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Modelling and Evaluating Risk Exposure for Motorized Two-Wheelers at Signalized Intersections in Urban Mixed Traffic
Tazim Ameen
Modelling and Evaluating Risk Exposure for Motorized Two-Wheelers at Signalized Intersections in Urban Mixed Traffic - p259–274
Motorized Two-Wheelers (MTWs) are increasingly prominent in traffic systems, posing challenges to road safety. This paper investigates the behavior of MTWs at signalized intersections and analyses factors contributing to the severity of MTW crashes, aiming to address the disparity in safety improvements compared to car occupants. MTWs do not adhere to the “first-in-first-out” rule, instead gradually moving to the front of the queue during the red-phase, a behavior referred to as “seepage”. The Seepage Index measures MTWs’ ability to maneuver to the front of the queue at intersections, increasing their vulnerability to crashes caused by red-light-running vehicles in opposing traffic, quantified as the Risk Exposure Index (REI). A model estimated REI, considering factors like average lane width, and vehicle types. For the current study, both traffic and geometric data were collected from four different sites, focusing on various spatial and traffic characteristics at these intersections, such as average lane width, and the presence of cars, three-wheelers, and heavy vehicles. The findings revealed that MTWs are more exposed at intersections due to their tendency to gather close to the stop-line during the red signal phase. This positioning allows for an earlier discharge during the initial green-phase, which is a more vulnerable period. The results showcased that wider lanes facilitate MTW movement, leading to an increase in REI, while the presence of more heavy vehicles impedes it, causing a decrease in REI. Additionally, the study found that MTWs are 3.415 times more likely to run red signals compared to car drivers, highlighting a significant disparity in risk. The validation process involved employing a confusion matrix to appraise the model's effectiveness at new sites. These findings may provide valuable insights for field engineers aiming to improve road safety for MTWs.
Risk Factors
Signalling gradients
Social Indicators
Transport Research
Transport Geography
Transportation Technology and Traffic Engineering
Modelling and Evaluating Risk Exposure for Motorized Two-Wheelers at Signalized Intersections in Urban Mixed Traffic - p259–274
Motorized Two-Wheelers (MTWs) are increasingly prominent in traffic systems, posing challenges to road safety. This paper investigates the behavior of MTWs at signalized intersections and analyses factors contributing to the severity of MTW crashes, aiming to address the disparity in safety improvements compared to car occupants. MTWs do not adhere to the “first-in-first-out” rule, instead gradually moving to the front of the queue during the red-phase, a behavior referred to as “seepage”. The Seepage Index measures MTWs’ ability to maneuver to the front of the queue at intersections, increasing their vulnerability to crashes caused by red-light-running vehicles in opposing traffic, quantified as the Risk Exposure Index (REI). A model estimated REI, considering factors like average lane width, and vehicle types. For the current study, both traffic and geometric data were collected from four different sites, focusing on various spatial and traffic characteristics at these intersections, such as average lane width, and the presence of cars, three-wheelers, and heavy vehicles. The findings revealed that MTWs are more exposed at intersections due to their tendency to gather close to the stop-line during the red signal phase. This positioning allows for an earlier discharge during the initial green-phase, which is a more vulnerable period. The results showcased that wider lanes facilitate MTW movement, leading to an increase in REI, while the presence of more heavy vehicles impedes it, causing a decrease in REI. Additionally, the study found that MTWs are 3.415 times more likely to run red signals compared to car drivers, highlighting a significant disparity in risk. The validation process involved employing a confusion matrix to appraise the model's effectiveness at new sites. These findings may provide valuable insights for field engineers aiming to improve road safety for MTWs.
Risk Factors
Signalling gradients
Social Indicators
Transport Research
Transport Geography
Transportation Technology and Traffic Engineering