Performance Evaluation of Multimodal Transportation Systems

AbstractConnectivity of more than one mode to a line haul in an urban area constitutes the multimodal transport system of the city. In this paper New Delhi has been taken up as a case study to evaluate performance of multimodal transportation system (MMTS), where metro became main mode in routine public transport trips. Public transport in Delhi carries only about 60% of total vehicular person trips as against 80% of the expected population size of the city. The present bus services, metro rail and IRBT (Integrated Rail-cum-Bus Transit), if implemented as planned together are estimated to carry about 15 million trips per day by 2021. Since, all the public transport trips are multimodal, it is necessary to evaluate the performance of multimodal transportation systems. The study is divided into two phases. In the first phase, the study of travel time elements (access time, transfer time, waiting time, line-haul time, and egress time) is done. Next, the influence of access and egress times on the total travel time is examined. Use is made of a comprehensive commuter travel diary to collect detail travel time estimates. A representative commuter survey, with 460 respondents, is drawn on platform at each station of Red Line and Yellow Line (Kashmiri Gate – Saket) Delhi Metro. Implementing the Second phase of study, performance measures such as Travel Time Ratio, Level of Service, Interconnectivity Ratio, Passenger Waiting Index, and Running Index were evaluated. Interconnectivity ratio (proportion of access and egress time w.r.t total travel time) for various combinations such as Mixed-Metro-Mixed, Walk-Metro-Walk, Walk-Metro-Bus and Walk- Bus-Walk has been observed. Travel Time (defined as the time differential between private transport and public transport) ratio shows much variation with trip direction, time of day, mode used, and distance travelled, etc.,. Level of Service Indicator (Out- of-vehicle Travel Time/In-Vehicle Travel Time) ratio inferred that people spends more time out-of-vehicle as compared to that of in-vehicle. Access time, transfer time, waiting time and egress time are the most important and complex travel time elements that transport systems should consider improving its efficiency and modal share. The results can be used in planning catchment area of public transport. Access and egress (together with waiting and transfer times) appear as factors that affect effectiveness and performance of a multimodal transportation system to a larger extent as unacceptable distances are likely to reduce ridership patronage. At the same time, there are key deciding factors when a trip originates as to whether the commuter shall choose public transit over personal mode of travel

A Compact Reconfigurable Multi-mode Resonator-based Multi-band Band Pass Filter for Intelligent Transportation Systems Applications

A compact wide band reconfigurable bandpass filter (BPF) which utilises a hemi-circular flower shaped multimode resonator (MMR) is presented. The proposed MMR provides three resonant modes which fall within the broad frequency spectra. Among these, two modes are even and one is odd. These modes are optimised by varying the dimensions so as to obtain the desired frequency response. The fractional bandwidth is more than 96 per cent. The filter can be operated as multi-band BPF. In OFF condition of ‘Pin’ diode, the centre frequencies are 2.43 GHz, 3.5 GHz, and 5.9 GHz in ON condition of ‘Pin’ diode centre frequencies are 2.43 GHz, 3.5 GHz, 5.9 GHz, 6.5 GHz, and 8.8 GHz which are used for vehicular, WiMAX, intelligent transportation systems and satellite communication respectively. Microstrip filter structures are integrated with ‘Pin’ diodes. Appropriate biasing has been provided by choosing lumped components with precise values. The insertion loss in OFF condition are 0.5 dB, 0.67 dB, and 0.8 dB and in ON condition 0.5 dB, 0.7 dB, 1.2 dB, and 1.9 dB. The measured results agree well with the full-wave simulated results

Modelling perceived pedestrian level of service of sidewalks: a structural equation approach

A disparity between developed and developing countries is not only in the terms of economy and geography, but also on the pedestrians’ perceptions and expectations about the level of service of sidewalks. Therefore, it is paramount to find the effect of various built environment measures, that impact perceived Pedestrian Level Of Service (PLOS) in the context of developing nations. This study investigates the most influential factors of the built environment that affect perceived PLOS of sidewalks in the Indian context. This is one of the first studies in India that utilize Structural Equation Modelling (SEM) technique to assess pedestrian satisfaction and thereby qualitative PLOS of sidewalks. A total of 502 personal interviews was conducted to extract the pedestrian perception about the quality of sidewalks of Thiruvananthapuram city, a typical Indian city. The results identified four latent exogenous constructs named “Safety”, “Security”, “Mobility and infrastructure” and “Comfort and convenience” that represent the main aspects of the PLOS of sidewalks among which factors of security has exhibited highest loading (λ = 0.60). The study identified that parameters like police patrolling, street lighting, cleaner sidewalks, sidewalk obstructions, sidewalk surface have an evident impact on the level of service of sidewalks. The results of the study provide a significant information for interpreting the aspects of the walking environment that mainly influences the PLOS. This information can help city planners to prepare new strategies, policy interventions that enhance the quality of sidewalks and thus making the city more walkable

Design of RF Receiver Front end Subsystems with Low Noise Amplifier and Active Mixer for Intelligent Transportation Systems Application

This paper presents the design, simulation, and characterization of a novel low-noise amplifier (LNA) and active mixer for intelligent transportation system applications. A low noise amplifier is the key component of RF receiver systems. Design, simulation, and characterization of LNA have been performed to obtain the optimum value of noise figure, gain and reflection coefficient. Proposed LNA achieves measured voltage gains of ~18 dB, reflection coefficients of -20 dB, and noise figures of ~2 dB at 5.9 GHz, respectively. The active mixer is a better choice for a modern receiver system over a passive mixer. Key sight advanced design system in conjunction with the electromagnetic simulation tool, has been to obtain the optimal conversion gain and noise figure of the active mixer. The lower and upper resonant frequencies of mixer have been obtained at 2.45 GHz and 5.25 GHz, respectively. The measured conversion gains at lower and upper frequencies are 12 dB and 10.2 dB, respectively. The measured noise figures at lower and upper frequencies are 5.8 dB and 6.5 dB, respectively. The measured mixer interception point at lower and upper frequencies are 3.9 dBm and 4.2 dBm

Short term traffic flow prediction in heterogeneous condition using artificial neural network

Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea to avoid traffic instabilities and to homogenize traffic flow in such a way that risk of accidents is minimized and traffic flow is maximized. There is a need to predict traffic flow data for advanced traffic management and traffic information systems, which aim to influence traveller behaviour, reducing traffic congestion and improving mobility. This study applies Artificial Neural Network for short term prediction of traffic volume using past traffic data. Besides traffic volume, speed and density, the model incorporates both time and the day of the week as input variables. Model has been validated using actual rural highway traffic flow data collected through field studies. Artificial Neural Network has produced good results in this study even though speeds of each category of vehicles were considered separately as input variables. First published online: 16 Oct 201

Comparative Appraisal of Metro Stations in Delhi Using Data Envelopment Analysis in a Multimodal Context

Urban public transit is a critical component for sustainable urban development and is crucial to multisector expansion of a developing economy. Continuous monitoring of infrastructure performance and assessment of its effectiveness are required to continually improve service quality. The urban agglomeration of Delhi, India, was studied for the efficacy of its multimodal urban public transit system. The toolkit used was Data Envelopment Analysis (DEA), a linear optimization technique that estimates relative efficiencies of its decision making units (DMUs) for a multitude of inputs and outputs. The study area includes the Red and Yellow lines of the Delhi Metro network. Commuter-based questionnaires were used to collect 1,328 valid responses about demographic, travel time, and quality perception parameters, which were analyzed, and relative rankings of the DMUs were evaluated. The efficiency was analyzed according to the Red and Yellow lines divided into seven corridor segments and individual stations. Results revealed efficiency scores and inefficiency slacks for which improvement strategies are proposed

Assessing commuters’ perceptions towards improvement of intermediate public transport as access modes to metro stations

The study considers the perception of Metro commuters to investigate the priority areas of interventions for improving the service quality of Intermediate Public Transport (IPT) as an access mode to the Metro stations in Delhi. Tablet-based face-to-face surveys were conducted to collect responses from 1121 commuters towards perceived importance and satisfaction ratings of 18 service quality attributes under study on a 6-point Likert scale. Collected responses were analysed using Revised Importance Performance Analysis. Implicit importance values of all the attributes were calculated to derive the factor structures and management schemes using the Fuzzy C-means clustering technique. The priority attributes were identified by comparing the factor structures and management schemes. Finally, the study proposed a priority order of resource allocation to improve attributes influencing IPT as access modes to the Metro stations. The study findings identified that ‘Transportation Subsidy’, ‘Accessibility in Bad Weather’ and ‘Universal Design Considerations’ were top priority attributes that demanded resource allocation for improvement. ‘Access Time’, ‘In-vehicle Travel Time’, ‘Luggage Space’, ‘Hygiene’, ‘Security’, ‘Riding Comfort’, ‘Frequency’ and ‘Travel Fare’ were operating at optimum service levels, hence, occupied a second-level priority in terms of resource allocation to ensure the levels were maintained. Two low-priority attributes, ‘Information at IPT stop’ and ‘On-board Information’ occupied a third-level priority in terms of resource allocation for improvement. Attributes under ‘Possible Overkill’, namely, ‘Safety’, ‘Convenience’, ‘Waiting Time’, ‘Egress Time’ and ‘Seat Availability’, suggested transferring resources towards improving other priority service attributes. The study findings can assist transport planners and policymakers in formulating policies for improving the performance of IPT as access modes to Metro stations in Delhi and extending the approach to other contexts to supplement the mass transit systems suitably and increase their ridership

Statistical modeling of traffic noise at intersections in a mid-sized city, India

The modeling of traffic noise is more debated around intersections due to traffic flow and road geometry complexity. The available intersection-specific traffic noise models cannot be transferred to predict the traffic noise at intersections in the mid-sized Indian cities due to traffic heterogeneity, variety in driving conditions, and vehicle compositions. This article aims to develop an intersection-specific traffic noise model by collecting data at 19 intersections in Kanpur, India. The data include a wide range of traffic, road, and weather-related variables. Furthermore, significant input variables are determined and used in the statistical regression model to develop an intersection-specific traffic noise model for the mid-sized Indian cities. This study develops a separate entrance and exit arm model based on the corresponding influencing variables. The coefficient of determination (R 2) value is 0.74 and 0.69 for the developed model at the entrance and exit arms, respectively, whereas these models achieve R 2 values of 0.73 and 0.67 in the validation step. Also, the performance of developed models is evaluated on the standard and mean absolute errors as performance metrics. This study finds that traffic volume and receiver distance are relatively the most important variables in the entrance and exit arm noise models

Demystifying service quality of Multimodal Transportation Hub (MMTH) through measuring users’ satisfaction of public transport

The present study attempts to explore the factors and their effects which influence the service quality of Multimodal Transportation Hub (MMTH) in Anand Vihar, Delhi. Total 515 samples are collected using satisfaction survey of public transport users. Exploratory factor analysis provides the six-factor solution and the same is confirmed using the confirmatory factor analysis. These factors are ‘transfer environment & important facilities’, ‘safety & security’, ‘transport modes and travel information’, ‘accessibility & signposting’, ‘comfort, convenience & quality of environment’ and ‘staff management & ticketing’. Structural Equation Modelling is used to identify relationships between service quality attributes and overall service quality. Results of the study show that service quality of MMTH is mostly affected by the transfer environment & important facilities (γ = 0.36) followed by safety & security (γ = 0.33). The results also demonstrate that evaluation of the overall service quality is better explained when people give ratings after knowing about the various attributes of the MMTH\u27s service quality. An external validation test is carried out, and results suggest that the values of service quality lie within the mean error range of ±6.5%, which presents the richness of the model. The findings of the study will help the government, operators and transport planners to formulate the policies in order to improve the service quality of the multimodal hub and ultimately promote the use of public transport

Travel Time Prediction for Traveler Information System in Heterogeneous Disordered Traffic Conditions Using GPS Trajectories

Precise travel time prediction allows travelers and system controllers to be aware of the future conditions on roadways and helps in pre-trip planning and traffic control strategy formulation to lessen the travel time and mitigate traffic congestion problems. This research investigates the possibility of using the GPS trajectory dataset for travel time prediction in Indian traffic conditions having heterogeneous disordered traffic and improvement in prediction accuracy by shifting from the traditional historical average method to modern machine learning algorithms such as linear regressions, decision tree, random forest, and gradient boosting regression. The present study uses massive location data consisting of historical trajectories that were collected by installing GPS devices on the probe vehicles. A 3.6 km long stretch of the Delhi–Noida Direct (DND) flyway is selected as a case study to predict the travel time and compare the performance as well as the efficiency of various travel time prediction algorithms