This paper presents a longitudinal freeway merging control algorithm for maximizing the average travel speed of fully automated connected vehicles. Communication with a roadside unit allows the computation and transmission of optimized trajectories to the equipped vehicles. These vehicles then carry out the trajectories and resume normal operation once they cease communication with the roadside controller. A tool was developed to simulate and carry out the merging algorithm, while interfacing with the optimization software LINGO. A hypothetical merging segment was simulated to evaluate the effectiveness of the merging algorithm, and its performance is compared to conventional vehicle operation. During uncongested conditions the algorithm is able to reduce travel time, increase average travel speed and improve throughput. The capacity of the merge segment is directly related to the safe time gap selected to run the algorithm. Once capacity is reached, queuing forms on both the ramp and mainline segments upstream of the merge area. The algorithm provides safe merging operations during this congested traffic state.

Efficient control of fully automated connected vehicles at freeway merge segments

Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority’s point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the importance of the number and locations of shelter sites and the trade-off between efficiency and fairness.

/pdf/compromising-system-and-user-interests-in-shelter-location-3sr3hng1oi.pdf

Compromising system and user interests in shelter location and evacuation planning

Autonomous vehicles (AVs) may significantly change traveler behavior and network congestion. Empty repositioning trips allow travelers to avoid parking fees or share the vehicle with other household members. Computer precision and reaction times may also increase road and intersection capacities. AVs are currently being test driven on public roads and may be publicly available within the next two decades; they therefore may be within the span of 20- to 30-year planning analyses. Despite this time scale, AV behavior has yet to be incorporated into planning models. This paper presents a multiclass, four-step model that includes AV repositioning to avoid parking fees (although incurring additional fuel costs) and increases in link capacity as a function of the proportion of AVs on the link. Demand is divided into classes by value of time and AV ownership. Mode choice—parking, repositioning, or transit—is determined through a nested logit model. Traffic assignment is based on a generalized cost function of ti...

Effects of Autonomous Vehicle Ownership on Trip, Mode, and Route Choice

https://hal.laas.fr/hal-02383753/document

Optimization models for large scale network evacuation planning and management: A literature review

A hybrid multi-objective decision model for emergency shelter location-relocation projects using fuzzy analytic hierarchy process and goal programming approach

This article presents a robust approach for determining optimal locations of public shelters and their capacities, from a given set of potential sites during evacuation planning under demand uncertainty. Demand uncertainty in the article refers to the uncertainty associated with the number of people using the public shelters during evacuation. It is assumed that a planning authority determines the number of shelters, their locations, and capacities whereas evacuees choose a shelter to evacuate and the routes to access it. The proposed model is formulated as a mathematical program with complementarity constraints and is solved by a cutting-plane scheme. A numerical example on the Sioux Falls network demonstrates that robust plans are able to achieve nearly the same level of performance with a significant lower cost as compared to a conservative plan, which assumes the highest demand of each origin node.

Robust Shelter Locations for Evacuation Planning with Demand Uncertainty

SUMMARY

This paper develops a decision-support model for transit-based evacuation planning under demand uncertainty. Demand uncertainty refers to the uncertainty associated with the number of transit-dependent evacuees. A robust optimization model is proposed to determine the optimal pick-up points for evacuees to assemble, and allocate available buses to transport the assembled evacuees between the pick-up locations and different public shelters. The model is formulated as a mixed-integer linear program and is solved via a cutting plane scheme. The numerical example based on the Sioux Falls network demonstrates that the robust plan yields lower total evacuation time and is reliable in serving the realized evacuee demand. Copyright © 2012 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/atr.1221

Pick‐up locations and bus allocation for transit‐based evacuation planning with demand uncertainty

Autonomous vehicles (AVs) could change travel patterns of the population significantly and with the rapid improvements in AV technology, transportation planners should address AV impacts in regional plans and project evaluations for the mid-term and long-term horizons (10–15 years and beyond). There are multiple travel model components from demand generation to network assignments that need to be modified, updated, or added to fully capture the potential impacts of AVs on regional travel patterns. This paper describes how the features of AVs were incorporated in the regional Activity-Based travel demand Model developed for Columbus, OH, metropolitan region. The model modifications included multiple adjustments to the travel demand sub-models, network assignments, as well as an addition of a new sub-model for vehicle routing and parking that addresses such new phenomenon as empty AV relocation trips. Due to many factors of uncertainty associated with AVs, a scenario-based approach was adopted for evaluation of the potential impacts of AVs on the travel patterns. The emphasis of the scenario analysis was on multiple dimensions of travel behavior in addition to such aggregate regional measures as VMT, etc. The paper presents an analysis of potential impacts of AVs on accessibility measures, activity participation, tour formation, and mode choice. The scenario analysis applied to the Columbus region showed overall logical potential impacts of AVs with many insights useful for transportation planning.

Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH

While the Highway Capacity Manual (HCM) 2000 does provide a separate procedure to estimate the back of queue for a lane group, its signalized intersection analysis procedure does not explicitly account for the impact to through movement traffic as a result of left-turn bay spillover If the HCM methodology is used for an analysis of an intersection approach where left-turn spillover interferes with the discharge of through vehicles, the estimated delay results, and corresponding level of service, will be overly optimistic Thus, the objective of this study was to determine the factors that significantly affect left-turn lane spillover and develop a model, or models, to predict the expected through movement capacity and discharge rate as a function of this spillover Two approaches were used in this study: an analytical approach that developed a probability of leftturn spillover equation to incorporate into a capacity estimation equation, and an empirical approach incorporating the use of microsimulation t

Impact of Left-Turn Spillover on through Movement Discharge at Signalized Intersections:

Auxiliary lanes are generally used to reduce the traffic turbulence created by merging and diverging movements and are primarily used by vehicles either entering or exiting the freeway. The Highway Capacity Manual (HCM) does not offer explicit guidance on the benefit of adding an auxiliary lane between an on- and off-ramp. The objective of this part of the project was to quantify the additional traffic volume that can be accommodated on a freeway segment by connecting an on-ramp to an off-ramp with an auxiliary lane. The approach used was to identify the traffic volume level at which each level of service density threshold was met for the conditions of with and without an auxiliary lane. The CORSIM simulation program was used to generate the data upon which to establish the quantitative effect of an auxiliary lane. Two versions of an adjustment equation that gives the percentage increase in volume throughput due to adding an auxiliary lane were developed. The developed equations are simply a function of the number of mainline lanes, as other factors were not found to significantly affect the percentage increase in volume throughput. The capacity of a freeway segment is a critical factor for the assessment of the traffic flow operations on freeway facilities. The HCM (2000) is considered to be one of the authoritative sources on capacity values for a variety of roadway types in the U.S. It provides a single set of capacity values for basic freeway segments as a function of free-flow speed. These values are considered to be reasonably representative values for freeways located throughout the U.S., but it is recognized that lower or higher values may be more appropriate in any given location. However, the HCM does not provide any guidance on how its recommended values can be adjusted to reflect significant differences in capacity due to local conditions, nor how to directly measure or estimate capacity values. The objective of this part of the project was to investigate various methods that can be used to arrive at an estimate of freeway capacity values, and to recommend one of these methods to the Florida Department of Transportation for use in developing its own estimates of capacity for Florida freeways. Three methods were investigated: one that fits a mathematical function to speed-flow data points, from which the apex of the function is taken as capacity; one that estimates a breakdown probability distribution based on flow rates preceding breakdown events, from which capacity can be taken to correspond to a certain percentile value of the breakdown probability distribution; and one that uses a flow rate corresponding to a specified percentile within a specified range of maximum flow rates observed at a site. It is recommended that this latter method is most suitable for planning and preliminary engineering applications.

Investigation of freeway capacity : (a) effect of auxiliary lanes on freeway segment volume throughput and b) freeway segment capacity estimation for Florida freeways

Ashish Kulshrestha

Papers

Robust Shelter Locations for Evacuation Planning with Demand Uncertainty

Pick‐up locations and bus allocation for transit‐based evacuation planning with demand uncertainty

Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH

Impact of Left-Turn Spillover on through Movement Discharge at Signalized Intersections:

Investigation of freeway capacity : (a) effect of auxiliary lanes on freeway segment volume throughput and b) freeway segment capacity estimation for Florida freeways