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 c...

General Lane-Changing Model MOBIL for Car-Following Models

Currently autonomous or self-driving vehicles are at the heart of academia and industry research because of its multi-faceted advantages that includes improved safety, reduced congestion, lower emissions and greater mobility. Software is the key driving factor underpinning autonomy within which planning algorithms that are responsible for mission-critical decision making hold a significant position. While transporting passengers or goods from a given origin to a given destination, motion planning methods incorporate searching for a path to follow, avoiding obstacles and generating the best trajectory that ensures safety, comfort and efficiency. A range of different planning approaches have been proposed in the literature. The purpose of this paper is to review existing approaches and then compare and contrast different methods employed for the motion planning of autonomous on-road driving that consists of (1) finding a path, (2) searching for the safest manoeuvre and (3) determining the most feasible trajectory. Methods developed by researchers in each of these three levels exhibit varying levels of complexity and performance accuracy. This paper presents a critical evaluation of each of these methods, in terms of their advantages/disadvantages, inherent limitations, feasibility, optimality, handling of obstacles and testing operational environments. Based on a critical review of existing methods, research challenges to address current limitations are identified and future research directions are suggested so as to enhance the performance of planning algorithms at all three levels. Some promising areas of future focus have been identified as the use of vehicular communications (V2V and V2I) and the incorporation of transport engineering aspects in order to improve the look-ahead horizon of current sensing technologies that are essential for planning with the aim of reducing the total cost of driverless vehicles. This critical review on planning techniques presented in this paper, along with the associated discussions on their constraints and limitations, seek to assist researchers in accelerating development in the emerging field of autonomous vehicle research.

Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

The agent computing paradigm is rapidly emerging as one of the powerful technologies for the development of large-scale distributed systems to deal with the uncertainty in a dynamic environment. The domain of traffic and transportation systems is well suited for an agent-based approach because transportation systems are usually geographically distributed in dynamic changing environments. Our literature survey shows that the techniques and methods resulting from the field of agent and multiagent systems have been applied to many aspects of traffic and transportation systems, including modeling and simulation, dynamic routing and congestion management, and intelligent traffic control. This paper examines an agent-based approach and its applications in different modes of transportation, including roadway, railway, and air transportation. This paper also addresses some critical issues in developing agent-based traffic control and management systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of agent technology in traffic and transportation systems are discussed.

A Review of the Applications of Agent Technology in Traffic and Transportation Systems

We generalize a wide class of time-continuous microscopic traffic models to include essential aspects of driver behaviour not captured by these models. Specifically, we consider (i) finite reaction times, (ii) estimation errors, (iii) looking several vehicles ahead (spatial anticipation), and (iv) temporal anticipation. The estimation errors are modelled as stochastic Wiener processes and lead to time-correlated fluctuations of the acceleration. We show that the destabilizing effects of reaction times and estimation errors can essentially be compensated for by spatial and temporal anticipation, that is, the combination of stabilizing and destabilizing effects results in the same qualitative macroscopic dynamics as that of the, respectively, underlying simple car-following model. In many cases, this justifies the use of simplified, physics-oriented models with a few parameters only. Although the qualitative dynamics is unchanged, multi-anticipation increase both spatial and temporal scales of stop-and-go waves and other complex patterns of congested traffic in agreement with real traffic data. Remarkably, the anticipation allows accident-free smooth driving in complex traffic situations even if reaction times exceed typical time headways.

https://arxiv.org/pdf/cond-mat/0404736.pdf

Delays, inaccuracies and anticipation in microscopic traffic models

This paper presents data, collected from video-recording, on the microscopic details of merging and weaving manoeuvres under congested traffic conditions. Based on these observations, a classification of the manoeuvres into free, forced and cooperative lane changes is proposed. A new lane change model is developed, incorporating explicit modelling of vehicle interactions using intelligent agent concepts. The model was implemented in the ARTEMiS traffic simulator, and several hypothetical test studies were conducted to demonstrate the capabilities of the new model. The results show that the model is able to reproduce the observed behaviour of individual vehicles in terms of speed, gap acceptance and conflict-resolution in all three types of lane change manoeuvres, and hence, it is able to simulate highly congested flow conditions in a realistic manner. The macroscopic results in terms of speed-flow relationship are close to the typical expected results. The model can simulate both freeways and signalised urban arterial networks.

Modelling vehicle interactions in microscopic simulation of merging and weaving

This paper introduces Simulation of Intelligent TRAnsport Systems (SITRAS), a massive multi-agent simulation system in which driver-vehicle objects are modelled as autonomous agents. The simulation outputs can be used for the evaluation of Intelligent Transport Systems applications such as congestion and incident management, public transport priority and dynamic route guidance. The model concepts and specifications, and the first applications of the model in the area of incident modelling in urban arterial networks were described in previous publications. This paper presents the details of the lane changing and merging algorithms developed for the SITRAS model. These models incorporate procedures for ‘forced’ and ‘co-operative’ lane changing which are essential for lane changing under congested (and incident-affected) traffic conditions. The paper describes the algorithms and presents simulation examples to demonstrate the effects of the implemented models. The results indicate that only the forced and cooperative lane changing models can produce realistic flow-speed relationships during congested conditions.

Modelling lane changing and merging in microscopic traffic simulation

Research into developing more reliable microscopic traffic simulation models is seriously hampered by the availability of suitable microscopic data for calibration and validation purposes. This paper presents a review of several data collection technologies that the authors have been experimenting with. The methods include (i) video recording (ii) the use of differential GPS (DGPS) and (iii) an instrumented vehicle fitted with the S.M.S. Drive Recorder system. Examples of data collection with each method are briefly described, and some of the results presented to illustrate the capabilities of the methods. The last section of the paper summarises the advantages and limitations of each method and conclusions are drawn on their suitability for the required purpose. The experiments shows that each method can provide some useful results for microscopic simulation model development, but cannot provide continuous spacing-, speed- and acceleration profiles of large vehicle platoons moving through various traffic scenarios. Further research is required to develop more sophisticated data collection techniques and to investigate such aspects of driver behaviour as aggressiveness, and factors influencing lane selection.

Review of Data Collection Methods for Microscopic Traffic Simulation

The purpose of this study is to investigate previously unknown effects of speed control devices on fundamental characteristics of traffic, such as vehicle headway distribution, absorption capacity and average delays to vehicles entering from driveways and pedestrian crossing opportunity. Headway data were collected at seven sites in the Sydney Metropolitan Area, under various levels of traffic flow and at various distances from the devices. The results demonstrate that although speed control devices do have some negative side-effects which are sometimes statistically significant, the magnitudes of the increase in average delays and the decrease in absorption capacities around the devices are below the level that would conceivably influence the practical crossing and merging abilities. These minor inconveniences to pedestrians and drivers are confined to the immediate vicinity of the devices and are, by far, outweighed by the benefits in terms of accident savings over the whole length of the street.

Peter Hidas

Papers

Modelling vehicle interactions in microscopic simulation of merging and weaving

Modelling lane changing and merging in microscopic traffic simulation

Review of Data Collection Methods for Microscopic Traffic Simulation

Negative effects of mid-block speed control devices and their importance in the overall impact of traffic calming on the environment