Beshr Sultan

Motorway driver behaviour: studies on car following

This paper will report findings of an instrumented vehicle study aimed at assessing one element of driver behaviour, that of car following, on UK motorways. The paper (re-) calibrates one of the most successful of such models—the Action Point model—using dynamic time series data acquired from field tests with an instrumented vehicle. Probability distributions for a number of parameters from the Action Point model are produced and a number of modifications made in order to enhance its value for use in traffic flow and simulation models. Lastly typical headways are compared with existing studies in the area, finding that current headways are far lower than believed. The rationale behind the adoption of such short headways is examined.

Dynamic Behavioral Data Collection Using an Instrumented Vehicle

A significant problem that has become increasingly apparent in the development of models of driver behavior over the last few years is the absence of reliable data with which simulated processes, such as car following, may be compared. Obtaining such data, and the associated increase in model validity that this would allow, is clearly becoming of greater importance since a reliable baseline is required against which improvements in traffic flow and safety produced by many advanced transport telematics systems can be judged. One source of such data is an instrumented vehicle; a vehicle equipped with relative distance- and speed-measuring sensors that may be deployed in the traffic stream to collect data that are realistic, accurate, and dynamic. The opportunities for data collection afforded by instrumented vehicles are examined, in particular, the construction and testing of a new facility fitted with an optical speedometer, a radar rangefinder (capable of measuring the distance to, and relative speed of, the next vehicle in the traffic stream), and forward- and rear-looking video camera. Examples are given of the use of the vehicle in several current research projects, the operational strategies for which will be presented and discussed along with output. These include experiments on close-following, lane-changing, and the perception of relative speed. In conclusion, future areas of research and development are examined.

Drivers' use of deceleration and acceleration information in car-following process

Understanding driver behavior is important for the development of many applications such as microscopic traffic simulation models and advanced driver assistance systems. The car-following process is an important phase of driving behavior and takes place when a driver follows a lead vehicle and tries to maintain distance and relative speed within an acceptable range. A key to improving knowledge of driver behavior during this process is determining the information perceived by drivers that could influence their decisions. It has been believed for some time that the main kinematic parameters that affect driver judgment in car following are the relative speed, the distance separation, and the absolute speed. The research described investigated whether drivers are also able to use information on the lead vehicles deceleration or acceleration during the car-following process through experimental validation of current car-following hypotheses. For this research, an instrumented vehicle was used to collect a large database of car-following time sequences, the analysis of which showed strong evidence that drivers are able to perceive information such as the deceleration or acceleration of the vehicle being followed, although no empirical relationship was determined. An example demonstrating the importance of such perception shows that modeling a driver trying to avoid a collision with a lead vehicle would lose 20% of its fit accuracy if the lead-vehicle acceleration state were not considered.

Modeling the dynamic cut-in situation

An instrumented vehicle study was performed on a motorway in the United Kingdom to examine the behavior of drivers faced with the cut-in of a vehicle lane-changing into the space between themselves and the preceding vehicle. Data concerning this activity are in short supply and may be used not only in formulating models of human response in driving but also in designing and optimizing driver assistance aids such as adaptive cruise control (ACC). The cut-in vehicle used was equipped with a rear-facing radar unit enabling it to monitor the degree and speed with which drivers attempted to restore their original headway. Cut-ins from both directions were examined—moving in from a slower lane (94 events) and from a faster lane (72 events). The criticality experienced by the follower vehicle ranged from moderately severe [time to collision (TTC) around 10 s and time gap around 0.35 s] to noncritical (lead car’s speed at cut-in greater than follower speed and time headway beyond steady-state values). Findings indicate that the “pullback” behavior, at least over the initial 5 to 10 s, can be described by a constant pullback speed (the rate of decrease of the initial speed), and causative models for this response have been derived using “instantaneous” variables (those that may be calculated on cut-in, such as relative speed and TTC) and longer-term “target” variables, such as desired headway, the former of which have been most effective in describing behavior. Finally, empirical responses have been compared with those that would be produced by ACC systems; it was found that a comparatively close match is produced for low values of relative speed.

FINDINGS ON THE APPROACH PROCESS BETWEEN VEHICLES: IMPLICATIONS FOR COLLISION WARNING

Over the past 10 years there has been a growing body of research into modeling and describing driving behavior, particularly for situations that occur on motorways. This interest has arisen from the need to assess safety and capacity benefits that could be produced by changes to road design, operation, signage, and in-vehicle advanced transport telematics, such as collision warning (CW) or autonomous cruise control. For the most part these investigations have focused on “close” or “car” following, which describes the maintenance of a time- or distance-based following headway. However, often overlooked, and of equal importance, is the “approach” process, describing how a driver decelerates when approaching a slower vehicle. There are several competing theories of the behavioral basis underlying this process, including, for example, those based on time-to-collision or optic flow. There are, however, very few data against which such models can be assessed and systems designed. Presented are the results from an exploratory, instrumented vehicle study designed to assess approach mechanisms. The two key features of the process are explored: the circumstances under which driver deceleration is instigated, and the process governing the control of the deceleration itself. Finally, there is a brief assessment of the implications of these findings for the design of CW systems, in which realistic warnings may prove vital to their acceptance by the driving public.