| dc.description.abstract | Connected vehicle technology has the potential to improve the performance of the transportation system. The real-time traffic information communicated between connected vehicles and infrastructure enables a more efficient management and use of the transportation system. This new technology equips vehicles to receive real-time information from their surroundings, which can warn them of approaching congestion. The emergence of connected vehicles that facilitate data exchange among vehicles and infrastructure has the potential to improve mobility, increase safety, and reduce the harmful environmental impacts of travel. Unfortunately, most of the studies that evaluate the impacts of connected vehicle technology focus only on highway performance. Moreover, these studies often ignore the impacts of uncertainties and unpredictable factors in evaluating the connected environment performance. One of these uncertainties is the behavior of travelers. Unlike the autonomous vehicles’ user, the driver of a connected vehicle has decision making power. This technology helps the users to make more informed decisions by providing real-time traffic information of the roads on their path. However, the users’ acceptance rate in response to the given information is still a significant parameter affecting the overall performance of the transportation system.
In order to address the questions concerning the impacts of travelers’ willingness to comply with the provided information, this research examined travelers’ responses to the real-time rerouting information provided through connected vehicle technology and its impact. An internet-based survey was employed to investigate the impacts of different factors such as socio-economic characteristics, time saving, visibility of congestion, and the length of the trip on drivers’ willingness to follow the rerouting information. A total of 1881 complete responses were collected from a random nationwide sample of people living in small and medium-sized metropolitan areas (SMMAs). The results of the study indicated the importance of trip and socio-economic characteristics of users on their willingness to follow the rerouting advice. Comparison of the probability of the results of the study demonstrated a higher percentage of acceptance to the received information from connected vehicles compared to dynamic message signs and other similar technologies.
The research goal was to investigate the impacts of communication technology on the transportation system. There are three types of simulation frameworks in evaluating the network performance: microscopic, mesoscopic and macroscopic simulation models. Due to the significant effects of individual travelers on network performance, the microscopic simulation model is more appropriate. Most of the studies in this area focus on the highways or a small network. However, an accurate microsimulation model with different types of roads is required to be able to generalize the results for the real-world applications. To this end, Simulation of Urban Mobility (SUMO) is combined with Traffic Control Interface (TraCI) to create the network and conduct the study on the impacts of connected vehicles on traffic operation and fuel consumption in a large portion of the city of El Paso, Texas. The main objective of this study was to investigate the effects of providing the real-time information to the connected vehicles from two perspectives: traffic operation and fuel consumption. Different rerouting algorithms including rerouting based on 1. The real travel time information, 2. Energy (fuel) consumption, 3. Average travel time and 4. The modified travel time with its variance were used to determine the effectiveness of different methodologies for rerouting and to investigate the network performance under these scenarios. Moreover, sensitivity analysis was carried out to assess the effects of important factors in the connected environment such as market penetration rate, driver’s acceptance rate, congestion levels, the update interval for rerouting etc. The impacts of incidents were also considered as an important factor affecting traffic operation and fuel consumption at different market penetration rates (MPR) of connectivity. Several scenarios were implemented and
tested on the simulation model to determine the impacts of incidents on the network performance in the urban area. The scenarios were defined by changing the duration of the incidents and the number of lanes closed. Finally, fuel-flow, flow-density and flow-speed diagrams were developed to characterize the macroscopic impacts of connected vehicles technology on the network performance.
The results of the study demonstrated the effectiveness of rerouting in improving traffic operations and reducing fuel consumption in a connected environment. The comparison between the four methods of rerouting demonstrated that the approaches involving the average travel time of individuals (real-time travel time and average travel time) resulted in higher efficiency of the network. The highest performance in terms of total travel time reduction and total decrease in fuel consumption over the network was observed a 20 percent of rerouting rate. The other two approaches (including the fuel consumption and the modified travel time which involve the variance of travelers’ speed) resulted in smaller improvements to travel. For these two approaches higher rerouting rates (40% and 60% correspondingly) resulted in higher performance in these two models. Various scenarios including different duration and number of lanes closed were then simulated. The impacts of update interval on the performance of the network were also investigated. Several cases of incidents including different duration and one and two-lane closures on the freeway were examined. For the incidents, three durations of 900, 1500 and 2400 seconds and for the update interval three values of 150, 300, and 600 seconds were simulated and analyzed. As expected, an increase in the duration of incidents and number of lanes closed worsens the operation of the network. The study also showed that the update interval of 150 seconds resulted in higher performance of the network. The ability of connected vehicles to receive real-time traffic data helps the network perform more efficiently. The real-time traffic data provided by connected vehicle technology informs drivers of the routes with lower congestion and distributes travelers in the main and alternative paths which increase the throughput and efficiency of the network. This was demonstrated in the study using the macroscopic variables including flow, density and average speed. Overall, the ability of the connected vehicles in receiving the real-time traffic data improves the overall performance of the transportation network. | en |
