Implementation of driverless vehicle at Flinders University’s Bedford Park campus

Author: . Sukhjinder Singh

Sukhjinder Singh, ., 2020 Implementation of driverless vehicle at Flinders University’s Bedford Park campus, Flinders University, College of Science and Engineering

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Abstract

The development and implementation of Autonomous vehicles (AVs) have made great progress in recent years. It is expected that they will play an important role in future transport systems as one of the key components in the next transport technology revolution. This paper describes the proposed implementation of driverless vehicles in the Bedford campus of Flinders University. The study includes the planning of the appropriate route for autonomous vehicles in Bedford Park precincts and the provision of the associate shuttle stop locations. It also covers the investigation in the appropriate frequency of driverless shuttle transport services for commuters and residents. The aim of this research is to test the different routes in the campus and recommend the best option that would enable a good connection for students, faculty staff members and visitors to the main campus of Flinders University. The traffic microsimulation approach is adopted in this project that was carried out using the software package tool called AIMSUN. This software is used to evaluate a number of different key traffic performance indicators including travel time, delay, number of bus stops, the direction of travel for specified route etc. The decision to use AIMSUN is made on the basis of this software package being adopted as the main microsimulation tool by the State Transport Agency in South Australia. The modelling methodology included the development of the existing network conditions and more than a dozen different alternative scenarios covering two different driverless vehicle routes for morning peak modelling period (8:00 AM-10:00 AM). The first route was the main campus Ring Road route and the second one was the current pedestrian path around the Central Campus lake. It was decided to first test the models that do not require any infrastructure upgrades and using current maximum operational speeds of 20 km/h for the driverless vehicles. Following this, the sensitivity analysis using AV speeds in the range of 20-50 km/h was performed. Both directions of travel, clockwise and counterclockwise were assessed on both routes. Each of the scenarios was run with 5 replications and using the random seed numbers as per the Department of Planning, Transport and Infrastructure (DPTI’s) Aimsun Manual specifications. The output of each scenario was recorded for comparison and evaluation of best performing scenario. In total, 18 alternative network scenarios were tested on both routes iv for both directions of travel, different number of bus stops and different maximum speeds of driverless vehicles. Initially, the outer Ring Road route with the length of 2,337.03 m was tested with 12 different scenarios with respect to speed, the direction of travel and indented and non-indented bus stops. A significant increase in vehicle delays of 73 percent was observed if no indented bus stops were provided and the current maximum driverless vehicle speed of 20km/h was adopted. Most of that delay was attributed to bus stop locations which have led to the recommendation to provide indented bus stops. Further investigation was conducted with the AVs being provided with the indented bus stops and using the current maximum speed of 20 km/h. Although the vehicle delays were reduced slightly, still significant delays were recorded to other vehicles as they were travelling behind the AVs since their speeds were significantly lower than the posted speed limit of 50km/h. An additional AV maximum speed sensitivity analysis was performed to measure the effects they are having on other conventional vehicles. The analysis included testing the speeds in the range of 20-50 km/h with the step of 5 km/h. It was shown that the AVs would cause a significant delay and disruption to other vehicles unless the top speed of the AVs can be increased to at least 40 km/h. This is the reason that the recommendation was made for AVs not be running on Ring Rd until the technology is improved so that the AVs can be run safely with an increased maximum speed of 40-50km/h. Since both directions of travel were tested for both alternative routes, the modelling results have shown that the counterclockwise direction in both cases performed better when compared with clockwise direction. Final modelling scenarios involved running the AV service off-road, using the existing pedestrian footpath along the Campus Central Park Lake. Six different scenarios with respect to the direction of travel and options with 3 and 5 stops along the route were developed. The results have shown that the travel time to complete one loop is approximately 8 minutes if the speed limit of 10km/h and 5 stops were used. However, if the 3 stops only were served the run travel time would decrease by 15 percent to around 6.8 minutes. Similarly, the scenario with the footpath speed limit of 20km/h would result in a reduction to travel times of 23.72 percent if only 3 bus stops were used. v Further study was conducted to evaluate the capacity of the Lake route in terms of the maximum number of passengers that it could be served. This study has shown that the minimum travel time of 4.5 (minute/run) can be achieved which means that a maximum of 13 runs per hour is feasible. Using the capacity of the current Flinders Navya shuttle of 15 passengers the entire route capacity would be 195 passengers per hour assuming that only one shuttle was used. The final recommendation of the study was to implement the AV service around the Central Lake in contraclockwise direction and not use the Ring Road route until the technology is improved and the maximum AV speeds increased to 40-50 km/h.

Keywords: Driverless Vehicle, Transport modelling, Microsimulation, Aimsun Mobility

Subject: Engineering thesis

Thesis type: Masters
Completed: 2020
School: College of Science and Engineering
Supervisor: Branko Stazic