Models of driving behavior (e.g., car following and lane changing) describe the longitudinal and lateral movements of vehicles in the traffic stream. Calibration and validation of these models require detailed vehicle trajectory data. Trajectory data about traffic in cities in the developing world are not publicly available. These cities are characterized by a heterogeneous mix of vehicle types and by a lack of lane discipline. This paper reports on an effort to create a data set of vehicle trajectory data in mixed traffic and on the first results of analysis of these data. The data were collected through video photography in an urban midblock road section in Chennai, India. The trajectory data were extracted from the video sequences with specialized software, and the locally weighted regression method was used to process the data to reduce measurement errors and obtain continuous position, speed, and acceleration functions. The collected data were freely available at http://toledo.net.technion.ac.il/downloads . The traffic flow characteristics of these trajectories, such as speed, acceleration and deceleration, and longitudinal spacing, were investigated. The results show statistically significant differences between the various vehicle types in travel speeds, accelerations, distance keeping, and selection of lateral positions on the roadway. The results further indicate that vehicles, particularly motorcycles, move substantially in the lateral direction and that in a substantial fraction of the observations, drivers are not strictly following their leaders. The results suggest directions for development of a driving behavior model for mixed traffic streams.

Motorcycles constitute a significant proportion of traffic in many countries but are poorly represented in existing traffic flow theories and simulation software. A new approach to modeling mixed traffic is introduced focusing on depicting the movements of motorcycles. In this study, the characteristic patterns of motorcycle behavior were identified, and the key elements contributing to these patterns were extracted. Then three mathematical models were developed to depict these key elements, which were calibrated by using field data collected at Victoria Embankment in central London. After the calibration procedures, these models were integrated into an agent-based simulation model system. The ability of the simulator to reproduce plausible patterns of car and motorcycle behavior was verified. A number of potential applications of this simulator for the management of mixed traffic streams in urban areas are discussed.

Peak car" and related discussions suggest that especially younger people (age cohort until 30) have less desire to drive and purchase cars. This might though only be true for a limited range of developed countries. This study aims to understand the role of personal background and the country context influencing future car ownership decisions of younger people in seven countries (

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