Experimental analysis of eGLOSA and eGLODTA transit control strategies

Battery powered electric buses have higher energy efficiency, lower emissions and noise when compared to buses with internal combustion engines. However, due to battery charging requirements, their large-scale integration into public transport operations is more complex. This study proposes a novel concept supporting said integration via new control strategies, dubbed e-GLOSA and e-GLODTA. These strategies extend the existing Green Light Optimal Speed and Dwell Time Systems (GLOSA/GLODTA) to account for the specific needs of electric buses. That is, they include the goals of minimizing the energy consumption between charging stations, and maximizing available charging time. At the same time, interference with schedule requirements is minimized. The formulated heuristics are tested on a Bus Rapid Transit (BRT) corridor case study, where different scenarios—such as placement of charging stations and bus regularity—are studied to assess under which conditions each action (maintain speed, accelerate or dwell for a longer time at a stop) is beneficial. Results show that eGLOSA contributes to schedule adherence while eGLODTA allows satisfying charging time constraints

Towards Optimized Deployment of Electric Bus Systems Using Cooperative ITS

In this paper we analyze the impact of using cooperative intelligent transportation systems (C-ITS) to manage electrical bus systems. A simulation-based study is presented where three control strategies are used to regulate the operations of a line, namely bus holding, Green Light Optimal Dwell Time Adaptation (GLODTA) and Transit Signal Priority (TSP). The results show, using a realistic scenario of a major line in Luxembourg City, that buses are efficiently operated without necessarily providing additional priority to public transport, hence without negatively affecting the capacity of the private vehicles system. Benefits in terms of headway regulations, energy consumption and travel time variance reductions are quantified

MULTILINE HOLDING CONTROL AND INTEGRATION OF COOPERATIVE ITS

Transportation is an important sector of the global economy. The rapid urbanization and urban sprawl comes with continuous demand for additional transportation infrastructure in order to satisfy the increasing and variable demand. Public transportation is a major contributor in alleviating traffic congestion in the modern megacities and provide a sustainable alternative to car for accessibility. Public transport operation is inherently stochastic due to the high variability in travel times and passenger demand. This yields to disruptions and undesired phenomena such as vehicles arriving in platoons at stops. Due to the correlation between the headway between vehicles and passenger demand, bunching leads to long waiting time at stops, overcrowded vehicles, discomfort for the passengers and from the operators side poor management of available resources and overall a low of service of the system. The introduction of intelligent transport systems provided innovative applications in order to monitor the operation, collect data and react dynamically to any disruption of the transit system. Advanced Public Transport Systems extended the range of control strategies and their objectives beyond schedule adherence and reliance on historical data alone. Among strategies, holding is a thoroughly investigated and applicable control strategy. With holding, a vehicle is instructed to remain at a designated stop for an additional amount of time after the completion of dwell time, until a criterion is fulfilled. Depending on the characteristics of the line the criterion aim for schedule adherence or regularity or minimization of passenger costs and its components. So far, holding is used for regulating single line operation. Beyond single line, it has been used for transfer synchronization at transfer hubs and recently has been extended to regulate the operation on consecutive stops that are served by multiple lines. The first part of this dissertation is dedicated to real time holding control of multiple lines. A rule based holding criterion is formulated based on the passenger travel time that accounts for the passengers experiencing the control action. Total holding time is estimated based on the size of all passenger groups that interact. The formulated criterion can be applied on all different parts of trunk and branch network. Additionally, the criterion is coupled with a rule based criterion for synchronization and the decision between the two is taken based on the passenger cost. The criterion has been tested for different trunk and branch networks and compared with different control schemes and its performance has been assessed using regularity indices as well as passenger cost indicators for the network in total but also per passenger group. Finally, an analysis has been conducted in order to define under which network and demand configuration multiline control can be preferred over single line control. Results shown that under specific demand distributions multiline control can outperform single line control in network level. Continuously new technologies are introduced to transit operation. Recently, Cooperative Intelligent Transport Systems utilized in the form of Driver Advisory Systems (DAS) shown that can provide the same level of priority with transit signal priority without changing the time and the phases of a traffic light. However, until now the available DASs focus exclusively on public transport priority neglecting completely the sequence of the vehicles and the effects on the operation. In the second part of the dissertation, two widely used DASs are combined with holding in order to meet both the objective of reducing the number of stops at traffic signals and at the same time maintain regularity. Two hybrid controllers are introduced, a combination of two holding criteria and a combination of holding and speed advisory. Both controllers are tested using simulation in comparison to the independent application of the controllers and different levels of transit signal priority. The hybrid controllers can drastically reduce transit signal priority requests while they manage to achieve both objectives