One typical application of intelligent transportation systems (ITS) is vehicle platooning where a group of vehicles travel with smaller inter-vehicle distance safely, improving energy efficiency as well as road capacity and traffic safety. Truck platooning on highways has been widely studied and showed the aforementioned effects. However, the platooning of buses in urban environments have not been investigated thoroughly in the literature. This paper examines the effects of bus platooning with respect to traffic control and energy consumption.Microscopic traffic simulations have been conducted to demonstrate that bus platooning improves the quality of service of buses and maintains the quality of the traffic flow. Subsequently, driving cycles of buses generated from the simulation study serve as input for an energy consumption analysis, showing that not only bus platooning itself result in a reduction of energy consumption but the traffic signal prioritisation for bus platooning lead to additional energy savings. I. INTRODUCTIONVehicle platooning is one typical application of intelligent transportation systems (ITS), it refers to an operational practice in which multiple vehicles follow one another closely. The intra-platoon distance is maintained shorter compared to today's practice, which leads to reduced aerodynamic drag, particularly for the vehicles in the middle of a platoon. The change in the aerodynamic drag results in reductions of energy usage, traffic congestion, and hence emissions [1-5]. A. Vehicle PlatooningModern driver assistant systems and vehicle-to-vehicle (V2V) communication enable the formation of an electronically coupled platoon [1,5,6]. The direct connection between the members of such a platoon leads to a decreased reaction time of about 0.1 seconds, which is significantly faster than the reaction time of a driver of about 2.5 seconds [1,2,[5][6][7][8]. It is thereby possible to reduce the headways within the platoon. The intra-platoon distance between the vehicles is a key performance indicator of the platooning [4].
<p>Urban air quality directly determines urban quality of life. To improve it, we need to know about local emissions, chemical transformations, and transport processes of the energy-containing vortices in the air. The combination of high-resolution ultrasonic anemometers and state-of-the-art vortex-resolving Large Eddy Simulation (LES) technique is a powerful key tool enabling this understanding. Here, we investigated the dynamics and transport of air with particular focus on nitrogen dioxide (NO<sub>2)</sub> in a highest-traffic street canyon with eight driving lanes in the urban setting of the city of Munich, Germany. Using spatially distributed observations and results from flow-resolving simulations, temporally and spatially resolved patterns and trends of airflow and pollutant concentrations are presented. The airflow conditions in the wide (approx. 80m) urban street canyon are largely decoupled from the synoptic flow over the city. The street is mostly characterized by a channeled, northerly current and weak wind speeds and turbulence kinetic energy (TKE) during the day, independent of prevailing synoptic forcing conditions. At night, the channeled current shifts to southern flow and reverses back to northerly winds in the early morning transition. One exception to this rule are infrequent synoptic easterly flows perpendicular to the street canyon orientation, which lead to a deflection of the flow by the building fronts and a flow reversal to westerly flows at the street level. In this case, TKE is strongly enhanced, and pollutant concentrations are low due to enhanced mixing and inflow of less polluted above-city air. Emission coefficients from the Handbook for Emission Factors for Road Transport (HBEFA) have been used in combination with traffic demand data from loop detectors to compute the respective NO<sub>2</sub> emissions. These emissions show daily peaks in the morning and afternoon hours, and a significant differentiation between weekday, Saturday, and Sundays with less traffic. The individual lanes also differentiate in amount of emission. Linking the results from the point turbulence and NO<sub>2</sub> measurements with the LES approach helps to understand the turbulent air transport and NO<sub>2</sub> in parts of the street canyon where no observations exist. The first results from an LES run in a twofold nested domain with a spatial resolution of &#916;x,y,z = 1m for the street canyon and buildings show promising similarities in airflow patterns and dynamics compared to the observations and are currently undergoing further validation. This study is financed by the Bavarian Ministry of the Environment and Consumer Protection.</p>
Disruptions in public transport operations occur every day. Thus, providing a reliable system is a challenge for operations and planning. This paper gives insights into the dynamics and processes of operations control centers in public transport to reveal potentials for further improvement in reliability. Therefore, directors were interviewed, dispatchers observed, and operations documentation was studied. It has become obvious that the process of dispatching has four different types of call signals (assault, accident, missing replacement, and wish-to-talk) corresponding to different kinds of incidents. The drivers use those call signals to contact the operations control center and initialize different procedures of communication between the dispatchers, drivers, and other involved parties. As the communication is mostly conducted via phone or radio, several improvements are possible, such as training in communications and increased use of information technology in operations. In planning tools, the handling of incidents is marginally supported. As all kinds of incidents can affect the service, they should be represented in planning tools to design more reliable public transport systems. However, they do not need to be represented in full detail. Verbal communication could mostly be reduced to single decisions. Accidents, for example, influence the operation by delayed vehicles and blocked ways. The findings of this work allow a better understanding of operations control centers and reveal their potentials for improvement.
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