DTUMOS, digital twin for large-scale urban mobility operating system.

The advancement of digital twin technology has significantly impacted the utilization of virtual cities in the realm of smart cities and mobility. Digital twins provide a platform for the development and testing of various mobility systems, algorithms, and policies. In this research, we introduce DTUMOS, a digital twin framework for urban mobility operating systems. DTUMOS is a versatile, open-source framework that can be flexibly and adaptably integrated into various urban mobility systems. Its novel architecture, combining an AI-based estimated time of arrival model and vehicle routing algorithm, allows DTUMOS to achieve high-speed performance while maintaining accuracy in the implementation of large-scale mobility systems. DTUMOS exhibits distinct advantages in terms of scalability, simulation speed, and visualization compared to current state-of-the-art mobility digital twins and simulations. The performance and scalability of DTUMOS are validated through the use of real data in large metropolitan cities including Seoul, New York City, and Chicago. DTUMOS' lightweight and open-source environment present opportunities for the development of various simulation-based algorithms and the quantitative evaluation of policies for future mobility systems.

Understanding individual-level travel behavior changes due to COVID-19: Trip frequency, trip regularity, and trip distance.

Understanding different mechanisms in trip changes depending on transportation modes due to COVID-19 pandemic is the key to providing practical insights for healthy communities. This study aimed to investigate the impact of the COVID-19 pandemic on individual-level travel behavior in Daejeon Metropolitan City, South Korea. Using smart card and private vehicle records, we explored different travel behaviors exhibited while using buses and private vehicles. An individual's travel behavior was represented in trip frequency, trip regularity, and trip distance and was compared weekly for about three months, including the initial period of pandemic. A significant decrease in trip frequency during non-peak hours on weekdays and during weekends indicates that people reduced non-mandatory trips more than commuter trips. This was also verified in that, as the number of infection cases increased, trip regularity with 24-hour intervals intensified. People maintained the size of their activity boundaries but reduced their daily trip distances. The interesting point is that private vehicle usage increased for shorter trip distances while bus usage dropped regardless of the ranges of trip distances under the pandemic. The findings provide evidence of possible inequality issues in transportation during the pandemic and can help make precautionary policies for future pandemics.

Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price.

This study aimed to explore the impacts of COVID-19 on car and bus usage and their relationships with land use and land price. Large-scale trip data of car and bus usage in Daejeon, South Korea, were tested. We made a trip-chain-level data set to analyze travel behavior based on activity-based travel volumes. Hexagonal cells were used to capture geographical explanatory variables, and a mixed-effect regression model was adopted to determine the impacts of COVID-19. The modeling outcomes demonstrated behavioral differences between associated with using cars and buses amid the pandemic. People responded to the pandemic by reducing their trips more intensively during the daytime and weekends. Moreover, they avoided crowded or shared spaces by reducing bus trips and trips toward commercial areas. In terms of social equity, trips of people living in wealthier areas decreased more than those of people living in lower-priced areas, especially trips by buses. The findings contribute to the previous literature by adding a fundamental reference for the different impacts of pandemics on two universal transportation modes.

Effects of speed humps on vehicle speed and pedestrian crashes in South Korea.

INTRODUCTION: Speeding is a crucial risk factor for pedestrian safety because it shortens reaction time while increasing the impact force in collisions. Various types of traffic calming measures to prevent speeding have been devised. A speed hump-a raised bump installed in the pavement-has been widely used for this purpose. METHOD: To evaluate the effectiveness of speed humps, the speed profiles of vehicles passing speed humps were analyzed along with pedestrian crash records near speed humps. RESULTS: The speed profiles showed that vehicles gradually diminished their speeds starting 30 m ahead of speed humps and, immediately after passing the humps, accelerated to regain their original speeds within a distance of 30 m. This speed reduction effect is substantial on both local and major roads: 18.4% and 24.0% reduction in speeds, respectively. The analysis of pedestrian crash records revealed that, inside the zones of speed reduction effect near speed humps (i.e., ±30 m from speed humps), fewer pedestrian crashes per roadway distance occurred and pedestrian injuries were less severe, compared with events outside the effect zones. This safety improvement was greater on major roads than local roads. Practical Applications: This work finds that the speed reductions that occurred near speed humps were gradual and influential ±30 m from their locations, suggesting that the hump installations should be close enough to the pedestrian crossings. It is noteworthy that, albeit that speed humps are more prevalent on local roads, the benefits of speed reduction effects from speed humps were more pronounced on major roads than on local roads. Therefore, speed humps on major roads can be considered a more effective measure for pedestrian safety.

Enforcement avoidance behavior near automated speed enforcement areas in Korean expressways.

Automated speed enforcement system (ASES) has been deployed as a safety countermeasure on Korean roadways to reduce speeding-related traffic crashes; information on ASES locations is mandated to be open to the public. However, because drivers are alerted about enforcement via on-board navigation systems and roadside signs, they can avoid enforcement by momentarily reducing their speeds near ASES locations. This enforcement avoidance behavior (EAB) can induce sudden changes in speed near the enforcement locations and thereby increase risk of crash occurrence. In light of this situation, the present study evaluates the effects of ASES on traffic behavior and safety. An analysis of traffic data shows that drivers indeed diminish their speeds near enforcement locations, and accelerate shortly after passing the locations. To investigate how this behavior affects safety performance, this study, by using Empirical Bayes analysis with comparison groups, compares crash occurrences along a certain section before and after the installation of ASES. The comparative analysis shows that overall crash occurrence dropped by 7.6% on average near the enforcement locations, although the reduction was not significant. However, an average 11% non-significant increase in crash occurrence is also observed in the upstream segment, where enforcement is announced to drivers and traffic starts to diminish speed. The findings suggest that the sudden changes in traffic speed induced by EAB substantially negate the benefits of ASES. Therefore, modification of the design of current ASES is required to mitigate EAB and further improve the effectiveness of ASES.

Effects of urban sprawl and vehicle miles traveled on traffic fatalities.

OBJECTIVE: Previous research suggests that urban sprawl increases auto-dependency and that excessive auto use increases the risk of traffic fatalities. This indirect effect of urban sprawl on traffic fatalities is compared to non-vehicle miles traveled (VMT)-related direct effect of sprawl on fatalities. METHODS: We conducted a path analysis to examine the causal linkages among urban sprawl, VMT, traffic fatalities, income, and fuel cost. The path diagram includes 2 major linkages: the direct relationship between urban sprawl and traffic fatalities and the indirect effect on fatalities through increased VMT in sprawling urban areas. To measure the relative strength of these causal linkages, path coefficients are estimated using data collected nationally from 147 urbanized areas in the United States. RESULTS: Through both direct and indirect paths, urban sprawl is associated with greater numbers of traffic fatalities, but the direct effect of sprawl on fatalities is more influential than the indirect effect. CONCLUSIONS: Enhancing traffic safety can be achieved by impeding urban sprawl and encouraging compact development. On the other hand, policy tools reducing VMT may be less effective than anticipated for traffic safety.

Contributing factors to vehicle to vehicle crash frequency and severity under rainfall.

INTRODUCTION: This study combined vehicle to vehicle crash frequency and severity estimations to examine factor impacts on Wisconsin highway safety in rainy weather. METHOD: Because of data deficiency, the real-time water film depth, the car-following distance, and the vertical curve grade were estimated with available data sources and a GIS analysis to capture rainy weather conditions at the crash location and time. Using a negative binomial regression for crash frequency estimation, the average annual daily traffic per lane, the interaction between the posted speed limit change and the existence of an off-ramp, and the interaction between the travel lane number change and the pavement surface material change were found to increase the likelihood of vehicle to vehicle crashes under rainfall. RESULTS: However, more average daily rainfall per month and a wider left shoulder were identified as factors that decrease the likelihood of vehicle to vehicle crashes. In the crash severity estimation using the multinomial logit model that outperformed the ordered logit model, the travel lane number, the interaction between the travel lane number and the slow grade, the deep water film, and the rear-end collision type were more likely to increase the likelihood of injury crashes under rainfall compared with crashes involving only property damage. PRACTICAL IMPLICATIONS: As an exploratory data analysis, this study provides insight into potential strategies for rainy weather highway safety improvement, specifically, the following weather-sensitive strategies: road design and ITS implementation for drivers' safety awareness under rainfall.

Impact of traffic states on freeway crash involvement rates.

Freeway traffic accidents are complicated events that are influenced by multiple factors including roadway geometry, drivers' behavior, traffic conditions and environmental factors. Among the various factors, crash occurrence on freeways is supposed to be strongly influenced by the traffic states representing driving situations that are changed by road geometry and cause the change of drivers' behavior. This paper proposes a methodology to investigate the relationship between traffic states and crash involvements on the freeway. First, we defined section-based traffic states: free flow (FF), back of queue (BQ), bottleneck front (BN) and congestion (CT) according to their distinctive patterns; and traffic states of each freeway section are determined based on actual measurements of traffic data from upstream and downstream ends of the section. Next, freeway crash data are integrated with the traffic states of a freeway section using upstream and downstream traffic measurements. As an illustrative study to show the applicability, we applied the proposed method on a 32-mile section of I-880 freeway. By integrating freeway crash occurrence and traffic data over a three-year period, we obtained the crash involvement rate for each traffic state. The results show that crash involvement rate in BN, BQ, and CT states are approximately 5 times higher than the one in FF. The proposed method shows promise to be used for various safety performance measurement including hot spot identification and prediction of the number of crash involvements on freeway sections.