Abstract
Car-following (CF) and lane-changing (LC) behaviours are basic components in driving process. Previous models described them as physical processes with vehicle dynamics and physical criteria. However, drivers’ decisions are greatly influenced by their subjective vision information of various traffic environment elements. To solve this problem, we propose a new concept of traffic environmental vision pressure to explain these two behaviours. The pressure source consists of two parts: nearby vehicles and infrastructures. Pressure models were built to quantify the impact of traffic and roadside infrastructures on these two behaviours. 103 field tests (53 LC and 50 CF) carried out by 40 drivers were conducted to test and calibrate the models. Drivers’ psychological data and vehicle data were collected and postprocessed. Results showed positive relationship between drivers’ psychological stress and vision pressure, which verified the assumption that traffic environmental vision information would have certain effect on driver behaviour. Quantitative thresholds of pressure value were also given and explained with test data. It is concluded that the traffic environmental vision pressure in CF and LC behaviours is quite different, and higher pressure has more impact on behaviour change. We believe that these results will be helpful to study the micro driver behaviour.
Highlights
Car-following (CF) and lane-changing (LC) are common behaviours in driving process
If the driver is satisfied with current vehicle state, he/she will keep following, which can be observed as a CF behaviour
The raw data were cleansed according to two principles: A discarding mandatory lane change behaviour; B deleting discontinuous behaviour records
Summary
Car-following (CF) and lane-changing (LC) are common behaviours in driving process. LC behaviour often happens when the driver cannot stand with current vehicle state. We believe that a human-driver-based behaviour explanatory model needs to explain the original reason for such behaviour from drivers’ view [30]. Based on this concept, a vision-based LCDAS (Lane Change Decision Aid System) was established to detect vehicles and motorcycles following behind in adjacent lanes with a single camera. The influence mechanism of traffic environment on such behaviour still needs a systematic theory based on drivers’ subjective vision information, which may become the foundation of personified autopilot system To interpret this mechanism, we assume that driver behaviour is motivated by the vision pressure that comes from nearby vehicles and roadside infrastructures.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have