Using Empirical Data to Find the Best Measure of Travel Time Reliability

ABSTRACT The value of travel time savings (VTTS) is often the largest benefit from transportation projects and has been studied extensively. Recently, additional attention has been paid to the fact that travelers also benefit from reliable travel times. The value of reliability (VOR) has usually been estimated through stated preference data or survey based revealed preference data. In this research, empirical data was used to estimate VOR. One concern regarding estimating VOR from empirical data is the lack of a definitive measurement for reliability. Should it be the standard deviation of travel time, the 95 th percentile, or another measure? Data from Katy Freeway, where travelers choose between tolled but generally more reliable lanes and free but generally less reliable lanes, were used in an attempt to find the best measurement of reliability that could lead to the best explanation of travelers' lane choice. Multinomial logit models were used to estimate travelers' lane choice based on trip attributes including travel time, many different measures of travel time reliability, and toll. Models including only travel time and toll yielded reasonable results and value of times ($2.78/hr,$9.09/hr, and $10.52/hr for off-peak, shoulder, and peak-period, respectively). However, adding reliability to the models caused many to have counter-intuitive results and it was not possible to conclude which measure is the best. Also, the results of this research suggest that reliability might not be an influential factor in lane choice decision on managed lanes, at least when travelers have reasonable knowledge of their potential travel time. Alemazkoor et al. Page 2 INTRODUCTION Reliability of travel time can be described as the variability of travel time either during a day or variability from day to day. Seven sources for variability in travel times have been identified: inadequate base capacity, demand fluctuations, traffic control devices, incidents, work zones, weather and special events (1). Reliability of travel time has been found to be an important factor in route choice of travelers (2, 3, and 4). Travel time reliability is more critical for trips with time constraints, such as trips to work. For such trips delays and late arrivals may have serious consequences, but arriving early is also undesirable. Travel time reliability is becoming more critical for travelers, shippers and transport agencies as traffic and congestion worsen. When an element is important for the transportation systems' users, it must be important for transportation planners as well and should be considered during the transportation planning process. Not considering the benefit that users gain from improved reliability might lead to sub-optimal planning decisions as a result of underestimating benefits from a transportation project. Due to fiscal constraints on transportation infrastructure expenditures, many transportation planning agencies are examining managed lanes (MLs) as a viable option that provides travel time savings and reliability to travelers with high values of time (VOT) and high values of reliability (VOR). MLs provide travelers a tolled but generally uncongested option while the general purpose lanes (GPLs) are free but might be congested. For those agencies that invest in MLs, it is important to predict how travelers choose between MLs and GPLs. This requires a good estimation of how travelers value the travel time and reliability offered by MLs. Although VOT has been studied extensively, studying VOR is relatively new and there are many uncertainties about it. The first question about travel time reliability is how it should be measured. A reliability measure is needed to conduct a cost/benefit analysis or a before/after study for a project which may improve reliability. Furthermore, to understand how the travelers value reliability, it is first necessary to find out how they perceive reliability. Different measurements are suggested for travel time reliability including standard deviation, variance, 90 th or 95 th percentile, percent variation, misery index, buffer index, travel time index, planning time index, shorten right range, interquartile range, and frequency that congestion exceeds some expected threshold (these will be defined in greater depth later in the paper and outlined in Revealed data from travelers on Katy Freeway, where travelers choose between MLs and GPLs, was used to examine which of these measures most closely resembles how travelers perceive travel time reliability. The dataset used in this research includes all travel information of those trips made on Katy Freeway by vehicles which have a transponder in April 2012. Therefore, the start time, travel time, travel length, cost (toll) and lane choice of each trip for a particular vehicle (known individually by transponder identification) on Katy Freeway in April 2012 were available. This dataset was developed from automated vehicle identification (AVI) sensors which records the transponder ID and detection time of the vehicles. Transponder IDs were randomized for use in this analysis. Therefore, it was impossible to identify who made the actual trip, but it was possible to identify specific vehicles and their trips over the month. Travel time reliability for the MLs and GPLs of Katy Freeway were calculated using different measurements of reliability. Discrete choice models were developed using these reliability measurements along with other trip attributes such as travel time and toll. The best measurements of reliability were those included in the model that best explained travelers' lane choice. As the final step, VOT and VOR were estimated