Modeling Vehicle Interactions during Lane-Changing Behavior on Arterial Streets

Abstract

Lane-changing algorithms have attracted increased attention during recent years in traffic modeling. However, little has been done to address the competition and cooperation of vehicles when changing lanes on urban streets. The main goal of this study is to quantify the vehicle interactions during a lanechanging maneuver. Video data collected at a busy arterial street in Gainesville, Florida, were used to distinguish between free, forced, and competitive/cooperative lane changes. Models particularly for competitive/cooperative lane changes were developed, depending on whether the following vehicle cooperates with the subject vehicle or not. By referring to the "TCP/IP" protocol in computer network communications, a sequence of "hand-shaking" negotiations were designed to handle the competition and cooperation among vehicles. The developed model was implemented and validated in the CORSIM microsimulator package, with the simulation capabilities compared against the original lane-changing model in CORSIM. The results indicate that the new model better replicates the observed traffic under different levels of congestion.

Lane-changing behavior on urban streets: A focus group-based study

“…Lane changes on arterial streets, especially under congested conditions, are characterized by various invoking reasons, such as stopped buses, lane channelization changes, turning movements, etc. Furthermore, driver interactions under congestion are frequent, and driver characteristics may play a significant role in lane changes (Sun and Kondyli, 2010). Existing microsimulators, such as CORSIM and AIMSUN, incorporate different driver types.…”

Lane‐Changing Behavior on Urban Streets: An “In‐Vehicle” Field Experiment‐Based Study

“…Lane changes on arterial streets, especially under congested conditions, are characterized by different invoking reasons, such as stopped buses, changes of lane channelization, turning movements, etc. Furthermore, driver interactions under congestion are frequent, and driver characteristics may play a significant role in lane changes (Sun and Kondyli, 2010). Existing micro‐simulators, such as CORSIM and AIMSUN, incorporate different driver types.…”

“…Comparing to Sun and Elefteriadou (unpublished results), which is more comprehensive, including focus group study, “in‐vehicle” experiment, model implementation, and simulation/calibration/validation, but directly uses the results of the focus group study and “in‐vehicle” experiment, this article mainly introduces the “in‐vehicle” experiment (the preparation and implementation issues), without touching the micro‐simulation part. The main objective is to observe the drivers’ action under various lane‐changing scenarios, and use both the personal characteristics and “in‐vehicle” trajectory data to classify drivers into different groups according to the lane‐changing maneuvers they performed in an urban street environment.…”

Time-Varying Lane-Based Capacity Reversibility for Traffic Management

“…Nowadays, many metropolitan areas have adopted various traffic management techniques (Adeli and Samant, 2000; Samant and Adeli, 2000, 2001; Karim and Adeli, 2002a,b, 2003a,b,c; Ghosh‐Dastidar and Adeli, 2003; Adeli and Jiang, 2003; Jiang and Adeli, 2004a,b, 2005; Liu and Danczyk, 2009; Hamad et al, 2009; Mirchandani et al, 2010; Ng et al, 2010; Sun and Kondyli, 2010; Ye and Zhang, 2010) to maintain an efficient flow of traffic. Capacity reversibility strategy (a.k.a.…”