The dissertation presents a connected vehicle based traffic signal control model (CVTSCM) for signalized arterials. The model addresses different levels of traffic congestion starting with the initial deployment of connected vehicle technologies focusing on two modules created in CVTSCM. For near/under-saturated intersections, an arterial-level traffic progression optimization model (ALTPOM) is being proposed. ALTPOM improves traffic progression by optimizing offsets for an entire signalized arterial simultaneously. To optimize these offsets, splits of coordinated intersections are first adjusted to balance predicted upcoming demands of all approaches at individual intersections. An open source traffic simulator was selected to implement and evaluate the performance of ALTPOM. The case studies’ field signal timing plans were coordinated and optimized using TRANSYT-7F as the benchmark. ALTPOM was implemented with connected vehicles penetration rates at 25% and 50%, ALTPOM significantly outperforms TRANSYT-7F with at least 26.0% reduction of control delay (sec/vehicle) and a 4.4% increase of throughput for both directions of major and minor streets. This technique differs from traditional traffic coordination which prioritizes major street traffic, and thereby generally results in degrading performance on minor streets. ALTPOM also provides smooth traffic progression for the coordinated direction with little impact on the opposite direction. The performance of ALTPOM improves as the penetration rate of connected vehicles increases. For saturated/oversaturated conditions, two queue length management based Active Traffic Management (ATM) strategies are proposed, analytically investigated, and experimentally validated. The first strategy distributes as much green time as possible for approaches with higher saturation discharge rate in order to reduce delay. For the second approach, green times are allocated to balance queue lengths of major and minor streets preventing queue spillback or gridlock. Both strategies were formulated initially using uniform arrival and departure, and then validated using field vehicle trajectory data. After validation of the modules, the effectiveness of CVTSCM is proven. Then, conclusions and recommendations for future researches are presented at the end.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-5765 |
| Date | 07 May 2016 |
| Creators | Huang, Zhitong |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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