Showing papers by "Gitakrishnan Ramadurai published in 2020"

Electric vehicle routing problem with non-linear charging and load-dependent discharging

Abstract: We propose a three-index formulation for E-VRP with Non-Linear charging and Load-Dependent discharging (E-VRP-NL-LD), and an Adaptive Large Neighborhood Search (ALNS) algorithm to solve the E-VRP-NL- LD and E-VRP-NL-LD with Capacitated Charging Stations (E-VRP-NL-LD-CCS). Existing implementations of EVRP duplicate charging station nodes which enables the modelling of EVRP using extended VRP formulations. Two limitations of such an approach are: (i) the number of such duplications is not known a priori, and (ii) the size of the problem increases. In our formulation, we allow multiple visits to a charging station without duplicating nodes. We propose five new operators for ALNS which are tested on 120 instances each of E-VRP-NL and E-VRP-NL-LD, and 80 instances of E-VRP-NL-LD-CCS. Results show that our ALNS outperforms the existing algorithms improving the solution in 63% of the instances and matching the best known solution in 31% of the instances. Results also show that considering load-dependent discharge is critical to optimally solve E-VRP optimally.

A comparison of online and in-person activity engagement: The case of shopping and eating meals

Abstract: The virtual (online) and physical (in-person) worlds are increasingly inter-connected. Although there is considerable research into the effects of information and communication technologies (ICT) on activity-travel choices, there is little understanding of the inter-relationships between online and in-person activity participation and the extent to which the two worlds complement one another or substitute for one another. Shopping is one of the activity realms in which the virtual and physical spaces are increasingly interacting. This paper aims to unravel the relationships between online and in-person activity engagement in the shopping domain, while explicitly distinguishing between shopping for non-grocery goods, grocery products, and ready-to-eat meals. Data from the 2017 Puget Sound household travel survey is used to estimate a multivariate ordered probit model of the number of days in a week that a sample of households engages in in-person activity engagement and online activity engagement for each of these shopping activity types – leading to a model of six endogenous outcomes. Model results show that there are intricate complementary and substitution effects between in-person and online shopping activities, that these activities are considered as a single packaged bundle, and that the frequencies of these activities are significantly affected by income, built environment attributes, and household structure. The findings suggest that travel forecasting models should incorporate model components that capture the interplay between in-person and online shopping engagement and explicitly distinguish between non-grocery and grocery shopping activities. Policies that help bridge the digital divide so that households of all socio-economic strata can access goods and services in the virtual world would help improve quality of life for all. Finally, the paper highlights the need to bring passenger and freight demand modeling, at least within urban contexts, into a single integrated structure.

Characteristics of tail pipe (Nitric oxide) and resuspended dust emissions from urban roads – A case study in Delhi city

Abstract: Introduction Personal exposure to elevated vehicle exhaust and non-exhaust emissions at urban roadside leads to carcinogenic health effects, respiratory illness and nervous system disorders. In this paper, an attempt has been made to investigate the exhaust and non-exhaust emissions emitted from selected roads in Delhi city. Methods Based on the vehicular density per hour and speed, three categories of roads have been considered in the present study: (a) low density road (≤1000 vehicles/hour, V ≥ 10 m/s); (b) medium density road (>1000 vehicles/hour but ≤ 2000 vehicles/hour, V ≥ 7.5 m/s 2000 vehicles/hour, V Results Results indicated real-world NO exhaust emissions of 0.5 g/m3 (2.03 g/km) on high-density roads and 0.23 g/m3 (0.67 g/km) on low and medium density roads. These values were significantly higher than the Bharat Standard (BS) IV (0.25 g/km). The silt load on the different types of roads indicated 3, 25 and 44 g/m2 -day dust deposition on, low, medium and high-density road, respectively. PM2.5 and PM10 emission rates were measured using US-EPA AP-42 methodology and were found to be least at low-density roads with values of 0.54 and 2.22 g/VKT (VKT -Vehicle Kilometer Travelled) respectively, and highest for high density roads with values of 12.40 and 51.25 g/VKT respectively. Conclusion The present study reveals that both tailpipe (exhaust) and resuspend able road dust (non-exhaust) emissions contributes significantly and deteriorates local air quality. Although there exists emission standards, but there are no enforced regulations for non-exhaust emissions (resuspension of road dust). Hence, there is need to regulate non-exhaust emissions on urban roads.

Joint Model of Application-Based Ride Hailing Adoption, Intensity of Use, and Intermediate Public Transport Consideration among Workers in Chennai City

Abstract: The introduction of mobile application-based ride hailing services represents a convergence between technologies, supply of vehicles, and demand in near real time. There is growing interest in quan...

Injury severity prediction model for two-wheeler crashes at mid-block road sections

Abstract: Motorised two-wheelers (TW) have the highest proportion among vehicles in Chennai district of Tamil Nadu, and they are involved in a large number of fatal traffic crashes every year. We develop a m...

Developing driving cycles using k-means clustering and determining their optimal duration

Abstract: Driving cycles are used to understand the driving pattern of vehicles and in estimating their emissions. Although several studies exist on driving cycles worldwide, few studies have focused on developing driving cycles for intra-city buses in heterogeneous traffic conditions. In this study, driving cycles for intra-city buses were developed using real-world GPS data collected during peak and off-peak periods in Chennai city, India. The methodology for the construction of the candidate cycle was based on k-means clustering and one-step Markov modelling. For Markov chain modelling, a transition matrix is constructed which is a probability matrix based on one step succession. To understand the effect of duration of the driving cycle, the candidate cycles were developed for different durations ranging from 400 seconds to 2800 seconds. Further, the average error for each duration of the candidate cycles was determined. The duration which corresponds to the least average error was chosen for developing the final driving cycle. Three driving cycles - corresponding to morning peak hour, off-peak hour, and evening peak hour - were developed. Finally, the developed cycles were compared with the existing local and international cycles. The developed driving cycle was found to be significantly different from the existing cycles for buses.

Topological properties of bus transit networks considering demand and service utilization weight measures

Abstract: We present a complex weighted network analysis of a bus transport network. We model the network as graphs in L-space and P-space and evaluate the statistical properties in unweighted and weighted cases. The weights considered include number of overlapping routes and passenger demand between two bus stops. We also introduce a new supply-based edge weight called Service Utilization Factor ( S U F ) and define it as the passenger demand per service between two stops. We extract the origin and destination of the passenger trips from bus ticket information. In the bus system under study, the tickets are issued between ’stages’ instead of between bus stops. We propose a points of interest based procedure to map the passenger demand between stages to between bus stops. The network has scale-free behaviour with preferential attachment of nodes and is similar to small-world networks. It is well-connected with an average of 1.4 transfers required to travel between any two points in the network. We identify redundant routes in the network from strength values in the SUF weighted networks. Disassortativity in the demand weighted network indicated that bus stops with higher attractiveness are not necessarily situated contiguously along a route. The SUF weighted network is assortative indicating presence of well-serviced stops along the same the route. We identified the stops with higher betweenness centrality, that can be ideal candidates for being developed as hubs. Our conclusions exemplify the importance of considering route overlaps, passenger demand and service utilization in bus network analysis and for building an efficient bus network.

Field data application of a non-lane-based multi-class traffic flow model

Abstract: Multi-class traffic flow modelling has various approaches several of which have focused on analytical proofs. A key limitation in this field of research is the limited field data applications. This study proposes a speed-gradient-based multi-class second-order model and shows its application to three different road sections, a mid-block section, a section with a bottleneck, and a section with a signal at the end, in Chennai, India. The model captures the congestion formation and dissipation phenomena well and could predict outflow and speed fluctuations generally observed in the field scenarios accurately. The prediction of traffic flow dynamics by the proposed model is also observed to be better when compared with two existing higher-order multi-class models. © The Institution of Engineering and Technology 2020

Real-World Emissions from Diesel Passenger Cars During Peak and Off-Peak Periods

Abstract: Emissions from motor vehicles lead to significant adverse effect on air quality of cities, with many cities reporting ambient air concentration of pollutants well beyond the permissible standards. In this paper, we determine the effect of changing driving patterns during peak and off-peak periods on emissions from diesel passenger cars. Second-by-second emissions of CO, CO2, HC, and NOx were measured during both peak and off-peak periods using portable emission measurement system (PEMS). It is seen that during peak hour, average speed decreases, percentage time spent in acceleration, deceleration, and idling increases, while time spent in cruising mode decreases significantly. Further, EFs are developed for peak and off-peak periods and compared with the Automotive Research Association of India (ARAI) emission standards. The EFs during peak periods are found to be significantly different from off-peak periods. The results of this study would be useful in accurate quantification of emissions.