Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC)
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Browsing Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC) by Author "Dadvar, Seyedehsan"
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- Applications of Connected Vehicle Infrastructure Technologies to Enhance Transit Service Efficiency and Safety, Part 2Lee, Young-Jae; Thomas, Clayton; Dadvar, Seyedehsan (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-09-30)Many transit agencies provide real-time operational information and trip-planning tools through phone, Web, and smartphone applications. These services utilize a one-way information flow from transit agencies to transit users. Current smartphone technology and connected vehicle infrastructure (CVI), however, can allow a two-directional information flow from users to transit agencies and back. This report provides a literature review on the state of current transit apps; proposes a system architecture for a smartphone app that allows for dynamic flexible routing and increased transit user safety; and presents the results of a survey conducted on the perception and acceptability of the model app. Survey results were analyzed in terms of safety, efficiency, and privacy for different demographic, travel behavior, and geographic characteristics. Results showed that users did not significantly consider the privacy issues (7.1 on a scale from 1 [least acceptable] to 10 [most acceptable]) but believed that it could improve nighttime safety (7.3/10.0). Users believed that the app could improve nighttime pedestrian safety if it were connected to the police department (7.8/10.0). This app was also expected to improve transit efficiency and increase ridership, and is eventually recommendable (7.3/10.0). The least expected improvement was daytime safety (6.4/10.0), which is reasonable and expectable.
- Measuring User Acceptance of and Willingness-to-Pay for CVI TechnologyShin, Hyeong-Shic; Callow, Michael; Farkas, Z. Andrew; Lee, Young-Jae; Dadvar, Seyedehsan (Connected Vehicle/Infrastructure University Transportation Center, 2016-09-30)The increased prevalence of Connected Vehicles (CVs) is expected to provide significant safety benefits to roadway users. Estimates indicate that the use of CVs will reduce non-impaired driver crashes by 80 percent. To ensure that the full benefits of CVs are realized, it is critical for transportation professionals to develop effective deployment strategies. However, the large number of unknowns currently makes this difficult. For instance, there are (1) no clear-cut deployment strategies due to a methodological void; (2) overly optimistic adoption estimates; and (3) no unified roadmaps to which state and local governments must conform. Current studies suggest that understanding drivers’ perceptions, needs, and acceptance of CVs will provide rich information for solving these unknowns. As price is a serious barrier to CV technology proliferation, the primary goal of the current study is to use an adaptive choice-based conjoint analysis to estimate drivers’ acceptance of and willingness to pay (WTP) for CVs through a simulation of participants’ purchasing decisions. Results show that, with regard to the acceptance of safety features, acceptance of “collision warning packages” was the highest. Comparisons of WTP considering several socioeconomic variables found that drivers between the ages of 40 and 49 years, African-Americans, those with less than a bachelor’s degree, and those with a higher budget for vehicle purchase were positively related to WTP. Results also indicate that, at every age, women are more concerned about safety than are men. While the study did not find statistical differences in WTP between men and women, women’s budgets for vehicle purchases were lower than men’s, and women reported significantly less prior knowledge of CVs. Also, women 50 and older appear less interested in CV technologies. As a result of these findings, the research team suggests that government agencies showcase CV technologies’ safety benefits via media catering to mature women and at family-oriented public events.
- Next Generation Transit Signal Priority with Connected Vehicle TechnologyHu, Jia; Lee, Young-Jae; Park, Byungkyu Brian; Dadvar, Seyedehsan (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-01-30)This project utilized connected vehicle (CV) technology allowing two-way communication among vehicles and infrastructure to develop a next-generation Transit Signal Priority (TSP) system that does not have to rely on conventional TSP sensors. The research team extended a previously proposed TSP system based on CV technology (TSPCV) to handle conflicting requests and to coordinate passage between intersections in a travel corridor. The proposed TSP mechanisms minimize installation and maintenance costs by eliminating the need for local agencies to perform a level of service (LOS) study and/or volume/capacity (v/c) ratio for potential TSP intersections before installation. Simulation-based evaluation results showed that, compared to conventional TSP mechanisms, the proposed TSP logic reduces bus delays between 5% and 48% (TSPCVM) and decreases the delay of a bus progressing along a corridor between 35% and 68% (TSPCV-C). The range of improvement corresponds to the four different v/c ratios tested, which were 0.5, 0.7, 0.9 and 1.0. In most cases, the proposed TSP logic caused no negative effects. A field experiment conducted on the Connected Vehicle test bed on the Virginia Smart Road, located at the Virginia Tech Transportation Institute (VTTI) in Blacksburg, Virginia, validated the performance of the proposed TSPCV system. The TSPCV algorithm provided green traffic signal timing to buses with different arrival times with a 100% success rate. It also reduced delays for a bus with a speed of 45 mph and a traffic signal with a 90-second cycle length and 30 seconds of green time by as much as between 32% and 75%. Moreover, the field experiment showed that two Global Positioning System (GPS) devices (regular and differential) performed almost identically and, in an aggregate sense, the difference in their performance was not statistically significant. This finding facilitates the large-scale implementation of TSP, since regular GPS devices are much cheaper than differential GPS devices and operated just as well for TSPCV.