Mandatory Lane Change Research Articles

The Study of Location Specific Lane Change Impacts on Traffic Delay using Extended Cell Transmission Model

This paper comprehensively evaluates the influence of location specific lane change executions on delay and queue length. The extended macroscopic Cell Transmission Model (CTM) based lane change model has been developed by adopting the formulations of diverging and merging in one-way traffic flow. The extended CTM model uses a pre-determined lane change rate and traffic parameters including free flow speed, jam density, cell length and time-step while the inflow parameters were generated form real traffic data collected in Bandar Sunway, Malaysia. The results demonstrate that the lane change maneuver approaching the exit of intersection incurs the highest delay. From real observation, drivers have high tendency to perform mandatory lane changing compared with discretionary lane change in urban arterials. The results can be further used to develop lane change assistance model to improve the traffic flows.

The influence of heavy vehicles on traffic dynamics around on-ramp system: Cellular automata approach

Although the on-ramp system has been widely studied, the influence of heavy vehicles is unknown because researchers only investigate the traffic dynamics around on-ramp system under homogeneous traffic conditions, which is different in real-world settings. This paper uses an improved cellular automaton model to study the heterogeneous traffic around on-ramp system. The forward motion rules are improved by considering the differences of driving behavior in different vehicle combinations. The lane change rules are improved by reflecting the aggressive behavior in mandatory lane changes. The phase diagram, traffic flow, capacity and spatial-temporal diagram are analyzed under the influences of heavy vehicles. The results show that by increasing the percentage of heavy vehicles, there will be more severe traffic congestion around on-ramp system, lower saturated flow and capacity. Also, the interactions between main road and on-ramp have been investigated. Increasing the percentage of heavy vehicles at the upstream of the conflict area on the main road or restricting heavy vehicles on the outside lane of the main road will deteriorate the performance of on-ramp. While the main road will have better performance as the percentage of heavy vehicles on the on-ramp increases when the on-ramp inflow rate is not low.

An optimal mandatory lane change decision model for autonomous vehicles in urban arterials

ABSTRACTAutonomous driving has become a popular topic in both industry and academia. Lane-changing is a vital component of autonomous driving behavior in arterial road traffic. Much research has been carried out to investigate discretionary lane changes for autonomous vehicles. However, very little research has been conducted on assisting autonomous vehicles in making mandatory lane changes (MLCs), which is the core of optimal lane-specific route planning for autonomous vehicles. This research aims to determine the best position for providing MLC instruction to autonomous vehicles. In this article, an optimization model is formulated to determine the optimal position at which an instruction to change lanes should be given through automotive navigation systems. First, the distribution of time spent waiting for safe headway to make a lane change is modeled as an exponential distribution. Lane-specific travel times are then calculated for vehicles in various situations by applying traffic shockwave theory and horizontal queuing theory. Finally, the expected travel time is derived for a vehicle receiving a lane change instruction to change lanes at an arbitrary position along the road. The proposed model is validated by a comparison with a simulation model in VISSIM. Additional experiments show that the instruction should be given earlier in the case of denser traffic or higher travel speed in the target lane and that vehicles can save considerable time, if they follow the guidance provided by the proposed model. The proposed model can be applied to guide autonomous vehicles to travel an optimal route.

Operational Efficiency Evaluation of Intersections with Dynamic Lane Assignment Using Field Data

The dynamic lane assignment at signalized intersections is a possible countermeasure to address the traffic demand variability problem. However, the operational efficiency is affected by the unfamiliarity of the drivers. This paper evaluates the operational efficiency of the intersections with dynamic lane assignment using field data collected at five intersections in China. A total of 63488 vehicles were captured, which were divided into four groups according to the lanes they drive on: Group 1, the variable approach lane; group 2, the lane adjacent to the variable lane with the same lane-use; group 3, the lane adjacent to the variable lane with different lane-use of the variable lane; and group 4, the lanes with the same lane-use as the variable lane at other approaches of the intersection. The statistical analysis was conducted to identify the difference of saturation flow rate among the four groups. A saturation flow rate adjustment model was established accordingly. Results indicate that the using of the dynamic lane assignment decreases the saturation flow rate of the variable lane and the adjacent lane with different lane-use 22.86% and 9.80%, respectively. For the variable lane, the reduction of the saturation flow rate comes from three aspects: the unequal distribution of traffic (8.9%), the mandatory lane-changing (10.7%), and the lane blockage (4.9%).

An entropy-based analysis of lane changing behavior: An interactive approach

ABSTRACTObjectives: As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety.Methods: The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided.Results: Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions.Conclusions: The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would match discretionary lane changing behavior. This article states that driver behaviors would be in the nonadditive entropy domain to provide a safe traffic stream and hence with vehicle accident prevention in mind.

A probability model for discretionary lane changes in highways

Lane changes are made frequently on the road and are therefore an important component in analyzing traffic situations. This behavior interferes with surrounding traffic, causes negative shockwaves, and may even lead to collisions. Lane changes can be categorized into mandatory lane changes and discretionary lane changes. There are various factors influencing the decision-making involved in discretionary lane changes, including relative velocity between target and original lane, and lead and lag gaps. The purpose of this paper is to present a stochastic approach for modeling discretionary lane changes with influential factors of velocity and spacing advantages. Using Next Generation Simulation (NGSIM) data, we proposed an exponential probability model with speed difference and lead gap difference between the target lane and the original lane. By transformed linear regression, these traffic variables have actual influences on the lane change probability of discretionary lane changes. The found results can be used for lane change models in microscopic traffic simulation.

A new bus lane on urban expressway with no-bay bus stop

The sharp increase in residents and vehicles causes heavy traffic pressure in many cities. To ease traffic congestion, it has been the common sense that we should develop public transit system. The priority of the bus appears particularly necessary with the rapid development of the public transport system. The bus lane is an important embodiment of the bus priority. Focusing on the problem of the unreasonable dedicated bus lane (DBL) under the lower ratio of buses, this paper proposed a new bus lane with limited physical length. And this bus lane can reduce the lane-changing conflict caused by the buses and cars running on roads without bus lanes. Based on the cellular automata (CA) traffic flow model and the lane-changing behavior of the vehicle including the optional lane-changing and the mandatory lane-changing, a three-lane traffic model with an isolated no-bay bus stop is proposed. The ordinary three-lane traffic without a bus lane and the cases of traffic with a DBL or the proposed bus lane are simulated, and the comparisons in the form of the fundamental diagrams are made among them. It is shown that the no-bay bus stop can act as a bottleneck on the traffic flow because of the mandatory lane-changing behavior. Under a certain ratio of the bus number to the total vehicles number, (1) the traffic with the proposed bus lane has less lane-changing conflict and can provide higher traffic capacity than the ordinary traffic without a bus lane, (2) compared with the DBL, the proposed bus lane is advantageous in easing congestion on the ordinary lanes when the traffic flow is high and can avoid unreasonable allocation of the road resources.

Study of Mandatory Lane Change Execution Behavior Model for Heavy Vehicles and Passenger Cars

Lane changing is one of the basic driver behavior interactions in microscopic traffic simulations for traffic, safety, and transportation system analysis. Although many traffic simulations pay attention to the decision process for lane changing, the execution process is often simplified or even ignored. This paper presents a study of lane change execution of heavy vehicles and passenger cars in a traffic situation with a blocked lane. A video camera was used to collect data from an arterial road in Melbourne, Australia. This paper investigates the behavior of heavy vehicles and passenger cars in mandatory lane changes and proposes a model framework for the execution of lane changes with regard to the emergency status and the impact of surrounding traffic for individual drivers who are changing lanes. The distance to the blockage was used to denote the emergency status. For the impact of the surrounding traffic, it was assumed that the driver would adjust the execution if a traffic conflict were detected and would continue the lane change if there were no conflict. A probability model was developed to interpret the driver’s choice of whether to continue the lane change. The data analysis found that the lane change performance of heavy vehicles differed from that of passenger cars. Therefore, the model was calibrated for heavy vehicles and passenger cars separately. In conclusion, the paper provides a framework of the future work of lane change execution models on traffic simulation to assess the traffic safety and road efficiency.

Optimal location of advance warning for mandatory lane change near a two-lane highway off-ramp

Improper mandatory lane change (MLC) maneuvers in the vicinity of highway off-ramp will jeopardize traffic efficiency and safety. Providing an advance warning for lane change necessity is one of the efficient methods to perform systematic lane change management, which encourages smooth MLC maneuvers occurring at proper locations to mitigate the negative effects of MLC maneuvers on traffic flow nearby off-ramp. However, the state of the art indicates the lack of rigorous methods to optimally locate this advance warning so that the maximum benefit can be obtained. This research is motivated to address this gap. Specifically, the proposed approach considers that the area downstream of the advance warning includes two zones: (i) the green zone whose traffic ensures safe and smooth lane changes without speed deceleration (S-MLC); the start point of the green zone corresponding to the location of the advance warning; (ii) the yellow zone whose traffic leads to rush lane change maneuvers with speed deceleration (D-MLC). An optimization model is proposed to search for the optimal green and yellow zones. Traffic flow theory such as Greenshield model and shock wave analysis are used to analyze the impacts of the S-MLC and D-MLC maneuvers on the traffic delay. A grid search algorithm is applied to solve the optimization model. Numerical experiments conducted on the simulation model developed in Paramics 6.9.3 indicate that the proposed optimization model can identify the optimal location to set the advance MLC warning nearby an off-ramp so that the traffic delay resulting from lane change maneuvers is minimized, and the corresponding capacity drop and traffic oscillation can be efficiently mitigated. Moreover, the experiments validated the consistency of the green and yellow zones obtained in the simulation traffic flow and from the optimization model for a given optimally located MLC advance warning under various traffic regimes. The proposed approach can be implemented by roadside mobile warning facility or on-board GPS for human-driven vehicles, or embedded into lane change aid systems to serve connected and automated vehicles. Thus it will greatly contribute to both literature and engineering practice in lane change management.

Mandatory Lane Change Model and Time Delay under Traffic Emergency Incidents

This paper proposed a kind of mandatory lane change model from the different three aspects. At the same time, it also researched the time delay of the vehicle under this situation and gave the reification of the time delay. The simulational results showed that the model was effectively and the analysis of the time delay was reasonable.

Investigation of Discretionary Lane-Change Characteristics Using Next-Generation Simulation Data Sets

In this article, we investigate discretionary lane change (DLC) characteristics using Next Generation SIMulation (NGSIM) data sets. We first develop a set of heuristic rules to automatically filter out abnormal samples from a massive trajectory data set and identify DLC trajectories from a mixture of mandatory lane change (MLC) and DLC trajectories. Then, we investigate a variety of DLC characteristics. We demonstrate that the kernel part of every normal DLC trajectory can be approximately depicted by a certain fifth-order polynomial. Moreover, we discuss the definition of begin/end points of DLC actions and show that the duration time of DLC actions follows a log-normal distribution with respect to navigation speed. All the findings can help promote temporal and spatial accuracy of lane changing models.

Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees

A lane changing assistance system that advises drivers of safe gaps for making mandatory lane changes at lane drops is developed. Bayes classifier and decision-tree methods were applied to model lane changes. Detailed vehicle trajectory data from the Next Generation Simulation (NGSIM) data set were used for model development (U.S. Highway 101) and testing (Interstate 80). The model predicts driver decisions on whether to merge or not as a function of certain input variables. The best results were obtained when both Bayes and decision-tree classifiers were combined into a single classifier using a majority voting principle. The prediction accuracy was 94.3% for nonmerge events and 79.3% for merge events. In a lane change assistance system, the accuracy of nonmerge events is more critical than merge events. Misclassifying a nonmerge event as a merge event could result in a traffic crash, whereas misclassifying a merge event as a nonmerge event would only result in a lost opportunity to merge. Sensitivity analysis performed by assigning higher misclassification cost for nonmerge events resulted in even higher accuracy for nonmerge events but lower accuracy for merge events.

Cellular automaton simulation of muti-lane traffic flow including emergency vehicle

Based on the analysis of urban road traffic flow affected by emergency vehicle, a muti-lane cellular automaton model is established. Three characteristic variables are introduced to modify the lane change rules, including the give-way state variable, the affected areas of police siren and the safe distance for mandatory lane change. Numerical simulation results indicate that lane number and hybrid vehicle scale factor have a great influence on vehicle speed and lane change number in low-density range. And the parameter setting for affected areas of police siren changes the lane change number within a certain range. Meanwhile, the parameter of safe distance for mandatory lane change mainly affects emergency vehicle speed and lane change number. The study indicates that the appearance of emergency vehicle interferences with traffic flow of lower density obviously, and the proposed parameters make cellular automaton model closer to the actual traffic scenarios under emergency conditions.

A simple lane change model for microscopic traffic flow simulation in weaving sections

This paper presents the development and validation of a simple microscopic traffic simulation model for driver lane change behavior in freeway weaving sections. The simple model, called the weaving model, is computationally efficient and requires fewer calibration parameters. The model's calibration parameters can be found from the field data which makes the calibration process simpler compared to more detailed simulation models. Two types of lane change logics were developed: a) discretionary and b) mandatory. Discretionary lane change logic considers a driver's dissatisfaction with his/her current speed and feasibility of speed gain in the target lane. A mandatory lane change is performed for vehicles exiting, entering or moving to a preferred lane on the highway. The weaving model was validated at the microscopic level by comparing the trajectories of vehicles from simulation with the field data, whereas macroscopic validation was performed using statistical and error tests for average speed and section density. Lane change frequency from the proposed model was also compared with the field data and good agreement was observed. The results from the proposed model were compared with two popular simulation models, VISSIM and AIMSUN, which indicated that the proposed model performed at least as good as these models.

Microscopic modeling and control logic for incident-responsive automatic vehicle movements in single-automated-lane highway systems

Automatic response to lane-blocking incidents is a critical issue in the field of automated highway systems (AHS). Accordingly, this paper presents a microscopic vehicular control methodology for automatic-control (AC) vehicular movements in response to lane-blocking incidents in the AHS environment. The embedded traffic control logic is based on the basic safety requirements for automatic-control lane traffic maneuvers responding to lane-blocking incidents in the single-automated-lane AHS environment. Accordingly, respective automated vehicular control models are proposed to deal with AC vehicles moving in three corresponding sequential phases, i.e., (1) AC platoon approaching the incident site from the blocked lane, (2) mandatory lane changing and mixed car following in the adjacent lane, and (3) AC platoon reforming downstream from the incident site in the blocked automated lane. Using a microscopic simulation model which embeds these proposed models, preliminary tests are conducted to investigate the relative performance of the proposed method in various traffic flow and control scenarios. The resulting numerical results, including simplified sensitivity analyses, indicate that the proposed microscopic traffic control logic permits regulating automatic-control vehicular movements in response to the effects of lane-blocking incidents on traffic flows either in control-free lanes or in the automatic-control lanes. Implications of the results and some findings are discussed for further research.

General Lane-Changing Model MOBIL for Car-Following Models

A general model (minimizing overall braking induced by lane change, MOBIL) is proposed to derive lane-changing rules for discretionary and mandatory lane changes for a wide class of car-following models. Both the utility of a given lane and the risk associated with lane changes are determined in terms of longitudinal accelerations calculated with microscopic traffic models. This determination allows for the formulation of compact and general safety and incentive criteria for both symmetric and asymmetric passing rules. Moreover, anticipative elements and the crucial influence of velocity differences of these car-following models are automatically transferred to the lane-changing rules. Although the safety criterion prevents critical lane changes and collisions, the incentive criterion takes into account the advantages and disadvantages of other drivers associated with a lane change via the “politeness factor.” The parameter allows one to vary the motivation for lane changing from purely egoistic to more cooperative driving behavior. This novel feature allows one first to prevent lane changes for a marginal advantage if they obstruct other drivers and second to let an aggressive driver induce the lane change of a slower driver ahead in order to no longer be obstructed. This phenomenon is common for asymmetric passing rules with a dedicated lane for passing. The model is applied to traffic simulations of cars and trucks with the intelligent driver model as the underlying car-following model. An open system with an on-ramp is studied, and the resulting lane-changing rate is investigated as a function of the spatial coordinate as well as a function of traffic density.