An Overview of Vehicle-to-Infrastructure Communication Technology

As a part of solutions to reduce problems associated with transportation in cities, technologies can have noticeable impacts. Due to efficiency and low costs, innovative transportation technologies can reshape and improve human’s transportation. This research aims to explore Vehicle-to-Infrastructure communication technology (V2I) and its benefits to safety, mobility, and environment. In addition, it explores the planning aspect of deploying V2I technology and its opportunities, challenges and concerns, and implication to communities. The research will also look at several case studies including pilot projects that have been taking place in the United States and studies that have been done to have a better understanding of the current situation of V2I technology and its future needs. Advisor: Rodrigo Cantarer

Traffic Safety Primer for Local Agencies

The purpose of this booklet is to empower local agency personnel to make informed decisions that can improve roadway safety in your community. By identifying and addressing potential roadway hazards, you can reduce the likelihood of a future traffic crash for your community and your family. Adapted by permission from the Michigan LTAP’s 2008 Publication What Elected Officials Need to Know About Traffic Safety (And What YOUR Constituents Expect YOU to Know!) This is an update of the 2014 version and includes a section on roadway departure crashes

Traffic Safety Primer for Local Agencies

The purpose of this booklet is to empower local agency personnel to make informed decisions that can improve roadway safety in your community. By identifying and addressing potential roadway hazards, you can reduce the likelihood of a future traffic crash for your community and your family. Adapted by permission from the Michigan LTAP’s 2008 Publication What Elected Officials Need to Know About Traffic Safety (And What YOUR Constituents Expect YOU to Know!

Pedestrian Behavior Study to Advance Pedestrian Safety in Smart Transportation Systems Using Innovative LiDAR Sensors

Pedestrian safety is critical to improving walkability in cities. Although walking trips have increased in the last decade, pedestrian safety remains a top concern. In 2020, 6,516 pedestrians were killed in traffic crashes, representing the most deaths since 1990 (NHTSA, 2020). Approximately 15% of these occurred at signalized intersections where a variety of modes converge, leading to the increased propensity of conflicts. Current signal timing and detection technologies are heavily biased towards vehicular traffic, often leading to higher delays and insufficient walk times for pedestrians, which could result in risky behaviors such as noncompliance. Current detection systems for pedestrians at signalized intersections consist primarily of push buttons. Limitations include the inability to provide feedback to the pedestrian that they have been detected, especially with older devices, and not being able to dynamically extend the walk times if the pedestrians fail to clear the crosswalk. Smart transportation systems play a vital role in enhancing mobility and safety and provide innovative techniques to connect pedestrians, vehicles, and infrastructure. Most research on smart and connected technologies is focused on vehicles; however, there is a critical need to harness the power of these technologies to study pedestrian behavior, as pedestrians are the most vulnerable users of the transportation system. While a few studies have used location technologies to detect pedestrians, this coverage is usually small and favors people with smartphones. However, the transportation system must consider a full spectrum of pedestrians and accommodate everyone. In this research, the investigators first review the previous studies on pedestrian behavior data and sensing technologies. Then the research team developed a pedestrian behavioral data collecting system based on the emerging LiDAR sensors. The system was deployed at two signalized intersections. Two studies were conducted: (a) pedestrian behaviors study at signalized intersections, analyzing the pedestrian waiting time before crossing, generalized perception-reaction time to WALK sign and crossing speed; and (b) a novel dynamic flashing yellow arrow (D-FYA) solution to separate permissive left-turn vehicles from concurrent crossing pedestrians. The results reveal that the pedestrian behaviors may have evolved compared with the recommended behaviors in the pedestrian facility design guideline (e.g., AASHTO’s “Green Book”). The D-FYA solution was also evaluated on the cabinet-in-theloop simulation platform and the improvements were promising. The findings in this study will advance the body of knowledge on equitable traffic safety, especially for pedestrian safety in the future

Route Segment Level Analysis of Bus Safety Incidents

This paper analyzes collision and non-collision incidents that occurred on TriMet’s bus system over a near two-year period. The bus route network was decomposed into stop and line haul segments, and a typology of models was estimated from segment level incident, risk exposure, and roadway feature data. The frequency of non-collision incidents – mainly slips, trips and falls – was estimated to be primarily related to associated risk exposure variables. The frequency of collision incidents was also estimated to be related to risk exposure variables, as well as a number of roadway design variables. The findings serve as an initial step in informing the safety planning process

Modeling pedestrian safety at roundabouts

This study proposes a method for using a human participant in a field experiment to model pedestrian safety at roundabouts in the United States. Studies show that roundabouts are safer for vehicles, but are inconclusive as to whether pedestrians are at greater risk at roundabouts than at signalized intersections. Recent simulations, including virtual reality, can model pedestrian vehicle interaction, but the proposed technique could use real-world data to calibrate these models. Eight hours of video was made to gather data at a signalized intersection and a roundabout. A physical simulation was used to assess the pedestrian’s cross/don’t cross decision. Standard walking pace was simulated at 3.5 feet per second and a disabled pedestrian at half that pace. This study focused on factors such as signalization, approach streams, exit vs. entrance lanes, pace and direction to provide a realistic picture of the cross vs. don’t cross decision. Data showed that slow pedestrians had a significantly higher rate of don’t cross decisions at the roundabout. Roundabouts are thought to be safer for pedestrians than signalized intersections due to a lower number of conflict points, but the confusing multiple streams of roundabout traffic converging on exit lanes and the frames of approaching traffic at roundabout entrances may mean that another concept may be needed to fully capture pedestrian risks. The data on ‘relevant traffic’ showed that pedestrians had to be attentive to almost six times as many approach streams of traffic in the roundabout as in the signalized intersection. The value of this study is four-fold: 1) Future studies could revisit the conflict point at the core of Traffic Conflict Analysis and consider conflict streams as well; 2) Future studies could consider the cross/don’t cross decision as an important data point with which to evaluate the safety of roundabout crossings; 3) Slow pedestrians fared worse in their ability to cross at the roundabout than at the signalized intersection; 4) The human participant in a field experiment method can be a valuable source of data for calibrating pedestrian safety simulation systems

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

driver pedestrian interaction under different road environments

Abstract The objective of the present study was to analyze the drivers' behavior while approaching pedestrian crossings under different driver – pedestrian interaction conditions and to assess the effectiveness of Advanced Driving Assistance Systems (ADASs) for pedestrian detection among several road environments. Three different road environments were implemented in a fixed-base driving simulator: urban road, sub – urban road and rural road. Several driver – pedestrian interactions were implemented in addition to the pedestrian absence condition. The simulated ADAS provided a visual – auditive message. Forty – five participants drove the three road environments scenarios in which three pedestrian crossroads were implemented (pedestrian absence, pedestrian presence with ADAS and pedestrian presence without ADAS). Overall, 369 driver speed profiles were plotted from 150 m before each pedestrian crossroad. ADAS affected the driver behavior in the interaction conditions with Time-To-Zebraarrive 6 s). The effect of ADAS among the road environments was similar for the urban and sub – urban road, resulting in a less abrupt braking maneuver that began in advance compared to that adopted in ADAS absence condition. For the rural road, the main effect was the reaching of a lower minimum speed near the pedestrian crossing and an advanced end of braking maneuver, highlighting the ability of the driver to complete a safer and effective yielding maneuver