•Simultaneously optimize CAV trajectories and intersection controllers.•Consider interactions between CAVs, human-driven vehicles, and intersection control.•Optimize for multiple performance measures ...(delay, fuel consumption, and safety).•Conduct numerical experiments with real-world intersection and signal control design.
Connected and automated vehicle (CAV) technologies offer promising solutions to challenges that face today’s transportation systems. Vehicular trajectory control and intersection controller optimization based on CAV technologies are two approaches that have significant potential to mitigate congestion, lessen the risk of crashes, reduce fuel consumption, and decrease emissions at intersections. These two approaches should be integrated into a single process such that both aspects can be optimized simultaneously to achieve maximum benefits. This paper proposes an efficient DP-SH (dynamic programming with shooting heuristic as a subroutine) algorithm for the integrated optimization problem that can simultaneously optimize the trajectories of CAVs and intersection controllers (i.e., signal timing and phasing of traffic signals), and develops a two-step approach (DP-SH and trajectory optimization) to effectively obtain near-optimal intersection and trajectory control plans. Also, the proposed DP-SH algorithm can also consider mixed traffic stream scenarios with different levels of CAV market penetration. Numerical experiments are conducted, and the results prove the efficiency and sound performance of the proposed optimization framework. The proposed DP-SH algorithm, compared to the adaptive signal control, can reduce the average travel time by up to 35.72% and save the consumption by up to 31.5%. In mixed traffic scenarios, system performance improves with increasing market penetration rates. Even with low levels of penetration, there are significant benefits in fuel consumption savings. The computational efficiency, as evidenced in the case studies, indicates the applicability of DP-SH for real-time implementation.
•New protocol for reservation-based intersection control that admits optimized trajectories.•Mixed integer linear programming formulation using conflict-point vehicle separation.•Rolling horizon ...solution approach that can be solved efficiently for large time periods.•Improves significantly over the widely-used first-come-first-served policy.
Reservation-based intersection controls, in which vehicles reserve space-time paths through the intersection, have the potential to make greater use of intersection capacity than traffic signals. However, the efficiency of previous microsimulations of reservations has been severely limited by a protocol that requires vehicles to request reservations and the intersection manager to accept or reject them. We propose a new protocol, AIM∗, in which the intersection manager assigns reservations to vehicles, to greatly increase the optimization possibilities. Then, we present a mixed integer linear program for optimally choosing vehicle reservations under AIM∗. The formulation is similar to conflict resolution models for aviation, and ensures separation at all points that vehicles might intersect. We therefore present a rolling-horizon algorithm to extend the method to larger numbers of vehicles. Results show that the optimal reservation assignments from AIM∗ significantly reduce delays over previous protocols. Furthermore, the rolling horizon solutions have similar delays to a fixed horizon, thereby providing an efficient method of implementing AIM∗.
Twenty years ago, the concept of aggregation‐induced emission (AIE) was proposed, and this unique luminescent property has attracted scientific interest ever since. However, AIE denominates only the ...phenomenon, while the details of its underlying guiding principles remain to be elucidated. This minireview discusses the basic principles of AIE based on our previous mechanistic study of the photophysical behavior of 9,10‐bis(N,N‐dialkylamino)anthracene (BDAA) and the corresponding mechanistic analysis by quantum chemical calculations. BDAA comprises an anthracene core and small electron donors, which allows the quantum chemical aspects of AIE to be discussed. The key factor for AIE is the control over the non‐radiative decay (deactivation) pathway, which can be visualized by considering the conical intersection (CI) on a potential energy surface. Controlling the conical intersection (CI) on the potential energy surface enables the separate formation of fluorescent (CI:high) and non‐fluorescent (CI:low) molecules control of conical intersection accessibility (CCIA). The novelty and originality of AIE in the field of photochemistry lies in the creation of functionality by design and in the active control over deactivation pathways. Moreover, we provide a new design strategy for AIE luminogens (AIEgens) and discuss selected examples.
What is essential in the aggregation‐induced emission (AIE) mechanism? This question is addressed by using the photophysical processes associated with 9,10‐bis(N,N‐dialkylamino)anthracene as a case study. The AIE phenomenon requires control of the non‐radiative decay (deactivation) pathway, that is, controlling the conical intersection (CI) on the potential energy surface enables the formation of fluorescent molecules (CI high) and non‐fluorescent (CI low) molecules separately.
We derive an explicit generating function of correlation functions of an arbitrary tau-function of the KdV hierarchy. In particular applications, our formulation gives closed formulæ of a new type ...for the generating series of intersection numbers of ψ-classes as well as of mixed ψ- and κ-classes in full genera.
•Introduce a phase-time-traffic hypernetwork model to model intersection automation.•Develop scheduling-oriented formulations to define the intersection automation problem.•Develop a sequential ...branch-and-bound algorithm to search the optimal solution.•Enhance solution search with efficient dominance rule and phase-time prism.
It is a common vision that connected and automated vehicles (CAVs) will increasingly appear on the road in the near future and share roads with traditional vehicles. Through sharing real-time locations and receiving guidance from infrastructure, a CAV's arrival and request for green light at intersections can be approximately predicted along their routes. When many CAVs from multiple approaches at intersections place such requests, a central challenge is how to develop an intersection automation policy (IAP) to capture complex traffic dynamics and schedule resources (green lights) to serve both CAV requests (interpreted as request for green lights on a particular signal phase at time t) and traditional vehicles. To represent heterogeneous vehicle movements and dynamic signal timing plans, we first formulate the IAP optimization as a special case of machine scheduling problem using a mixed integer linear programming formulation. Then we develop a novel phase-time-traffic (PTR) hypernetwork model to represent heterogeneous traffic propagation under traffic signal operations. Since the IAP optimization, by nature, is a special sequential decision process, we also develop sequential branch-and-bound search algorithms over time to IAP optimization considering both CAVs and traditional vehicles in the PTR hypernetwork. As the critical part of the branch-and-bound search, special dominance and bounding rules are also developed to reduce the search space and find the exact optimum efficiently. Multiple numerical experiments are conducted to examine the performance of the proposed IAP optimization approach.
•A simplified continuous flow intersection called CFI-Lite is proposed.•CFI-Lite does not need sub-intersections, thus is ideal for arterials with short links.•CFI-Lite performs superiorly to the ...conventional and CFI designs.•Pareto capacity improvement can be achieved in CFI-Lite under effortless conditions.
Oversaturation has become a severe problem for urban intersections, especially the bottleneck intersections that cause queue spillover and network gridlock. Further improvement of oversaturated arterial traffic using traditional mitigation strategies, which aim to improve intersection capacity by merely adjusting signal control parameters, becomes challenging since exiting strategies may (or already) have reached their “theoretical” limits of optimum. Under such circumstance, several novel unconventional intersection designs, including the well-recognized continuous flow intersection (CFI) design, are originated to improve the capacity at bottleneck intersections. However, the requirement of installing extra sub-intersections in a CFI design would increase vehicular stops and, more critically, is unacceptable in tight urban areas with closed spaced intersections. To address these issues, this research proposes a simplified continuous flow intersection (called CFI-Lite) design that is ideal for arterials with short links. It benefits from the CFI concept to enable simultaneous move of left-turn and through traffic at bottleneck intersections, but does not need installation of sub-intersections. Instead, the upstream intersection is utilized to allocate left-turn traffic to the displaced left-turn lane. It is found that the CFI-Lite design performs superiorly to the conventional design and regular CFI design in terms of bottleneck capacity. Pareto capacity improvement for every traffic stream in an arterial system can be achieved under effortless conditions. Case study using data collected at Foothill Blvd in Los Angeles, CA, shows that the new design is beneficial in more than 90% of the 408 studied cycles. The testing also shows that the average improvements of green bandwidths for the synchronized phases are significant.
Set intersection is a fundamental operation in many applications, such as common neighbor computation in graph-based algorithms, set similarity computation, item recommendation, etc. In the ...literature, many set intersection methods are proposed. We observe that the state-of-the-art algorithm <inline-formula><tex-math>{\sf RCode}</tex-math></inline-formula> bears several limitations, such as high index time complexity, inefficient for large-sized sets, and not friendly to the generic set intersection. In this paper, we introduce the B ucket S ig nature for Set (<inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula>), an efficient generic set intersection algorithm. <inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula> consists of two phases, namely the preprocessing phase and the query phase. In the preprocessing phase, <inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula> partitions the elements of a record into <inline-formula><tex-math notation="LaTeX">O(2^{k})</tex-math></inline-formula> buckets and uses a bitmap to indicate the status of the buckets where <inline-formula><tex-math notation="LaTeX">n</tex-math></inline-formula> is the record length and <inline-formula><tex-math notation="LaTeX">k</tex-math></inline-formula> is the number of bits in the signature. In the query phase, <inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula> calculates the results using a candidate generating-and-verification framework. Specifically, a set of candidate elements is identified as those falling in the same buckets. Then, for each bucket, <inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula> collects the common elements using a merge-based method. To improve the performance, we introduce two optimizations, including bucket sharing and size-aware signature construction techniques. We conduct experiments on 10 real graph datasets and 5 real generic set datasets to evaluate the performance of our proposals. The experiment results show that <inline-formula><tex-math>{\sf BigSet}</tex-math></inline-formula> is 20× faster than the leading generic set intersection algorithms. Besides it outperforms the <inline-formula><tex-math>{\sf RCode}</tex-math></inline-formula> with 5× speedup, and while uses up to 8× less memory.
The study of the mapping class group Mod(S) is a classical topic that is experiencing a renaissance. It lies at the juncture of geometry, topology, and group theory. This book explains as many ...important theorems, examples, and techniques as possible, quickly and directly, while at the same time giving full details and keeping the text nearly self-contained. The book is suitable for graduate students.
Geographically weighted regression (GWR) models have been employed in previous studies regarding vehicular travel demands, but few studies have locally modeled walking travel demands at intersections ...to address the issue of spatially varying relationships. Harnessing a comprehensive collection of walking and bicycling traffic counts over 10years in Chittenden County, Vermont, US, along with socioeconomic characteristics, transit accessibility indices, land use attributes and characteristics of intersections and roadway networks, this study utilizes GWR models to identify whether there are spatially varying relationships between active mode travel demands and ambient built-environment attributes. One Ordinary Least Square (OLS) model and two GWR models were parametrically calibrated: a full GWR model of all local variables and a mixed GWR model of both global and local variables. K-fold cross-validation method is used to select variables that significantly influence the volume of active travel modes in the OLS model. The uniform set of variables is investigated in two GWR models. Only residuals of the mixed GWR model exhibit spatial independence. The prediction accuracy of the three models is respectively compared by means of the k-fold cross-validation method. Results show that the mixed GWR model has higher prediction accuracy, while the other two models have roughly the same level of performance. We find that not all independent variables possess a spatially varying relationship with active mode volumes. The flexibility of the mixed GWR model that allows some independent variables to be global strengthens its prediction power. With these findings, transportation planners can dynamically estimate bicycle and pedestrian volumes at widespread intersections, and this geographical realism would facilitate local transportation planning, facility design, safety enhancement and operation analysis, as well as instilling new insights into interdisciplinary spatial research domain.
Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy ...consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable changes. This paper summarizes the developments and the research trends in coordination with the CAVs that have been reported in the literature to date. Remaining challenges and potential future research directions are also discussed.