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Connected Vehicles (CVs) provide both vehicle trajectory data and occupancy information to the junction controller, which make person-based signal controls to be possible by realizing the importance of reducing person delay. This study presents a coordinated person-based signal control algorithm (C-PBC), which has extended a previously developed approach from isolated junctions to multiple junctions. C-PBC incorporates vehicle information that is outside the CV communication range from the adjacent junction. It also updates data inputs for signal optimization algorithms based on formulated different arrival vehicle trajectory situations and coordinated data supplement algorithms. The developed algorithm has been evaluated using simulation with benchmarking signal control methods under a variety of scenarios involving CV penetration rates and predictive horizons. The results indicate that C-PBC is able to significantly improve person delay reduction when compared with fixed time control and vehicle-based control using CV data in 100% CV penetration rate under saturated flow conditions.

Urban person delay and congestion have becoming an increasing important issues. Connected vehicle (CV) technologies offer opportunities for managing urban traffic efficiently to reduce vehicle delays. The adaptive signal controls in CV environments are vehicle based controls, ignoring the importance of reducing person delay and improving person mobility in urban areas. This paper proposes an innovative Adaptive Person Based Signal Control Algorithm (APBSCA) to minimize person delay at isolated urbans. APBSCA is able to explore flexible phase combinations and stage sequences to find optimal signal timing solutions in certain prediction horizon. The vehicle information including positions, speeds and occupancy levels are collected through CV technology as data sources. A three-level dynamic programming approach is adopted in APBSCA to update the predictive departure time of every vehicle surrounding junctions, which is affected by network environments and signal decisions. APBSCA figures out optimal signal timing parameters that yield highest person delay saving values indicators at isolated junction over the prediction period and implement the corresponding signal timings. The results indicate that APBSCA have better results in reducing average person delay in vehicle in terms of high occupancy vehicles. APBSCA offers significantly average person delay reduction up to 55%. The proposed APBSCA indicates that person based controls have potential benefits in reducing person delay to consistent the future urban goals of improving person mobility over vehicle based controls by better utilizing CV data incorporating occupancy levels.

Shared space is an innovative streetscape design which seeks minimum separation between vehicle traffic and pedestrians. Urban design is moving towards space sharing as a means of increasing the community texture of street surroundings. Its unique features aim to balance priorities and allow cars and pedestrians to co-exist harmoniously without the need to dictate behaviour. There is, however, a need for a simulation tool to model future shared space schemes and to help judge if they might represent suitable alternatives to traditional street layouts. This thesis presents a microscopic mathematical model to simulate pedestrians and 4-wheeled motorised vehicles in shared space schemes. The complete development of the model is addressed: mathematical formulation of three interrelated layers based on the Social Force Model (SFM), software implementation, calibration and validation using the case studies from New Road (Brighton) and Exhibition Road (London). Microscopic pedestrian, vehicle and mixed traffic models are reviewed and evaluated with respect to their ability to reproduce behavioural phenomena, resulting in the SFM being adopted as the most suitable basis for this thesis. The behavioural patterns of shared space users are analysed to identify specific manoeuvres that need consideration. These patterns are realised in a three-layer model: The first layer introduces the flood fill algorithm to define intermediate destinations for agent’s path around obstacles to the final destination. The second layer explains how the SFM is modified for pedestrians and vehicles. The third layer describes conflict avoidance with minimal change of speed and direction. The new mathematical model is calibrated and validated according to defined performance indicators using real data from the two case study sites. The results show that this model is suitable to simulate shared space users but that the physical parameters depend on how a shared space scheme is realised compared to the original philosophy. The achievements of this thesis can be beneficial to urban planners and councils considering the implementation of a new shared space scheme. Open Access