Modeling Passenger Mode Choice in Tiruchirappalli City: A Regression Analysis Using Stated Preference Data

2024-09-13T02:28:47+00:00

The choice of transportation by passengers is vital for urban transportation forecasting and planning in any city. Mode choice represents the third stage in the planning process and significantly influences a traveler's decision-making. Predicting future travel demand relies on modal shares. To analyze mode choice in a city, the efficiency of passenger travel in urban areas is considered. This study examines the behavior of travelers when selecting a mode for various types of trips in Tiruchirappalli city. The evaluation involves the characteristic features of travelers and uses household survey data collected from the Tiruchirappalli Corporation areas, as well as from bus and railway stations, to gather information on intercity travel between Tiruchirappalli and Chennai. The survey was conducted on both weekdays and weekends. A mode choice model was developed using SPSS and NLOGIT 3.0 software, with multinomial logistic regression applied to analyze the mode choice behavior of travelers and their selected modes for intercity travel in Tiruchirappalli city. This investigation utilized Spearman’s correlation, multinomial logistic regression analysis, and the Likelihood Ratio test to identify the preferred mode choice of passengers in Tiruchirappalli. The SPSS analysis concluded that for intercity travel, a higher percentage of passengers from Tiruchirappalli prefer buses over trains. The NLOGIT software tool was used to model work trips, shopping trips, and educational trips, evaluating mode choice across different trip purposes. Based on the characteristics of trip frequency and the purpose of the journey, bus travel emerged as the most popular choice among passengers for intercity travel, compared to trains in Tiruchirappalli.

Vehicle Accident Prevention on Curve Roads using VANET

2024-11-17T05:32:38+00:00

Vehicular ad hoc network is infrastructure less networks, which have dynamic wireless nodes with the RSU. In real life vehicular communication, data broadcasting is a difficult task for the drivers. This difficulty leads to vehicle accidents on curve roads. Centrifugal force, fog, coverage of vehicle by another vehicle, curved nature of the roads and skill of the drivers are the main reason for vehicle accidents on the curve roads. Due to those factors, vehicle accidents being occurred on the curved nature of roads. Therefore, in this paper vehicle, accident prevention algorithm on the curve roads has been proposed using quantitative research methodology for vehicles to vehicle and vehicle to infrastructure communications. To prevent the accident on curve roads, we have used RSU on the curve roads to create communication with the OBU of the vehicles. For these, we have implemented and tested the proposed algorithm using a simulation tool called NS2.35 for V2V and V2I communication scenario and computed the performance of the algorithm on different parameters of the network. The simulation result of the proposed vehicle accident prevention algorithm on a curve road improved the packet delivery ratio, throughput, end-to-end delay and routing overhead by 11.91%, 4.7%, 11.4% and 1.5% from the previous value of 86.8%, 20.6%, 20.9%, and 22.2% respectively for different number of vehicles

Research

Modeling Passenger Mode Choice in Tiruchirappalli City: A Regression Analysis Using Stated Preference Data

Vehicle Accident Prevention on Curve Roads using VANET