A Platooning Strategy for Automated Vehicles in the Presence of Speed Limit Fluctuations

2018 ◽  
Vol 2672 (20) ◽  
pp. 154-161 ◽  
Author(s):  
Sina Arefizadeh ◽  
Alireza Talebpour
Keyword(s):  
Velocity Profile ◽  
Travel Time ◽  
Transportation Network ◽  
Congestion Management ◽  
Transportation Systems ◽  
Driver Model ◽  
Speed Limit ◽  
Travel Time Reliability ◽  
Automated Vehicles ◽  
Car Following Model

Platooning is expected to enhance the efficiency of operating automated vehicles. The positive impacts of platooning on travel time reliability, congestion, emissions, and energy consumption have been shown for homogenous roadway segments. However, the transportation system consists of inhomogeneous segments, and understanding the full impacts of platooning requires investigation in a realistic setup. One of the main reasons for inhomogeneity is speed limit fluctuations. Speed limit changes frequently throughout the transportation network, due to safety-related considerations (e.g., changes in geometry and workzone operations) or congestion management schemes (e.g., speed harmonization systems). In the current transportation systems with human-driven vehicles, these speed drops can potentially result in shockwave formation, which can cause travel time unreliability. Automated vehicles, however, have the potential to prevent shockwave formation and propagation and, therefore, enhance travel time reliability. Accordingly, this study presents a constant time headway strategy for automated vehicle platooning to ensure accurate tracking of any velocity profile in the presence of speed limit fluctuations. The performance of the presented platooning strategy is compared with Gipps’ car-following model and intelligent driver model, as representatives of regular non-automated vehicles. Simulation results show that implementing a fully autonomous system prevents shockwave formation and propagation, and enhances travel time reliability by accurately tracking the desired velocity profile. Moreover, the performance of platoons of regular and automated vehicles is investigated in the presence of a speed drop. The results show that as the market penetration rate of automated vehicles increases, the platoon can track the velocity profile more accurately.

Origin–Destination-Based Travel Time Reliability

2017 ◽  
Vol 2643 (1) ◽  
pp. 139-159 ◽  
Author(s):  
Shu Yang ◽  
Chengchuan An ◽  
Yao-Jan Wu ◽  
Jingxin Xia
Keyword(s):  
Travel Time ◽  
Performance Indicator ◽  
Transportation Systems ◽  
Travel Time Reliability ◽  
Primary Difference ◽  
Route Information ◽  
Time Periods ◽  
Approximate Confidence Intervals ◽  
Deviation Coefficient ◽  
Insight Into

Travel time reliability (TTR) is an important performance indicator for transportation systems. TTR can be generally categorized as either segment based or origin–destination (O-D) based. A primary difference between the two TTR estimations is that route information is implied in segment-based TTR estimations. Segment-based TTR estimations have been widely studied in previous research; however, O-D–based TTR estimations are used infrequently. This paper provides detailed insight into O-D–based TTR estimations and raises three new issues: ( a) How many routes do travelers usually take and what are the TTR values associated with these routes? ( b) Do statistical differences exist between route-specific and non-route-specific (NRS) TTR values? ( c) How can O-D–based TTR information be delivered? Two processes were proposed to address the issues. Three TTR measures—standard deviation, coefficient of variation, and buffer index—were calculated. The bootstrapping technique was used to measure the accuracy of the TTR measures. Approximate confidence intervals were used to investigate statistically the differences between route-specific and NRS TTR measures. A large quantity of taxicab GPS-based data provided data support for estimating O-D–based TTR measures. The results of O-D–based TTR measures showed that no statistically significant differences existed between route-specific and NRS TTR measures for most of the time periods examined. Statistically significant differences could still be found in some time periods. Travelers may take advantage of these differences to choose a more reliable route. Access to both numeric TTR values and route preference, instead of just to TTR information on segments of interest, can be beneficial to travelers in planning an entire trip.

Illustrating the Monetary Impact of Transportation Projects/Alternatives using the Values of Travel Time and Travel Time Reliability

2018 ◽  
Vol 2672 (51) ◽  
pp. 88-98 ◽  
Author(s):  
Venkata R. Duddu ◽  
Srinivas S. Pulugurtha ◽  
Praveena Penmetsa
Keyword(s):  
Travel Time ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Transportation Systems ◽  
Travel Time Reliability ◽  
Benefit Analysis ◽  
Transportation Projects ◽  
Travel Time Savings ◽  
Time Savings ◽  
The Impact

State agencies, regional agencies, cities, towns, and local municipalities design and maintain transportation systems for the benefit of users by improving mobility, reducing travel time, and enhancing safety. Cost–benefit analysis based on travel time savings and the value of reliability helps these agencies in prioritizing transportation projects or when evaluating transportation alternatives. This paper illustrates the use of monetary values of travel time savings and travel time reliability, computed for the state of North Carolina, to help assess the impact of transportation projects or alternatives. The results obtained indicate that, based on the illustration of the effect and impact of various transportation projects or alternatives, both improved travel time and reliability on roads yield significant monetary benefits. However, from cost–benefit analysis, it is observed that greater benefits can be achieved through improved reliability compared with benefits from a decrease in travel time for a given section of road.

scholarly journals A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Haigen Min ◽  
Yukun Fang ◽  
Runmin Wang ◽  
Xiaochi Li ◽  
Zhigang Xu ◽  
...  
Keyword(s):  
Game Theory ◽  
Travel Time ◽  
Fuel Consumption ◽  
Transportation Network ◽  
Control Algorithms ◽  
Traffic Density ◽  
Automated Vehicles ◽  
Network Efficiency ◽  
Total Travel Time ◽  
The Cost

Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. In this paper, we focused on the scenario of on-ramp merging of CAVs, proposed a centralized approach based on game theory to control the process of on-ramp merging for all agents without any collisions, and optimized the overall fuel consumption and total travel time. For the framework of the game, benefit, loss, and rules are three basic components, and in our model, benefit is the priority of passing the merging point, represented via the merging sequence (MS), loss is the cost of fuel consumption and the total travel time, and the game rules are designed in accordance with traffic density, fairness, and wholeness. Each rule has a different degree of importance, and to get the optimal weight of each rule, we formulate the problem as a double-objective optimization problem and obtain the results by searching the feasible Pareto solutions. As to the assignment of merging sequence, we evaluate each competitor from three aspects by giving scores and multiplying the corresponding weight and the agent with the higher score gets comparatively smaller MS, i.e., the priority of passing the intersection. The simulations and comparisons are conducted to demonstrate the effectiveness of the proposed method. Moreover, the proposed method improved the fuel economy and saved the travel time.

Stochastic Simulation of Bus Traveling Time

2011 ◽  
Vol 186 ◽  
pp. 556-559
Author(s):  
Lian Xue ◽  
Dan Jie Zhao ◽  
Gui Mei Liu
Keyword(s):  
Travel Time ◽  
Stochastic Simulation ◽  
Public Transportation ◽  
Simulation Method ◽  
Service Level ◽  
Transportation Systems ◽  
Travel Time Reliability ◽  
Public Transport System ◽  
Public Transportation Systems ◽  
Bus Travel Time

The development of the city's public transport system has an indispensable role to alleviate the pressure of urban roads. Bus travel time reliability is an important evaluation index of the bus operation service level. The simulation of bus travel time helps us understand the reliability of bus running time. In this paper, we use Monte Carlo stochastic simulation method to calculate the reliability of bus travel time. On this basis, we establish a model of the reliability of public transportation systems to research the reliability of bus travel time.

Factors Affecting Minimum Number of Probes Required for Reliable Estimation of Travel Time

2005 ◽  
Vol 1917 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Mecit Cetin ◽  
George F. List ◽  
Yingjie Zhou
Keyword(s):  
Travel Time ◽  
Transportation Network ◽  
Travel Time Reliability ◽  
System State ◽  
Travel Times ◽  
State Estimate ◽  
Factors Affecting ◽  
Minimum Number ◽  
Time Information ◽  
Detection Technologies

Using probe vehicles rather than other detection technologies has great value, especially when travel time information is sought in a transportation network. Even though probes enable direct measurement of travel times across links, the quality or reliability of a system state estimate based on such measurements depends heavily on the number of probe observations across time and space. Clearly, it is important to know what level of travel time reliability can be achieved from a given number of probes. It is equally important to find ways (other than increasing the sample size of probes) of improving the reliability in the travel time estimate. This paper provides two new perspectives on those topics. First, the probe estimation problem is formulated in the context of estimating travel times. Second, a method is introduced to create a virtual network by inserting dummy nodes in the midpoints of links to enhance the ability to estimate travel times further in a way that is more consistent with the processing that vehicles receive. Numerical experiments are presented to illustrate the value of those ideas.

scholarly journals A Space-Based Car-Following Model: Development and Application for Managed Motorway System Safety Evaluation

2021 ◽  
Vol 1 (3) ◽  
pp. 443-465
Author(s):  
Kaveh Bevrani ◽  
Edward Chung ◽  
Pauline Teo
Keyword(s):  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Simulation Models ◽  
Transportation Systems ◽  
Speed Limit ◽  
Variable Speed ◽  
Driver Behaviour ◽  
Car Following ◽  
Micro Simulation ◽  
Car Following Model

Traffic safety studies need more than what the current micro-simulation models can provide, as they presume that all drivers exhibit safe behaviors. Therefore, existing micro-simulation models are inadequate to evaluate the safety impacts of managed motorway systems such as Variable Speed Limits. All microscopic traffic simulation packages include a core car-following model. This paper highlights the limitations of the existing car-following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car-following models, modelling driver behaviour with precise parameters such as headways and time-to-collisions. The comparison evaluates the robustness of each car-following model for safety metric reproductions. A new car-following model, based on the personal space concept and fish school model is proposed to simulate more accurate traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit from variable speed limit (VSL) systems. This model can also emulate different traffic states and can be easily calibrated. These research findings facilitate assessing and predicting intelligent transportation systems effects on motorways, using microscopic simulation.

scholarly journals Flexible Bus Route Optimization for Multitarget Stations

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Sun Ji-yang ◽  
Huang Jian-ling ◽  
Chen Yan-yan ◽  
Wei Pan-yi ◽  
Jia Jian-lin
Keyword(s):  
Travel Time ◽  
Optimization Model ◽  
Transportation Network ◽  
Transportation Systems ◽  
Route Optimization ◽  
Planning Time ◽  
Bus Scheduling ◽  
Proposed Model ◽  
Average Travel Time ◽  
Better Than

This paper proposes a flexible bus route optimization model for efficient public city transportation systems based on multitarget stations. The model considers passenger demands, vehicle capacities, and transportation network and aims to solve the optimal route, minimizing the vehicles’ running time and the passengers’ travel time. A heuristic algorithm based on a gravity model is introduced to solve this NP-hard optimization problem. Simulation studies verify the effectiveness and practicality of the proposed model and algorithm. The results show that the total number of vehicles needed to complete the service is 17–21, the average travel time of each vehicle is 24.59 minutes, the solving time of 100 sets of data is within 25 seconds, and the average calculation time is 12.04 seconds. It can be seen that under the premise of real-time adjustment of connection planning time, the optimization model can satisfy the passenger’s dynamic demand to a greater extent, and effectively reduce the planning path error, shorten the distance and travel time of passengers, and the result is better than that of the flexible bus scheduling model which ignores the change of connection travel time.

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