Method for Modeling Lane-Based Driving Discipline of Drivers on Divided Multilane Urban Roads
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 4
Abstract
Lane-based driving (lane-keeping) problems generally prevail in undeveloped and developing countries, where drivers’ lane-keeping behaviors are fairly weak for reasons such as poor surface conditions, undisciplined driving, low-quality lane line visibility, inappropriate number of lanes and lane width, and nonexistence of raised lane lines with vibration. Drivers’ undisciplined lane-based driving behaviors generally cause an increase in dangerous lateral interactions between vehicles. Thus, problems such as irregular lane utilization, difficulties in traffic management, arbitrary lane changing, and illegal overtaking can be observed on divided multilane urban roads. It is necessary to investigate lane-keeping violations on urban roads to find causal parameters and thereafter formulate suitable solutions. This studied aimed to model lane-based driving behavior by considering the parameters of road geometry (e.g., lane width and number of lanes), vehicle type (passenger car, minibus, light commercial vehicle, midibus, bus, truck, lorry) and traffic flow (volume, heavy vehicle ratio, speed, vehicles in adjacent lanes, and roadside parking) on major urban divided roads in three Turkish cities. For this purpose, lateral position data were collected. A probit regression (PR) analysis was conducted to model the relationship between lane-based driving behavior and the examined parameters. It was found that lane width and lane volume have a positive effect, and heavy vehicle ratio (%), vehicle width, speed, and number of lanes have a negative effect as covariates of the proposed model. Numerical tests also showed the developed PR model to be statistically significant and to have a good ability to fit the observed and predicted data for the examined parameters.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (all continuous and categorical data).
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Received: Jun 9, 2020
Accepted: Nov 30, 2020
Published online: Feb 16, 2021
Published in print: Apr 1, 2021
Discussion open until: Jul 16, 2021
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