Active Transit Signal Priority Research Articles

Coordination Optimization of Real-Time Signal Priority of Self-Driving Buses at Arterial Intersections Considering Private Vehicles

Transit Signal Priority (TSP) is a system designed to grant right-of-way to buses, yet it can lead to delays for private vehicles. With the rapid advancement of network technology, self-driving buses have the capability to efficiently acquire road information and optimize the coordination between vehicle arrival and signal timing. However, the complexity of arterial intersections poses challenges for conventional algorithms and models in adapting to real-time signal priority. In this paper, a novel real-time signal-priority optimization method is proposed for self-driving buses based on the CACC model and the powerful deep Q-network (DQN) algorithm. The proposed method leverages the DQN algorithm to facilitate rapid data collection, analysis, and feedback in self-driving scenarios. Based on the arrival states of both the bus and private vehicles, appropriate actions are chosen to adjust the current-phase green time or switch to the next phase while calculating the duration of the green light. In order to optimize traffic balance, the reward function incorporates an equalization reward term. Through simulation analysis using the SUMO framework with self-driving buses in Zhengzhou, the results demonstrate that the DQN-controlled self-driving TSP optimization method reduces intersection delay by 27.77% and 30.55% compared to scenarios without TSP and with traditional active transit signal priority (ATSP), respectively. Furthermore, the queue length is reduced by 33.41% and 38.21% compared to scenarios without TSP and with traditional ATSP, respectively. These findings highlight the superior control effectiveness of the proposed method, particularly during peak hours and in high-traffic volume scenarios.

An Improved Transit Signal Priority Strategy for Real-World Signal Controllers that Considers the Number of Bus Arrivals

Active transit signal priority (TSP) is used more conveniently and widely than the other strategies for real-world signal controllers. However, the active TSP strategies of real-world signal controllers use the first-come-first-served rule to respond to any active TSP request and are not effective at responding to the number of bus arrivals. With or without the green extension strategy, the active TSP has little impact on the final green time of priority phase, even in the case where more buses arrive during the priority phase. The reduced green time of early green strategy is relatively large when a bus arrives, and it would be worse when more buses arrive, the active TSP has a big adverse impact on the final green time of the non-priority phase. Therefore, the active TSP strategies of real-world signal controllers cannot handle the downtown intersection where many bus lines converge or where many buses arrive in a signal cycle during the evening rush hour. Traffic engineers need to do much work to optimize the TSP parameters before field application. Consequently, it is necessary to improve the TSP strategy of the real-world signal controllers for the intersections with a lot of bus arrivals. In order to achieve that objective, the authors present the CNOB (cumulative number of buses) TSP strategy based on the Siemens 2070 signal controller. The TSP strategy extends the max call time according to the number of buses in the arrival section when priority phases are active. The TSP strategy truncates the green time according to the number of buses in the storage section when non-priority phases are active. The experiment’s result shows that the CNOB TSP strategy can not only significantly reduce the average delay per person without using TSP optimization but can also reduce the adverse impact on the general vehicles of non-bus-priority approaches for the intersections with a lot of bus arrivals. Additionally, because the system dynamically adjusts, traffic engineers do not need to do much optimization work before the TSP implementation.

Timetable Optimization for a Two-Way Tram Line With an Active Signal Priority Strategy

Modern trams typically run along semi-exclusive right-of-way. Although tram lanes isolate trams from other traffic in the running sections, the operation process will be affected by signal control. To improve the service quality of trams and reduce the negative impact on intersections caused by bidirectional priority requests, we propose a timetable optimization method for a single two-way tram line based on active transit signal priority strategy. Combining with the characteristics of bidirectional signal priority strategy, trams can pass through the intersections without stopping by adjusting the running times and dwell times. A multiobjective optimization model of a tram timetable is established to minimize the total travel time, dwell time increment, and negative effect of the signal priority strategy. For obtaining a timetable with equal satisfaction for the three objectives, we adopt the fuzzy mathematical programming approach to transform the problems into mixed integer linear programming (MILP) problems, which can be solved by using standard solvers. The case study of Nanjing Qilin Tram Line 1 shows that the timetable optimization method designed in this paper can effectively improve the service efficiency of trams, and reduce the negative impact of the signal priority strategy on social vehicles. These empirical findings can give us some useful insights on the optimum design of tram timetable.

Simulation analysis of traffic signal control and transit signal priority strategies under Arterial Coordination Conditions

This paper presents the findings of a simulation study evaluating the potential benefits of implementing transit signal priority (TSP) combined with arterial signal coordination for an isolated intersection. Traffic signal coordination is usually implemented along corridors with bus lanes. Active transit signal priority (active TSP) is a traffic-responsive control that prioritizes transit vehicles at signalized intersections. Thus, implementing active TSP under a stable cycle length is necessary to meet the relative demand of the non-priority phase and to maintain system stability. A real key intersection on an artery is taken as the object, and TSP controlling logics with specific restrictions are realized by using the VISSIM vehicle actuated programming module. Simulation analysis reveals the effect of TSP strategies with flow variation on the optimal cycle, and also identifies a reasonable method for selecting the gap time and initial green time of the priority phase. Results show that under special flow combination, increasing the cycle time generated by the traditional transportation and road research laboratory approach can give rise to additional benefits. The volume influences both the gap time and initial green time of the TSP phase. Moreover, the efficiency of red truncation is slightly better than that of the green extension strategy.

Determination Method of Optimal Detector Location for Active Transit Signal Priority

Determination Method of Optimal Detector Location for Active Transit Signal Priority

Passive transit signal priority for high transit demand: model formulation and strategy selection

With the increasing of transit vehicles in urban networks, traditional active transit signal priority (TSP) control may fall short of efficiency and bring negative impacts to non-priority approaches due to overusing priority grants. To reduce the frequency of activating TSP under high bus volumes, this study presents a new model, named INTEBAND, to facilitate the platooning of both passenger-cars and buses along arterials. The model integrates the conventional signal progression model with bus progression model to balance the travel delay of car-users and bus-passengers. Taking Jingshi road in Jinan for example, this study employs VISSIM for model evaluations. Further sensitivity analysis reveals that INTEBAND could clearly outperform the two conventional models in reducing network person delay when the ratio of bus-passengers and car-users exceeds a threshold of 1.5. Moreover, a multi-classifier model based on simulation results is to conveniently answer when INTEBAND can yield more benefit than conventional progression models.

충격파 이론을 이용한 대중교통 우선신호의 신호시간 산정모형

본 연구에서는 충격파 모형을 이용하여 능동식 우선신호의 최적 신호시간을 산정하기 위한 모형을 제시하였다. 본 신호 최적화 모형을 이용하여 능동형 우선신호 기법 중 Early green 및 Green extension이 적용되는 조건에서 충격파 면적을 산정할 수 있다. 본 연구에서는 평균통행시간 및 교차로 진출시각을 이용해 충격파의 발생 속도를 산정하기 위한 방법을 제시하였으며, 이를 이용해 우선신호로 인한 현시 변화량에 따라 충격파 면적 변화량을 산정할 수 있다. 또한 교차로 전체의 충격파 면적이 최소화되는 신호시간을 산정하여 우선신호로 인해 증가하는 일반차량의 지체를 최소화할 수 있도록 하였다. 우선신호 신호시간 산정 모형의 효과평가를 위해 VISSIM과 ComInterface를 이용한 미시적 시뮬레이션 분석을 시행하였으며, 이동류의 포화상태를 고려하여 지체 최소화를 위한 신호시간이 산정됨을 확인하였다. 독립교차로를 대상으로 하는 사례분석에서 우선신호를 위해 비우선현시를 균일하게 단축하는 전략 대비 본 모형에서 일반차량 지체가 10% 이상 개선됨을 확인하였다. 본 연구는 트램, BRT, 중앙버스 전용차로 등 대중교통 우선시설이 확산되고 있는 최근 국내 상황에서 신호교차로의 운영효율을 높이기 위한 새로운 우선신호 제어 방법을 제시하였다는데 의의가 있겠다. This research suggested the traffic signal calculation model of active transit signal priority using a shockwave model. Using this signal priority timing optimization model, the shockwave area is computed under the condition of Early Green and Green Extension among active transit signal priority techniques. This study suggested the speed estimation method of backward shockwave using average travel time and intersection passing time. A shockwave area change is calculated according to signal timing change of transit signal priority. Moreover, this signal timing calculation model could determine the optimal signal priority timings to minimize intersection delay of general vehicles. A micro simulation analysis using VISSIM and its user application model ComInterface was applied. This study checked that this model could calculate the signal timings to minimize intersection delay considering saturation condition of traffic flow. In case studies using an isolated intersection, this study checked that this model could improve general vehicle delay of more over ten percentage as compared with equality reduction strategy of non-priority phases. Recently, transit priority facilities are spreading such as tram, BRT and median bus lane in Korea. This research has an important significance in that the proposed priority model is a new methodology that improve operation efficiency of signal intersection.

Feasibility of Unconditional Transit Signal Priority Considering Delay Savings at Signalized Intersections: A Case Study of Dalian BRT Line No.1

Active transit signal priority (TSP) is a useful tool to remove or minimize control delay for buses at signalized intersections and consequently improve the performance of bus service. Conditional TSP has been proofed to be an effective measure with fewer impacts to non-prioritized traffic, and aroused increasingly research interests and implementation in European and North American cities nowadays. However, the implementation of conditional TSP requires a sophisticated mechanism for examining the schedule deviation of priority required buses, as well as scanning traffic operational conditions at network level. By contrast, unconditional TSP is a less costly and easier measure for implementation, because it gives priority to every required bus without considering its schedule deviation. The critical argument on unconditional TSP is its adverse impacts to non-prioritized traffic, particularly during peak hours. To determine the threshold for implementing unconditional TSP, in this paper, theoretical analysis based on signal display graphs of differential TSP granting strategies was undertaken to estimate delay savings and increments for prioritized and non- prioritized approaches respectively. In the next step, Dalian BRT line was taken as an example to verify the feasibility of unconditional TSP based on the proposed theory. Results show that unconditional TSP is feasible during off-peak hours, while for peak hours, feasibility of unconditional TSP mainly depended on the traffic volume of each approach.

Optimal Cycle Model Based on Active Transit Signal Priority Strategies in Artery Coordination Systems

AbstractStudies on active transit signal priority (active TSP) focus primarily on the advantages and parameters of priority strategies within a given cycle time, which is not necessarily the optimal cycle. With consideration for the restrictions resulting from arterial coordination, the effect of three active TSP strategies on vehicle delays at a key intersection on an arterial road was discussed. Using an actual case, the effect of possible real volume variations on optimal cycles under active TSP strategies was analyzed. Results show that under special flow conditions, additional benefits exist when the cycle time is increased from the value generated by the TRRL approach. The extent of increase can rise with the ratio of priority phase flow to nonpriority phase flow. Cycle time can be dynamically established in accordance with the flow conditions in actual operations. The findings also show that the efficacy of red truncation is better than that of green extension.

Comparative Analysis of Unconditional and Conditional Priority for Use at Isolated Signalized Intersections

Conditional priority is recognized as having the potential to improve transit service reliability at small cost to general traffic. The popular preference for conditional priority over unconditional priority encounters the challenges of various and challenging test scenarios. This paper makes a comparative analysis of unconditional and conditional priority in terms of intersection performance, based on the logic rule-based bus rapid transit signal priority (BRTSP), an active transit signal priority (TSP) for use at isolated signalized intersections with median bus-only lanes. Compared to previous study, the design of phase scheme, including two BRT phases, eight vehicle phases and four pedestrian phases, and the technical framework of BRTSP, centered on four categories of logic rules, have been improved to incorporate a mechanism for providing phase insertion, a special signal priority treatment in addition to green extension and early green. Phase insertion detector, if phase insertion is desired, is installed on the bus-only lane between check-in and check-out detector to trigger phase insertion request. A new category of logic rules, i.e., rules for early green response, is introduced into as a component of BRTSP to dynamically alter the response of the vehicle phases conflicting with the BRT phases to early green request. Inductive loop detector placed on each lane of the vehicle phases is used to monitor time headway and occupancy time on a lane by lane basis. The simulation experimental results indicated that: (1) phase insertion contributed substantially to late schedule deviations correction, but was recommended to be embedded in conditional priority rather than unconditional priority; (2) there was lack of convincing evidence that conditional priority had an inherent effectiveness of managing the intersection performance by varying the lateness criterion; (3) at TSP-enabled isolated intersections with green extension and early green, compared to having conditional priority, having an integration of unconditional priority and holding early BRT vehicles at control points may be a cost-effective solution not only to improve schedule adherence but also to accommodate the benefits of general traffic; and (4) at TSP-enabled isolated intersections with green extension, early green and phase insertion, there seemed to be a pressing need to move from unconditional priority to conditional priority.

Active Transit Signal Priority for Streetcars

Although streetcar systems benefit from a strong identity, they face considerable challenges as a result of mixed traffic operations. These problems have been compounded by growing urban auto traffic, which has increased competition for limited road space and time. Active traffic signal priority (TSP) has been identified as a cost-effective way to improve the management of manage traffic systems to make on-street public transport more reliable, faster, and more cost-effective. Although the implementation of TSP is growing throughout the world, relatively few studies have examined its application to streetcar-based systems. This paper reviews the experience with TSP in Melbourne, Australia, and Toronto, Canada. These cities run some of the world's oldest and largest streetcar-based TSP systems. This paper describes the TSP systems adopted in the two cities, including key experiences. TSP performance is reviewed, and identified problems and issues are assessed. The review established that the TSP systems in the two cities have many similarities including the configuration of approach and request loop and stop line and cancel loop detection, the degree of priority provided, and the targeting of clearance phases for turning traffic at intersections. There are some slight differences in the handling of bunching trams and opposing tram movements, which are better handled in the Toronto case. The two systems see rather different futures for TSP development. Toronto is focused on full systemwide TSP implementation and advancement of TSP algorithms, whereas Melbourne aims to make priority more conditional on the degree of lateness of trams and on the degree of traffic congestion experienced.