity, yet it remains a major contributor to environmental pollution, including noise pollution, which is often overlooked due to its non-acute health effects and requires increased awareness and vigilance. This study examines the issue of high noise pollution on urban roads in India, using Vijayawada City as a case area. The objective is (a) to gain insights into the characteristics of traffic noise and (b) to identify the factors that contribute to noise pollution. Three intersections were selected, along the National Highway-16 (Chennai-Srikakulam Highway) that runs through the city to measure the levels of noise. A videography survey was conducted for 6 h a day for 1 week (42 h) in the month of January 2023. Noise monitoring equipment (Norsonic 140) was used to measure the noise levels. To estimate the noise levels, a prediction model was developed using structural equation modeling. This model considered both direct and indirect impacts of various factors on noise levels. This analysis helped establish the relationships between road geometry, traffic flow, built environment factors, and their impact on road noise levels. Furthermore, the study revealed that the noise at intersections was primarily influenced by two factors, the honking behavior of two-wheelers and the volume of heavy traffic. The developed prediction model offers a valuable tool for estimating noise levels.

There is an increasing tendency to buy bigger cars, especially SUVs, as a status quo symbol. Automobile companies observed an increased demand this year. This is likely to aggravate the already congested roads in most Indian metropolitan cities. Many signalized intersections are experiencing long queues and longer waiting times. Unlike public transport, which carries more passengers for the space it occupies, SUVs have a lower vehicle occupancy. Many studies have been conducted on SUVs based on the safety, environment aspects while there is a gap in studying the impact of SUVs on traffic. This study proposes an impact assessment of the penetration of SUVs through simulations. Vehicle pooling is also assessed as an alternative. The study has been conducted on Silk Board junction in Bangalore with peak hour and off-peak hour traffic. It was observed that up to 3 min in peak and 4 min in non-peak hour per vehicle for a 4 km ride can be saved if all cars are pooled while up to 2 min in peak and 5 min in non-peak hour per vehicle can be saved if only SUVs are pooled for the same journey. The results showcase that penalizing buying private SUVs as a mode of transport and incentivizing carpooling or adopting high occupancy vehicles to make them a lucrative option need to be done to improve the overall sustainability of urban transport. The study could help the policymakers to address the issue of this new trend of buying bigger private cars such as SUVs.

In urban areas, on-street parking is considered a standard feature, despite its advantages and disadvantages. Numerous researchers identified on-street parking as a significant side friction factor and a more pressing issue in developing nations. Especially when it exists near signalized intersections for reasons such as insufficient sight distance, unused green time, decreased capacity at signalized intersections, etc. The various editions of the Highway Capacity Manual (HCM) [HCM. Highway Capacity Manual (2010) (vol. 3) Transportation Research Board] provide the fundamental concepts and techniques for estimating saturation flow (SF), primarily for lane-based homogeneous traffic patterns with different adjustment factors, including for on-street parking. On-street parking was viewed as a categorical variable, either ‘absence’ or ‘presence’ in the vast majority of research conducted worldwide. These techniques are inapplicable in developing nations with heterogeneous, non-lane-based traffic and largely unauthorized on-street parking. Also, the Indian Highway Capacity Manual (Indo-HCM) [Indo-HCM (2017) Indian Highway Capacity Manual (Indo-HCM). In: CSIR-Central Road Research Institute, New Delhi] does not address the effect of on-street parking near signalized intersections. The objective of the present study is to determine the impact of on-street parking near signalized intersections and to identify its influencing zone. The present study collected data from eight signalized intersections, including four base and non-base sections each, located in different regions of India (Delhi, Kerala, and Maharashtra) to examine the variation in traffic composition, driver characteristics, land use, and control conditions. It has been observed that parking maneuver time in Indian conditions is significantly less than that specified by HCM. The primary focus of this study was to analyze the variations in occupied effective width for different types of vehicles, distance of first parked vehicle from the stop line near signalized intersections within a mixed traffic environment. As the distance between the first parked vehicle and the stop line varies, variation in SF at these intersections is also evaluated. When the distance between the first parked vehicle and the stop line exceeds 65 m, there is no observable reduction in SF from base SF. This result aligns with the finding in Indo HCM, which stated that bus stations should not be placed within 75 m of signalized intersections. The findings of this research will aid traffic engineers and planners in assessing the performance of signalized intersections with on-street parking.

Effective transportation infrastructure planning requires road agencies to develop a sequential Travel Demand Model (TDM) process, beginning with Trip Generation. This involves using the total number of person-trips generated in specific areas as the dependent variable, with Household (HH) and socioeconomic factors as independent variables influencing travel behavior. In India, accurately collecting household information and trip characteristics is challenging due to dynamic travel patterns influenced by socioeconomic and urban development factors, making secondary data unreliable over time. Trip rates, indicating the average number of trips per unit of a specific factor, are essential for understanding travel demand trends. This study examines travel patterns in Surat, Gujarat, India, using data from one thousand households collected through home interviews. It investigates the relationship between Per Capita Trip Rates (PCTR) and household variables such as size, vehicle ownership, income, students, and earners, based on previous studies and mobility plans for Indian cities. The hypothesis testing showed no significant difference between the sample mean and population mean at a 10% significance level, with Surat’s mean trip rate estimated at 1.57. Specific trip rates for work, education, shopping, and other activities were 0.82, 0.46, 0.13, and 0.16, respectively. Analysis revealed a negative correlation between household size and trip rates, and a positive correlation between earning members, income groups, and vehicle ownership. Regression analysis using Linear Regression (LR) and Multiple Linear Regression (MLR) highlighted the unpredictability of infrequent trips like shopping and recreation, while regular work and educational trips showed significant relationships with household variables. The study provides valuable insights into Surat’s travel behavior, aiding future trip production estimations as the urban population grows.

With the number of metro rail systems in Indian cities growing, there is an intensifying focus on boosting ridership and improving land utilization around mass transit. The National Transit Oriented Development (TOD) Policy has given this concern its legitimacy by offering guidelines to cities and states. Among other things, a decisive factor influencing such planning efforts is the delineation of station areas. Many of the concepts and practices of Station Area Planning (SAP) rely on thumb rules and ‘best practices’ that are often replicated from studies and projects carried out in widely differing contexts. Our study seeks to initiate a debate on the downside of such an approach in planning practice and policymaking. Using secondary datasets, a case comparison has been developed across select Indian cities with metro rail facilities. We argue that SAPs are a highly context-sensitive strategy, which demand a thorough examination. By discounting the importance of a wide range of contextual factors, templatizing influence areas can have perverse results. There is, hence, a dire need to understand the nuances of area delineation more thoroughly before embarking on empirical investigations of policy interlinkages. It is our belief that by serving to initiate debate on these lines, it is possible to achieve multiple objectives that cities are constantly striving for.

Rapid urbanization in India has driven a heightened need for public transportation, particularly Mass Rapid Transit Systems (MRTS) due to their speed, reliability, and affordability. This prompted the initiation of the Delhi Metro project and the preparation of Detailed Project Reports (DPRs) for comprehensive demand assessment. However, a recent audit report revealed significant discrepancies between projected and actual ridership, raising concerns about the existing travel demand modeling method's reliability. Given the high costs of metro system construction and the need for accurate demand estimation, this study focuses on the efficacy of probabilistic models—Gaussian, Negative binomial, and Log-linear regression—for predicting passenger demand at metro stations. The investigation encompasses diverse variables like land use, socio-economic factors, and station attributes. The research concentrates on the Delhi Metro's Yellow Line, a prominent route within India's busiest metro system. To gather the necessary data, the research utilized Geographic Information System (GIS) software to effectively map and analyze the various land use variables. Additionally, a primary survey was conducted to capture relevant passenger characteristics. Once the data collection phase was completed, the research employed statistical software R for the purpose of modeling and analysis. Furthermore, to ensure the robustness of the developed models, additional validation was carried out in two other cities. The study's results indicate that the Gaussian regression model outperforms the negative binomial and log-linear models with an R2 value of 0.93 and a lowest MAPE value of 11%. This suggests that the Gaussian model provides a better fit to the data and more accurately predicts passenger demand. Hence incorporating probabilistic regression models and a comprehensive set of variables can address limitations in the current demand modeling process.

Passenger ferry boats of various capacities operate in rivers and canals, transporting a significant number of passengers. This research examines the performance of passenger ferry services in Mumbai city, along the creeks, and harbors of the western and eastern coasts. The goal of this research is to develop a level of service categories for parameters affecting the performance of ferry service by understanding the existing scenarios. The study considers both passenger's and operators’ perspectives. The outcome is in the form of a framework procedure to assess the service in the respective cities along with the suggestions for additional revenue generation for operators. The findings of this study will be useful for policymakers, academicians, and stakeholders to evaluate ferry services in their cities by altering the process according to the need. It will help decide suitable interventions and the necessary investments to be made in the water transportation sector.

The paper disseminates the knowledge of Dry Port Planning in the shadow of the seaport. For the planning of dry port location, land suitability analysis, and location-allocation analysis, considering parameters such as population density, accessibility, proximity to production centers, and avoidance of existing infrastructure have been carried out. The weighted sum tool technique is used to combine these parameters. The weights are assigned using the ‘Analytical Hierarchy Process’ (AHP). Also, the service area analysis is made to check the service area reach of each proposed dry port location. This analysis identifies the optimal locations of dry ports and includes a comparative study to assess the effectiveness of the proposed rail connectivity solution in relation to freight traffic circulation through the road network. The study reveals significant reductions in greenhouse gas emissions and transportation costs. Effective location planning for dry ports is essential for enhancing trade efficiency, optimizing transportation operations, driving economic development, and promoting sustainable port cities.

Urban public transport (PT) is essential for sustainable cities due to its capacity and benefits for economy, health, and environment. However, merely providing PT services is insufficient; ensuring equal accessibility is crucial. The Public Transport Accessibility Levels (PTAL) tool, developed in London, is a global standard for assessing PT systems using Points of Interest, Service Access Points, frequency, and walk networks. Despite its utility, factors like time, fare, land use, density, infrastructure, comfort, safety, and cleanliness also affect PT accessibility. A Melbourne study revealed disparities between expected and observed PTAL, suggesting additional parameters might help. In India, where PT users are mainly captive, PTAL assessments often overlook smaller cities. This study, conducted in Rewa, Satna, and Singrauli in Madhya Pradesh, tests PTAL’s accuracy and explores additional parameters, focusing on intra-city PT and Intermediate Para Transit (IPT). Findings indicate PT is preferred for low fares, while IPT is chosen for convenience. Enhancing PTAL accuracy involves incorporating layers like building cover and land use, applicable through a Geographic Information System (GIS) plugin.

The concept of perceived accessibility, which refers to an individual's belief about the ease of accessing and using various locations, services, or resources through the transportation system, is a valuable addition to traditional objective measures of accessibility. Recognizing the importance of user perceptions, it is crucial to include perceived accessibility in analyses to understand how transit users perceive the overall quality of services. This study employs Structural Equation Modelling (SEM) to examine complex relationships between latent variables (unobservable constructs) and observed variables (measurable indicators). Service quality is influenced by various aspects of the transportation system, such as stop and vehicle facilities, safety measures, and journey components outside the vehicle. Perceived accessibility assesses the system's ability to provide access to opportunities and activities. A focused questionnaire survey among 700 users of Vadodara's city bus service, including regular and infrequent passengers, measured user perceptions and satisfaction levels. The SEM model incorporates four latent variables: Stop-level facilities, In-vehicle facilities, Safety, and System facilities. Analysis revealed that System facilities had the strongest influence on perceived accessibility, followed by stop-level and in-vehicle facilities. Safety had a lesser influence. Key factors for System facilities include access distance, service frequency, waiting time, total travel time, and facilities for elderly and disabled individuals. Closeness at the end of journeys, stop waiting time, and total journey time significantly influences perceived accessibility, reflecting users’ beliefs in the system's ability to make desired opportunities reachable on time. The study found significant satisfaction differences among socio-economic clusters in the city. It emphasizes the relationship between service quality and perceived accessibility, offering practical implications for transportation companies and managers to improve services and cater to diverse user needs effectively.

Public transport (PT) drivers play a vital role in our communities. They are the backbone of the urban transportation system in most cities worldwide. Many issues faced by PT drivers are yet to be explored in the context of developing countries. Studies in developed countries are concentrated on drivers’ stress and emotional well-being. The current research focuses on understanding the challenges and barriers faced by PT drivers in urban India. The study is based on a questionnaire survey in Kota City, Rajasthan. A total of 289 predominantly male drivers participated and completed the survey. The study uses descriptive analysis to explore the challenges faced by the drivers. Further research can build upon these descriptive findings to explore the relationships between variables, investigate potential solutions to enhance PT drivers’ well-being and satisfaction and propose targeted solutions to address the identified challenges. By analysing and addressing the needs of PT professionals, transport planners can foster a more inclusive and efficient urban mobility framework, enhancing the overall quality of life for residents and commuters in the city.

A dearth of research exists concerning the road influence of road infrastructure on road safety in low- to medium-income nations, particularly in relation to vulnerable road users (VRUs). To address this void, an extensive five-year study (2017–2021) was conducted in Vadodara, examining VRUs involvement in fatal crashes and the impact of various road infrastructure. This investigation primarily scrutinized variables such as land use, street lighting, lane count, parking facilities, road width, medians, median cuts, lane markings, zebra crossings, speed breakers, footpath presence, commercial activities, and access density on VRU fatal crashes. The study analysed 608 midblock within the road network, incorporating pertinent geometric aspects. To ascertain risk factors for VRU fatal crashes, an unmatched case–control methodology applying a Logistic regression model was employed, defining cases as midblock with VRU fatal crashes and controls as midblock without, presenting both univariate and fully adjusted models. Throughout the study period, 169 pedestrian and 198 motorized two-wheeler fatal crashes occurred. Bicyclist crashes were excluded due to their relative rarity compared to pedestrians and motorized two-wheelers. Key findings reveal that higher traffic volume and an increased number of lanes significantly correlate with elevated pedestrian crash risks. Similarly, motorized two-wheeler (M2W) crashes are notably influenced by the number of lanes and median width. However, wider medians exhibit a negative correlation with M2W crashes, indicating a safety benefit. Moreover, residential land use is statistically significant for both pedestrian and M2W crashes, highlighting the elevated crash likelihood associated with increased pedestrian and M2W activity. These findings underscore the need for targeted interventions to enhance VRU safety and inform policy decisions for improved road infrastructures.

Understanding the urban network's structure is essential to comprehend how a city's traffic moves. A well-planned city can be distinguished from a demand-oriented development, where the road network is created based on traffic demand rather than a plan, using the topology of the road network. Though the usual measures of understanding the formation of a road network, including the road network density, the junction density, average path length, etc., aid in characterizing the road network, they are weak in explaining the importance or influence of specific nodes/links in the network. Betweenness centrality is particularly relevant for understanding urban movement patterns because it quantifies the extent to which a node lies on the shortest paths between other nodes. Nodes with high betweenness centrality are often located on important routes that facilitate efficient transportation and experience a higher flow of traffic. As betweenness centrality highlights the important edges present in a network there should, hypothetically, exist a correlation between the width of the road segments and their corresponding betweenness. The current study aims to mathematically quantify the correlation between the widths of different road segments in the network and their corresponding betweenness centralities. The topological analysis is conducted for the road network of Ludhiana City of Punjab. The final value of correlation is interpreted and further policy implications are discussed.

Kathmandu is facing escalating challenges related to congestion, air pollution and energy consumption due to increase in demand for personalized transportation. Efforts are being made to strengthen the public transport system in Kathmandu and much imitative is introduction of electric vehicles. Development of these buses is expected to augment public transport capacity, create clean environment, and modernize the transportation system. In this context, a study has been undertaken to determine which aspects of service quality are important and to what extent the rider's overall satisfaction with the electric bus can be achieved with these aspects of service quality. Partial least square structural equation modeling (PLS-SEM) integrated with the necessary condition analysis is used to analyze the service quality and overall satisfaction of riders. 388 data were collected using the customer satisfaction questionnaire, which captured satisfaction ratings of service quality attributes, socio-demographic characteristics, and trip characteristics. After the analysis, among the latent construct of service quality it was observed that riders ‘overall satisfaction with electric buses is highly influenced by latent constructs comfort followed by security, availability, and time & reliability. Between latent construct of personal attitude, riders’ overall satisfaction is mostly affected by involvement than that of perceived value. Improving these latent constructs can boost the rider’s overall satisfaction. This study will assist electric bus operators and researchers in identifying key attributes for improving service quality and attracting more riders to public buses. Additionally, it will provide public authorities, policymakers, and researchers with essential insights into making electric buses, a sustainable and low-emission public transport option, more appealing.

With growing urbanization, our cities require efficient planning measures and infrastructure upgradation to maintain a fine balance between growth and sustainability. In this regard mixed-use development has become an essential component of various planning movements like Smart Growth, New Urbanism and significantly influences the interaction between land use and transportation. In case of Indian cities, mixed-use development has taken place in incremental ways where people have changed and used their residential units in commercial developments, creating multifunctional areas hosting different economic activities including informal activities. Such self-organized development is mostly influenced by high level of local accessibility and consumption demands of retail and services at neighborhood level. This study focuses on both planned and unplanned residential areas of North-West Delhi, where survey of selected mixed-use streets is conducted, and ordinal logistic regression-based model is developed to understand the relationship between customer attraction and type of commercial activities, clustering of commercial activities, mixed-use characteristics, and road network connectivity indices. Results of this study can be further utilized in framing policies for transport and pedestrian infrastructure, travel demand assessment along with planning for catchment areas of transit-oriented development for Indian cities.

Metro stations are vital urban transportation hubs, handling substantial pedestrian traffic, especially during peak hours. Research on pedestrian movement within these stations is crucial for understanding crowd behavior, flow patterns, congestion, and evacuation strategies. This study employs a microscopic analysis approach, using the social force model to simulate pedestrian behavior at Choti Choupar Jaipur metro station. It examines various pedestrian parameters, including walking speeds, densities, and directional preferences. Alongside simulation, a questionnaire survey captures user perceptions of discomfort in different station areas. The VISWALK tool analyzes pedestrian movement dynamics, focusing on flow patterns and congestion levels. The study carefully considers factors such as station layout, platform configuration, and passenger behavior to propose strategies for optimizing station design and crowd management. The research also assesses the level of service (LOS) related to changes in average pedestrian density, emphasizing comfort, convenience, and safety. This focus on service quality allows metro station operators and urban planners to identify improvement areas, prioritize enhancements, and implement interventions to enhance the passenger experience. Additionally, the study examines the impact of shops with varying dimensions within entry/exit and passageway areas. Notably, the findings suggest that strategically integrating shops into passageways can be done without compromising pedestrian comfort. The research highlights that the entry/exit and platform areas contribute most to pedestrian discomfort, as indicated by user perception surveys and average density results during peak hours. These insights are valuable for optimizing metro station user dynamics and improving overall service quality.

The advent of the COVID-19 pandemic has significantly impacted the travel patterns of university students in urban India, leading to a decline in their use of public transportation, active mobility, and lifestyle that may have long-term impacts on future mobility patterns. The present study, therefore, aims to investigate the similarities and differences in physically passive (PP), and physically active (PA) behaviors before (BL) and during the lockdown (DL) period, enabling the identification of effective strategies to mitigate undesirable lifestyle changes experienced by the university population. A multivariate ordered probit (MOP) model was estimated to examine the objectives. The data used for modeling was collected through an online survey conducted in pan-India from May to July 2020. A total of 631 responses were collected, of which 203 survey forms were deemed eligible. Gathering responses from the same cohort during the BL and DL period is a unique feature of this study. Activity episodes consisted of dependent variables, while socio-demographics, mode use behavior, and psychometric indicators were the explanatory variables. The psychometric indicators consisted of measurement items related to ‘anxiety (AL)’, ‘physical well-being (PW)’ and ‘leisure (LE)’ and a principal component analysis (PCA) was used to identify these latent factors. The results indicate that PP episodes for BL and DL periods were complementary, while PA episodes were substitutive. Age, education, and access to private modes had an adverse effect on an active lifestyle (PA). However, students with high scores on PW constructs are more inclined to carry out PA episodes. The study concludes with relevant policy discussions based on model outcomes.

Mumbai suburban railway system remains critical to the lifeline of the city. This paper looks at the inclusive and accessible dimensions of the suburban railway system. It intends to reflect upon the key issues involved in making the suburban railway system more inclusive and human centric, especially for persons with disabilities. It is based on a study carried out on over forty (40) suburban rail stations in Mumbai over a period of more than six (06) months. It involves direct and indirect observations, along with qualitative insights through surveys with diverse stakeholders involving persons with disabilities and other allied service professionals. It highlights the broad issues and challenges faced by diverse persons with disabilities in the Mumbai suburban railway system and reviews learnings from the best practice models. Guided by the Rights of Persons with Disabilities Act, 2016, it analyses the key accessibility issues in terms of information, infrastructure, and services in the suburban railway system of Mumbai. This includes accessibility perspectives in the digital information systems like Mobile rail applications (like UTS, YATRI app). It brings out specific learnings of the needs of diverse population groups along with disability perspectives rooted in an understanding of demographic impact. It paves a diagnostic way toward mobility infrastructure development specific to the context of Mumbai. This study recommends a holistic framework of understanding suburban railway systems through the lens of inclusivity, incorporating the diverse needs of persons with disabilities and other population groups.

The Regional Rapid Transit System (RRTS) is an initiative launched to promote public transportation in the National Capital Region (NCR) and act as a catalyst for development and growth of the region. The study aims to understand how people perceive the introduction of RRTS in their vicinity. A primary survey targeting stakeholders within a 1.5 km radius of RRTS stations was undertaken to gain valuable insights into the changes observed, whether positive or negative. The Relative to an Identified Distribution Integral Transformation (RIDIT) analysis was further used to identify the factors that garner the highest consensus among the stakeholders. Maximum stakeholders strongly agreed that RRTS will reduce travel time and make it easier to reach the connected areas. Further, most of the stakeholders disagreed that the RRTS has ruined the looks of their neighborhood. The newly proposed RRTS corridor suggests a predominantly favorable outlook, benefiting not only the people but also the land in proximity to the corridor. Such a study will allow organizations to gauge how the transit system influences the surrounding areas and propose strategies to maximize benefit from such systems.

Urban areas worldwide recognize Transit Oriented Development (TOD) as a successful strategy to foster sustainability. Over the years, TOD has gained prominence in integrating land use and transportation and improving quality of life. In India, effective implementation of TOD should require addressing key issues such as heterogeneity and equity, policy and regulatory frameworks, financial availability, integration of multiple agencies, the risk of gentrification, and the carrying capacity within densely populated urban cores. A document analysis approach has been adopted to examine existing government policies, laws, and regulations and understand the current status of TOD implementation in Indian cities. Although the 2017 TOD Policy and Metro Rail Policy offer guidelines and regulations, there remains ambiguity concerning its implementation, particularly the responsibilities and evaluation framework, along with the lack of integration with master plans and building regulations. Findings reveal that few cities have text-based policies and emphasize that TOD’s scope varies with city size and planning type. Thus, there is a need for a context-sensitive, policy-driven, and micro-level planning approach that integrates multiple aspects of TOD, including land use, social structure, travel patterns, infrastructure, and environment. This paper comprehensively explains existing TOD strategies and their challenges, forming a base for an integrated approach and evidence-based strategies to ensure sustainability.

Traffic noise threat is higher at intersections in mid-sized cities due to complex road geometry, reckless driving, heterogeneous traffic flow and poor traffic management. Traffic noise reduces the quality of life and causes negative impacts on health. Annoyance is a commonly reported problem due to traffic noise, which can mediate various health problems, including cardiovascular disease, sleep disturbances, and stress. Therefore, the current study aims to analyse annoyance levels at intersections in mid-sized cities. Various personal and situational factors such as gender, age, and education affect the annoyance levels. This study investigates the effect of individual characteristics and traffic noise levels on annoyance levels at intersections in mid-sized cities. For this, hourly equivalent noise level (Leq) due to road traffic is measured near the facades and individual characteristics (i.e., age, gender, income, education, exposure hour, and noise sensitivity) are measured based on the community survey at 15 intersections in Kanpur. In addition, the annoyance level of a person is measured during different activities such as conversing, reading, resting, sleeping, using phone, watching TV, and working. The results indicate that gender, age, and income do not significantly affect annoyance, while noise sensitivity, education, exposure hours and Leq significantly affect annoyance levels. Noise sensitivity has the highest effect on annoyance among people residing at intersections, followed by education, exposure hour, and Leq. The developed PLS-SEM model has a 69% capability to explain the variance in annoyance levels at intersections in mid-sized cities. This finding has important implications for public health interventions, as it suggests that targeting noise sensitivity could effectively reduce negative effects of traffic noise on health.

Transportation planning professionals are continuously striving to provide a multitude of sustainable travel alternatives to the public, such as walking, cycling, and utilizing public transportation. These eco-friendly options serve as formidable competitors to private motorized vehicles, known for their high emissions of greenhouse gases. Surprisingly, despite the prevalence of private vehicles, there exists a group of road users who staunchly favour sustainable transport modes. Their motives for this preference are diverse and evolve over time, reflecting the shifting attitudes and priorities of individuals towards environmental sustainability and personal well-being. The present study investigated the impact of attitudes towards owning private vehicles and attitudes towards public transport on users’ preferences for sustainable transport modes (STM), i.e., walking, bicycling and public transport. The study examined a model of sustainable transport mode preference that can explain attitudes towards owning vehicles and public transport. The study analyses the sustainable transport mode preference derived from commuters in Nagpur, India, using a two-stage MIMIC approach (Multiple Indicator Multiple Cause model). To analyse this dataset, a two-stage MIMIC approach was employed, which combines EFA (exploratory factor analysis) and MIMIC model. The result confirms that preference for STM is majorly influenced by attitudes towards private vehicles and public transport. Although the socio-demographic of individuals should not be overlooked, they play a pivotal role in influencing attitudes towards both public and private transport modes. By examining factors influencing the preference for sustainable transport modes, policymakers and transport planners can gain insight into the importance of users’ perceptions about private and public transport in developing a sustainable transport system.

Accessibility in transportation is an often overlooked aspect of urban planning and infrastructure development. It plays a significant role in ensuring that vulnerable groups including Persons with Disabilities (PwDs) can lead an independent and inclusive life. However, historically, transportation systems have often under-prioritised the needs of PwDs, creating barriers to their mobility and participation in society. Recognising these challenges and the importance of creating accessible transportation systems, the Government of India launched the Accessible India Campaign (AIC) in 2015. This campaign aims to bridge the gap between the aspirations and the reality of creating a fully accessible transportation system. Multimodal transportation hubs have been on the rise in recent times, aiding cities to improve the efficiency of their transportation systems. These hubs enable the users to seamlessly transfer between the various modes of travel. Vyttila Mobility Hub, a multimodal transportation hub in Kerala, India, integrates road, metro rail, and water transport services. While the hub gives an opportunity to shift between the various modes, its ease of use by the vulnerable groups is to be ascertained. The considerations include vehicular accessibility, the built environment, and the organisational systems, ensuring that PwDs can navigate the hub independently and with dignity. Evaluating and addressing accessibility at all levels of transportation infrastructure is crucial for creating a more equitable and inclusive society.

The COVID-19 pandemic significantly impacted how people travel, particularly in terms of the choices they make regarding transportation modes. While there is debate about the temporary nature of travel behaviour changes during COVID-19, it continues to be a topic of study in different geographical contexts. The disparities in travel options among cities of varying sizes may have had distinct impacts on travel patterns during COVID-19 restrictions and in the post-pandemic era. To analyse the argument, this paper compares the shift in mode choice behaviour for commuting before and after COVID-19. Two multinomial logit models were estimated to analyse work trips, utilising 344 observations from a Pan-India online survey conducted in the late 2021 and early 2022 period. The findings demonstrate the substantial influence of variables such as family size, gender, income, and education on individuals’ decision-making regarding their mode of transportation for work. The findings also indicate that the size of the city and the number of vehicles owned significantly influence the choice of commuting modes.

As urbanization continues to accelerate across the country, it births numerous challenges, such as transportation, pollution, and parking shortages attributed to the non-walkability of many Indian cities, especially in the commercial markets. The Government has initiated pedestrianization measures in various commercial markets to address this. However, the accessibility to these commercial markets needs improvements to meet the shoppers’ expectations. Therefore, the present study aims to measure the shoppers’ satisfaction with accessing the two pedestrianized urban commercial markets, namely, Lajpat Nagar and Karol Bagh in Delhi, India. Accordingly, the study derived the satisfaction ranking of selected eight attributes influencing the accessibility of markets based on shoppers’ perceived satisfaction. Using digital and pen-paper survey methods, a face-to-face questionnaire survey was conducted to collect 400 samples of shoppers’ satisfaction with the selected attributes on a 5-point Likert-type ordinal scale ranging from 1 (strongly disagree) to 5 (strongly agree). Subsequently, the database was analyzed using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to derive the satisfaction rankings of the attributes. The results show that the attributes shoppers find most satisfying are ‘safety’ and ‘social life’. While ‘cleanliness’ and ‘universal accessibility’ are the attributes, shoppers are least satisfied. ‘Cleanliness’ was observed as the major concern among shoppers, regardless of gender and age. The study findings would help policymakers and urban planners by providing valuable insights into the impact of pedestrianization on urban market spaces and shed light on the specific areas for improvement for accessibility in Indian commercial markets.

Pedestrian gap acceptance behavior becomes more critical at un-signalized, unmarked midblock crossings due to complex interactions of pedestrians with moving vehicles. The critical gap is an essential parameter in exploring the gap acceptance behavior. This paper analyzes the gap acceptance behavior of pedestrians crossing an un-signalized mid-block with no marked crosswalk through critical gaps. Existing literature has many methods for estimating the critical gaps, such as Clearing time, Greenshield’s, Raff’s, and Harder’s methods. The present study aims to estimate and compare the critical gaps for pedestrians crossing individually and in a group at the un-signalized midblock section for morning and evening peak times. The study also explores the perceived risk of crossing pedestrians at the un-signalized mid-block section under study. Accordingly, the data were recorded using a video-graphic survey at an un-signalized unmarked midblock crossing in Delhi, India. Further, the Dartfish software was used to extract vehicular gaps with an accuracy of 20 ms (0.020 s), resulting in 3126 lags/gaps data of 635 pedestrians. Subsequently, the critical gaps were estimated and compared using (a) Clearing time, (b) Greenshield’s, (c) Raff’s, and (d) Harder’s methods. The study found that critical gaps using Greenshield’s, Raff’s, and Harder’s methods are lower than the Clearing time method. The findings suggested that the Clearing time method is the most appropriate for estimating critical gaps in Indian traffic conditions. The study results would help urban planners and policymakers evaluate safety performances and design pedestrian crossing facilities accordingly.