Showing papers by "Gitakrishnan Ramadurai published in 2019"

Multi-depot Two-Echelon Fuel Minimizing Routing Problem with Heterogeneous Fleets: Model and Heuristic

Abstract: We formulate the two-echelon routing problem considering multiple depots and heterogeneous fleets. Our study (a) presents a Mixed Integer Linear Programming (MILP) formulation with load-dependent fuel minimization objective, (b) uses driving cycles to represent speed variations along a path, (c) allows the vehicles to return to any depot/satellite, and (d) conserves the total number of vehicles at each depot/satellite. We call the problem a Multi-Depot Two-Echelon Fuel Minimizing Routing Problem (MD2E-FMRP). Prior studies assumed there is a fixed number of vehicles available at each satellite/depot, whereas we allow different number of vehicles of each vehicle type at each satellite and depot. Our formulation relaxes several unrealistic assumptions in existing two-echelon formulations and hence has greater practical application. Despite the relaxation of constraints, the running time of our model is comparable to existing formulations. Gurobi optimizer is used to find a better upper bound for up to 56 node instances within a given time limit of 10,000s. We also propose an Adaptive Large Neighborhood Search (ALNS) based heuristic solution technique that outperformed Gurobi in all the tested instances of MD2E-FMRP. We observe an average saving of 13.11% in fuel consumption by minimizing fuel consumed instead of minimizing distance. In general, adapting heterogeneous fleets results in fuel savings and consequently lower emissions compared to using a homogeneous fleet.

Real-world emissions of gaseous pollutants from motorcycles on Indian urban arterials

Abstract: Motor vehicles contribute significantly to the total emissions in a city. Several studies have attempted to quantify emissions from cars, buses, and trucks using laboratory-based or real-world emission tests. However, real-world emissions from motorcycles (or motorized two-wheelers) has not received adequate attention. Unlike developed countries where cars are predominantly used for personal transport, motorcycles are widely used in developing countries. In this study, we quantify emissions of carbon monoxide (CO), hydrocarbons (HC), and nitric oxide (NO) from four typical motorcycles (MC 1, MC 2, MC 3, and MC 4) using real-world emission measurements and develop emission models. We also compare the observed real-world speed-time profiles with the laboratory test cycles and the emission factors developed using real-world emission measurements with the Bharat Stage (BS) emission standards. The real-world emission factors of CO for MC 1, MC 2, MC 3, and MC 4 were 12.3 times, 3.18 times, 9.71 times, and 5.84 times above the respective BS emission standard values. Also, the CO and [HC + NO] emissions from a two-stroke motorcycle (MC 1) were higher than the four-stroke motorcycles. The models presented in this paper can be used to accurately quantify real-world emissions from motorcycles on Indian urban arterials and to formulate policies for air quality improvement.

Numerical Study with Field Data for Macroscopic Continuum Modelling of Indian Traffic

Abstract: Heterogeneous traffic as observed in several south Asian countries is characterized by complex interactions of widely varying vehicle types that do not follow lanes and with smaller vehicles filling any gaps available. This paper discusses on four main components of macroscopic simulation of traffic flow in the Indian traffic context. One of the prime component, namely the traffic flow model, is discussed in detail with respect to the continuum modelling approach.

Analytical Model for Queue Length Estimation at Signalized Intersections from Travel Time

Abstract: Queue formation and dissipation are a major feature of urban road networks and estimation of queue lengths is important in traffic flow modeling. In this study, we propose a methodology for estimating the queue length at signalized intersections using only travel time data and signal timing information. We use analytical equations to trace the trajectory of the vehicle and estimate the location of the vehicle in queue. We compare the performance of our Queue Location Estimation Using Travel Time data (QLE-UTT) with another methodology which used travel time data from multiple detectors and kinematic equations for vehicle location estimation. The performances of both methodologies were found to be comparable; however, the limited data requirement and simplicity of QLE-UTT makes the methodology attractive for practical implementation. The vehicle locations estimated from QLE-UTT was used to estimate the maximum queue length in a signal cycle using a probabilistic approach. This methodology for queue length estimation was tested both on a simulated dataset, for undersaturated, saturated, and oversaturated traffic conditions, and the real-world NGSIM dataset. The methodology combining QLE-UTT and the probabilistic approach was found to estimate the vehicle trajectories and queue lengths with good accuracy.

Temporal Analysis of a Bus Transit Network

Abstract: Transit networks are essentially temporal with their topology evolving over time. While there are several studies on the topological properties of bus transit networks, none of them have captured the temporal network characteristics. We present a temporal analysis of a bus transit network using snapshot representation. We propose a supply-based weight measure, called the service utilization factor (SUF), and define it as the passenger demand per trip between two bus stops. We evaluate the complex network properties in three weighted cases for a bus network in India, using the number of overlapping routes, passenger demand between routes and SUF as weights. The study network is well-connected with 1.48 number of transfers on average to travel between any two stops over the day. The temporal analysis indicated an inadequate number of services in peak periods and route redundancy across the time periods. We identified the existing and potential hubs in the network, which were found to vary across time periods. The network has strongly connected communities that remain constant across the day. Our conclusions exemplify the importance of temporally analyzing transit networks for improving their efficiency.

Simulated Annealing Algorithm for Multi Depot Two-Echelon Capacitated Vehicle Routing Problem

Abstract: Although urban freight transport is a significant contributor to the development of a country, it has adverse effects on the environment and the quality of life in urban areas. To reduce these adverse effects, we can deploy sustainable city logistic strategies. Scheduling and routing of vehicles is a crucial decision in city logistic strategies. Hence, in this paper, we solve the Multi-Depot Two Echelon Capacitated Vehicle Routing Problem (MD2E-CVRP), which is a variant of Vehicle Routing Problem (VRP) with heterogeneous fleets at both levels. Since VRP is NP-hard, we have proposed a Simulated Annealing (SA) based heuristic solution algorithm and have tested it on the standard 2E- CVRP and MD2E-CVRP instances. The results obtained from SA have a good solution quality at just one-fiftieth of computational time using CPLEX and was found to be faster than Adaptive Large Neighborhood Search (ALNS) with only a marginal drop in solution quality.

Multi-class Traffic Flow Model Based on Three-Dimensional Flow-Concentration Surface

Abstract: This paper proposes a continuum model based on a three-dimensional flow-concentration surface for multi-class traffic. The model assumes that the flow of any vehicle class is a function of the class density as well as the fraction of road area occupied by other vehicle classes. By considering occupancy of road area instead of lane occupancy, the model effectively describes traffic flow that does not follow lane discipline. The propagation speed of small disturbance (PSSD), conventionally defined from the two-dimensional flow–density relationship, is reformulated for each class using a three-dimensional flow–concentration surface. Using the proposed PSSD and a speed–area occupancy (speed- A O ) relationship, a second-order continuum model for multi-class traffic is formulated. The speed– A O relationship captures class-specific congestion and replicates the gap-filling behaviour commonly observed in lane-indisciplined traffic. Properties of the proposed model are validated theoretically where possible, and through numerical simulation when theoretical derivations are cumbersome. Numerical simulation of the proposed multi-class traffic model replicates field-observed phenomena such as shockwaves and rarefaction waves, local cluster effect, and gap-filling behaviour. Finally, the model is calibrated using field traffic data collected on a road section with bottleneck, and is found to replicate class-wise vehicle flows and speeds, and stop-and-go phenomena.