A game-theoretic approach for modelling pedestrian-vehicle conflict resolutions in uncontrolled traffic environments.

The interactions of motorised vehicles with pedestrians have always been a concern in traffic safety. The major threat to pedestrians comes from the high level of interactions imposed in uncontrolled traffic environments, where road users have to compete over the right of way. In the absence of traffic management and control systems in such traffic environments, road users have to negotiate the right of way while avoiding conflict. Furthermore, the high level of movement freedom and agility of pedestrians, as one of the interactive parties, can lead to exposing unpredictable behaviour on the road. Traffic interactions in uncontrolled mixed traffic environments will become more challenging by fully/partially automated driving systems' deployment, where the intentions and decisions of interacting agents must be predicted/detected to avoid conflict and improve traffic safety and efficiency. This study aims to formulate a game-theoretic approach to model pedestrian interactions with passenger cars and light vehicles (two-wheel and three-wheel vehicles) in uncontrolled traffic settings. The proposed models employ the most influencing factors in the road user's decision and choice of strategy to predict their movements and conflict resolution strategies in traffic interactions. The models are applied to two data sets of video recordings collected in a shared space in Hamburg and a mid-block crossing area in Surat, India, including the interactions of pedestrians with passenger cars and light vehicles, respectively. The models are calibrated using the identified conflicts between users and their conflict resolution strategies in the data sets. The proposed models indicate satisfactory performances considering the stochastic behaviour of road users - particularly in the mid-block crossing area in India - and have the potential to be used as a behavioural model for automated driving systems.

Emission modeling at toll plaza under mixed traffic condition using simulation.

Mixed traffic conditions, i.e., the presence of different vehicle classes in a toll lane, causes congestion, leading to extra delay and emissions. The determination of the emission levels in the field is tedious process and thus there is need to look over it. Further, the dynamic toll pricing schemes are well established in developed countries to mitigate the congestion, but its application in developing countries is not observed so far. Hence, an attempt is made in the present study to establish the dynamic toll rates based on emission at toll plazas operating under mixed traffic conditions. The sensitivity analysis is carried out by changing the traffic composition and the approach volume in simulation. After that, the traffic composition and approach volume-based emission estimation equations are developed that can be used to predict the emissions easily in the field. The methodology finally moves towards the development of emission-based toll rates (EBTR).