| Abstract |
- Transportation systems are facing safety and operational challenges with a cost
of billions of dollars annually in lost production time and wasted fuel. Infrastructure expansion, previously held as a panacea to most transportation challenges
has lost its appeal due to financial, land-use and environmental constraints. Interest is surging in intelligent transportation systems (ITS) and connected-automated
vehicles (CAV) as potential solutions. Enabled by communication technology, connected vehicle can exchange probe data to enhance safety and mobility. Although
the safety benefits of connected vehicle are not contested, their operational benefits are the subject of heated debate. There is a practical urgency to fill the
knowledge gap related to the transition period from the existing transportation
system dominated by ordinary vehicles to one with a full fleet of connected vehicles. Understanding the potential scenarios during this transformative period willaid decision makers in outlining strategies and enacting mitigation measures that
can guarantee a smooth transition into the impending transportation revolution.
A flexible open source platform, based on SUMO (Simulation of Urban MObility),
has been developed to simulate connected vehicle INFLO (Intelligent Network Flow
Optimization) applications in a multi-lane corridor with mixed connected and ordinary vehicles. These applications consist of Cooperative Adaptive Cruise Control
(CACC), Dynamic speed Harmonization (DSH-HARM) and Queue-Warning (QWARN). Using a well-known data-set, NGSIM I-80 freeway data, vehicle trajectory
reconstructed from video have been parsed and incrementally increasing market
diffusion of connected vehicles and different communication range were simulated
ensuring the same naturalistic driving characteristic as observed in the original
data-set. Traffic performance measures, communication network properties and
dynamical stability of the system have been assessed to determine the impact of
connected vehicles on existing transportation facilities. Several potential scenarios have been considered including the spatio-temporal distribution of connected
vehicles, queue formation, heterogeneous connected vehicles and managed lane.
The research problem has been formulated as a networked dynamical system, where
vehicles form connected vehicle networks (CVN) and through the exchange of
travel related attributes they alter their driving decision. The key elements of
this networked dynamical system are: vehicle dynamics, vehicle connectivity and
vehicle cooperation. From the interaction of this triad, emergent behavior such as
convergence to consensus, synchronization or flocking can be observed. A key tenet
of this work is the reliance on a decentralized approach to vehicle cooperation andcontrol, which averts the drawbacks associated with centralized control in terms of
network resilience, ease and speed of computation and finally infrastructure cost.
Increased market penetration of connected vehicles results in the reduction of travel
time and improvement of travel time reliability. With high market penetration (75-
100%) showing a 20% reduction in travel time. Moreover, lane capacity is observed
to increase from medium market penetration (40-60%) of connected vehicles. The
traffic flow stabilizes in the high market penetration with the flow being confined in
the free flow section of the fundamental diagram. Due to the constantly changing
CVN topology, the effective communication range has minimal to no impacts on the
effectiveness of connected vehicles in all simulated scenarios. However, marginal
benefits are observed for heterogeneous connected vehicles and queue warning scenario with higher communication range. Managed lanes, as travel management
strategy during the initial CV deployment stages, have been shown to outperform
all scenarios in terms of travel time reduction, increase in travel time reliability,
capacity and network robustness.
A word of caution is warranted to this rosy picture. The benefits that increased
market penetration of connected vehicles is expected to generate, should be viewed
in a wider context. Information related to traffic state downstream helps drivers to
enact maneuver that improve the overall traffic condition. However, this response
comes into effect through throttle control, by accelerating or deceleration, which
may have negative impact on emission control.
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