Levin, Michael W.

Some school districts schedule elementary schools with early start times for various reasons. Such start times sometimes necessitate travel before sunrise during winter months. Intuitively, this could potentially conflict with a desire for increased use of active transportation, e.g. from the Safe Routes To School program, to reduce motor vehicle travel and associated traffic congestion from driving students to school. Since prior literature has identified that parents are concerned about child safety around traffic, it is possible that travel before sunrise (where visibility is reduced) would also be a concern to parents and further discourage active transportation. To answer this question, we conducted a stated preference survey of parents about their child's travel choices, asking parents to rank the importance of various factors including travel before sunrise. Due to concerns about whether stated parental preferences would align with actual behavior, we also conducted a revealed preference survey using StreetLight data on travel to elementary schools. Survey distribution and data collection occurred in February in Minnesota, during a period of late sunrise. Overall, the results from all data analyses are aligned. Early school start times were associated with slightly higher use of active transportation in both stated and revealed travel patterns. Parents ranked travel before sunrise only as a moderate concern behind distance, infrastructure, crossing busy roads, and child's age. We did not find data to conclude that travel before sunrise significantly limits use of active transportation.

Running red traffic signals is a major cause of traffic collisions and resulting injuries and fatalities. Despite extensive prior work on systems to reduce red light violations, they continue to be a major problem in practice, partly because existing systems suffer from the flaw of providing the same guidance to all drivers. As a result, some violations are avoided, but other drivers ignore or respond inappropriately to red light running systems, resulting in safety issues overall. We present a novel method of providing accurate warnings to individual drivers to avoid the broad guidance approach of most existing systems. Recognizing if a driver will run red lights is highly dependent on signal phase and timing, traffic conditions along the road, and individual driver behavior, the proposed warning system contains three parts: a traffic prediction algorithm, an individual warning signal optimizer, and a driver warning display. The traffic prediction algorithm predicts future traffic states along the road towards the signalized intersections using the latest traffic conditions obtained through vehicle-to-vehicle and vehicle-to-infrastructure communications. Then, an optimization problem is formulated to compute the optimal warning signal based on predicted traffic states and driver reaction model. Finally, the optimal warning signal is shown on the display screen to advise driver on how much braking is needed to avoid running the red light. The results of both simulated driving scenarios and real-world road tests show that the proposed system provides more effective and accurate warning signals to drivers, helping them avoid running red lights.

Max-pressure (MP) traffic signal control is a new and innovative control algorithm that uses upstream and downstream vehicle counts to determine signal timing that maximizes throughput. While this method has been extensively tested in simulation, it has not yet been tested on actual traffic signals in the US. To close this gap, this report presents the results of the development of a hardware-in-the-loop traffic signal testbed where microsimulation is used to simulate realistic traffic conditions, and the MP algorithm is used to control the signal display using a traffic controller (Q-Free MaxTime controller). The hardware-in-the-loop results demonstrate that MP can be safely deployed on North American traffic signal control hardware.

The objective of this methodology is to refine the preliminary results from previous work (11% fuel savings for one vehicle, one intersection) to an entire corridor of SPaT signals, with different CV market penetration, and with driver awareness of fuel savings benefits. The research will proceed in three parts. First, several vehicles will be instrumented with DSRC receivers and GPS tracking to record SPaT data and the vehicle trajectories together. Offline, the project team will optimize the speed and powertrain control based on recorded SPaT data, using the recorded vehicle trajectories to identify the constraints of traffic flow. A living lab consisting of a GM car engine loaded by a transient hydrostatic dynamometer will be used to measure the fuel consumption with and without speed control. Second, the project team will conduct traffic flow simulations to study the impacts of higher market penetration on the overall fuel benefits, including the benefits to legacy vehicles which unintentionally use SPaT based speed controls by following CVs. Third, network models will be used to predict changes in route choices as drivers recognize the benefits of fuel savings in the route utility. The numerical predictions of fuel savings will be combined into cost/benefit analyses to inform MnDOT on the future deployment of SPaT on other corridors.

Max-pressure control is a new adaptive method for signal timing that is mathematically proven to achieve maximum throughput for the entire city road network. This throughput guarantee is nevertheless achieved by a decentralized control algorithm that depends only on local traffic information and is easy to compute. These mathematical properties suggest high potential for use in Minnesota, but the method’s performance in practice is not well-known. Furthermore, it lacks some practical constraints on signal timing that could cause confusion to drivers. This project conducted methodological improvements and simulation experiments on a calibrated model of 7 intersections in Hennepin County. We modified the theory behind max-pressure control to model first-in-first-out behaviors on lanes shared by multiple turning movements, and to force max-pressure control to follow a signal cycle. After making these significant methodological improvements, we proved that the maximum throughput properties still hold. Then, we calibrated SUMO (Simulation of Urban MObility) microsimulation models of 2 Hennepin County corridors with 7 intersections using signal timing data and 15-minute observed counts, and compared different versions of max-pressure control with existing actuated-coordinated signals. We varied the maximum cycle length and the time step (signal phases can only change once per time step). The performance depended on the control parameters. Overall, for most intersections and demand periods, we were able to find max-pressure control settings that significantly improved over current signal timings. Large reductions in delay (sometimes over 50%) suggested that max-pressure signal timing both achieved higher throughput during peak demand and was more responsive to queues.

Basic Safety Message (BSM) containing data about the vehicle's position, speed, and acceleration. Roadside receivers, RSUs, can capture BSM broadcasts and translate them into information about traffic conditions. If every vehicle is equipped with awareness, BSMs can be combined to calculate traffic flows, speeds, and densities. These three key parameters will be post-processed to obtain queue lengths and travel time estimates. The project team proposed a traffic state estimation algorithm using BSMs based on the Kalman filter technique. The algorithm's performance was tested with BSMs generated from several arterial in a microscopic simulation model and BSMs generated with radar data collected on freeway sections. Then the project team developed a traffic monitoring system to apply the algorithm to a large-scale network with different types of roads. In the system, computers could remotely access the online server to acquire BSMs and estimate traffic states in real-time.